(4)

(5)

(6)

(7)

RESULTS AND DISCUSSION

Consecutive batch filtration with a kaolin suspension and a WWTP influent

Figure 2 shows the permeability of each GDM system as a function of the cumulative filtrate volume for tests with the 200 mg/L kaolin suspension and the WWTP influent. The closed symbols indicate the permeability after maintenance cleaning.

Figure 2(a) shows the permeability variation of each GDM system with the kaolin suspension. For the E-GDM system, the initial permeability was 13.8 LMH/kPa. The permeability decreased to 87.8% of the initial permeability during the filtration of 381 L, after which the permeability increased to 90.7% after maintenance cleaning was conducted once during the operation of the system. For GDM-1, the initial permeability was 10.8 LMH/kPa. The permeability in this case decreased to 31.2% of the initial water permeability during the filtration of 420 L. The permeability increased to 61% due to the maintenance cleaning step. The initial permeability of GDM-2 was 3.96 LMH/kPa, and the permeability decreased to 84.8% of the initial water permeability during the filtration of 362 L. After conducting maintenance cleaning 12 times, the permeability was restored to the initial permeability.

Figure 2(b) shows the variation of the permeability of each GDM system with the WWTP influent. The permeability of the three GDM systems decreased sharply to less than 1 LMH/kPa during the first batch due to the high turbidity and DOC concentration of the WWTP influent. The permeability of the E-GDM system decreased to 7.2% of the initial permeability during the filtration of 394 L, and the permeability increased to 44.1% after each of the two maintenance cleanings. The permeability of GDM-1 decreased to 3.7% of the initial permeability during the filtration of 308 L. Maintenance cleaning was conducted nine times during the filtration process, and the permeability increased to approximately 19.9%. The permeability of GDM-2 decreased to 2.6% of the initial permeability during the filtration of 200 L. Maintenance cleaning was conducted 24 times in this case, leading to a permeability increase of 46.3%.

Figure 3 shows the variation of the flux at 20 °C for each GDM system as a function of the cumulative filtrate volume for tests with the 200 mg/L kaolin suspension and the WWTP influent. The closed symbols indicate the flux after maintenance cleaning.

Figure 3

Variations in the flux at 20 °C as a function of the cumulative filtrate volume of E-GDM (circle), GDM-1 (triangle), and GDM-2 (square) with (a) 200mg/L of the kaolin suspension and (b) the WWTP influent. The closed symbols reveal the permeability or flow rate after maintenance cleaning. Chemical cleaning was not applied.

Figure 3

Variations in the flux at 20 °C as a function of the cumulative filtrate volume of E-GDM (circle), GDM-1 (triangle), and GDM-2 (square) with (a) 200mg/L of the kaolin suspension and (b) the WWTP influent. The closed symbols reveal the permeability or flow rate after maintenance cleaning. Chemical cleaning was not applied.

Figure 3(a) shows the flux variation of each GDM system with the kaolin suspension. For the E-GDM system, the initial flux was 63.7 LMH and, because of the water pressure, the flux increased and decreased repeatedly and the flux decreased to 40.5 LMH during the filtration of 381 L. After maintenance cleaning, the flux increased to 95.4% compared to the initial flux. For GDM-1, the initial flux was 61.5 LMH and the flux decreased to 13.3 LMH during the filtration of 420 L. The flux recovered to 86.9% compared to the initial flux due to maintenance cleaning. For GDM-2, the initial flux was 52.4 LMH, and the flux decreased to 84.9% of the initial flux during the filtration of 362 L.

Figure 3(b) shows the variation of the flux of each GDM system with the WWTP influent. The flux of the E-GDM system decreased from 37.6 LMH to 1.1 LMH during the filtration of 394 L. The flux increased to an average of 44.0% after each of the two maintenance cleanings. For GDM-1, the flux decreased from 84.5 LMH to 2.2 LMH during the filtration of 308 L, and after nine rounds of maintenance cleaning, the flux increased to 19.9% on average, compared to the initial flux. For the GDM-2, the flux decreased from 55.8 LMH to 18.7 LMH during the filtration of 200 L. Maintenance cleaning was conducted 24 times, and the flux increased to approximately 51.1% compared to the initial flux.

Figure 4 shows the variation of the flow rate of each GDM system as a function of the cumulative filtrate volume for tests with the 200 mg/L kaolin suspension and the WWTP influent. The closed symbols indicate the flow rate after maintenance cleaning.

Figure 4

Variations in the flow rate as a function of the cumulative filtrate volume of E-GDM (circle), GDM-1 (triangle), and GDM-2 (square) with (a) 200mg/L of the kaolin suspension and (b) the WWTP influent. The closed symbols reveal the permeability or flow rate after maintenance cleaning. Chemical cleaning was not applied.

Figure 4

Variations in the flow rate as a function of the cumulative filtrate volume of E-GDM (circle), GDM-1 (triangle), and GDM-2 (square) with (a) 200mg/L of the kaolin suspension and (b) the WWTP influent. The closed symbols reveal the permeability or flow rate after maintenance cleaning. Chemical cleaning was not applied.

Figure 4(a) shows the filtration flow rate versus the cumulative filtrate volume of each GDM system. For the E-GDM system, the flow rate fell from 23.04 L/h to 14.64 L/h during the filtration of 381 L. The average flow rate was 17.96 L/h. The flow rate of GDM-1 decreased from 12.35 L/h to 2.68 L/h during the filtration of 420 L. The average flow rate was 6.28 L/h. For GDM-2, the flow rate was reduced from 15.63 L/h to 13.39 L/h during the filtration of 362 L. The average flow rate was 12.90 L/h. The mean flow rate after filtration of over 18,000 L, which is the guaranteed filter life, was 8.8 L/h for artificial water that contained 15 NTU of turbid matter and 5 mg/L of humic acid (Clasen et al. 2009).

Figure 4(b) shows the filtration flow rate according to the filtration volume of each GDM system. The flow rate of the E-GDM system decreased from 13.60 L/h to 0.71 L/h during the filtration of 394 L, and the average flow rate was 2.81 L/h. The flow rate of GDM-1 decreased from 16.77 to 0.42 L/h during the filtration of 308 L, and the average flow rate was 1.65 L/h. The flow rate of GDM-2 decreased from 16.40 to 5.49 L/h during the filtration of 200 L, and its average flow rate was 3.94 L/h.

In summary, the E-GDM system showed the highest average permeability and thus would facilitate the highest production level at the same pressure condition among the GDM systems tested here. Tumwine et al. (2002) reported that 5 L of safe water per capita is needed for daily drinking and cooking in low- and middle-income countries and that an additional 7 L per capita is needed for bathing and personal hygiene. For a five-person family, 25 L of safe water is required for drinking and cooking. A total of 60 L of water is needed for drinking, cooking, bathing, and personal hygiene. The E-GDM, GDM-1, and GDM-2 systems could produce 215.52 L, 75.36 L, and 154.8 L of filtrate, respectively, when operating during 12 h of daytime. For filtration with the kaolin suspension, all the GDM systems could meet the minimum water requirement and family basic hygiene requirement. For the filtration with WWTP influent, The E-GDM, GDM-1, and GDM-2 systems could produce 33.74 L, 19.80 L, and 47.28 L of filtrate, respectively, during operation for 12 h of daytime. The E-GDM and GDM-2 systems could meet the daily minimum water requirement for a five-person family. However, GDM-1 could not do so for such a family during 12 h of operation.

The feed water turbidity of the kaolin suspension was 118.1 ± 15.0 NTU, and that of the filtrate was 0.09 ± 0.03 NTU, 0.14 ± 0.04 NTU, and 0.13 ± 0.04 NTU for the E-GDM, GDM-1, and GDM-2 systems, respectively. For the WWTP influent, the turbidity of the raw water was 117.6 ± 46.5 NTU, and that of the filtrate was 0.11 ±0.03 NTU, 0.23 ± 0.09 NTU, and 0.16 ± 0.08 NTU in the E-GDM, GDM-1, and GDM-2 cases, respectively. The E. coli colonies were 2,290,000 CFU/100 mL in the WWTP influent, whereas E. coli was not detected in the filtrates of the three GDM systems. World Health Organization (WHO) regulations state that the turbidity should be less than 5 NTU, and E. coli should not be present in drinking water (WHO 2008). For all the filtrates here, it was therefore confirmed that the levels of turbidity and E. coli met the corresponding drinking water standard.

The lifespan of the E-GDM system with the WWTP influent

Membrane lifespan is one of the most important issues related to the cost of the membrane system. Figure 5 shows the permeability changes of the E-GDM system during filtration of the WWTP influent with maintenance and chemical cleanings every five batches. The cleanings were effective for maintaining the operation of the module over 100 batches, but the permeability values after the chemical cleanings decreased gradually, as shown by the gray circles in Figure 5. The maximum lifespan of the E-GDM system was estimated by extrapolating the permeability trend and determining the number of chemical cleanings until the time when the flow rate after chemical cleaning was expected to be less than 25 L/d, which corresponds to an average permeability of 0.62 LMH/kPa for the E-GDM system. It was determined that 131 cleanings would be necessary. Considering that the system could complete 48 batches without any chemical cleaning, as shown in Figure S1 in the Supporting Information, the estimated maximum lifespan was 131 × 48 batches (between chemical cleanings), i.e. 6,288 batches, corresponding to 8.61 years at two batches (25 L) per day. Considering the guaranteed filtration quantities of GDM-1 and GDM-2 were 10,000 L and 18,000 L, respectively, and thus the guaranteed membrane lifespans for GDM-1 and GDM-2 provided by each manufacturer were 1.10 years and 1.97 years when filtrating 25 L/d, respectively, it was concluded that the E-GDM system could be operated 7.82 and 4.37 times longer than GDM-1 and GDM-2, respectively.

Figure 5

Estimation of the lifetime of the E-GDM with 3,000ppm sodium hypochlorite chemical cleanings. Gray circles denote the permeability after maintenance and chemical cleaning.

Figure 5

Estimation of the lifetime of the E-GDM with 3,000ppm sodium hypochlorite chemical cleanings. Gray circles denote the permeability after maintenance and chemical cleaning.

Filtration cost comparison

Table 3 shows the filtration cost of the GDM systems and other filtration systems for household water treatment. The capital cost requirements of the E-GDM, GDM-1, and GDM-2 systems were US$50, US$265.5, and US$69.09, respectively. The capital cost of GDM-1 was 5.3 times higher than that of the E-GDM system. The filter of the GDM-1 system should be replaced after 10,000 L of filtration, at a cost of about US$130/filter. The filtration cost was calculated using the corresponding guaranteed filtration volume from the manufacturer. The filtration costs per 1,000 L for the E-GDM, GDM-1, and GDM-2 systems were estimated at US$0.63, US$39.56, and US$3.84, respectively. Therefore, the annual costs of the E-GDM, GDM-1, and GDM-2 systems were calculated and found to be US$5.71, US$360.99, and US$35.02 per household. The annual cost per household of the E-GDM system was significantly lower than that of the other GDM systems.

Table 3

Cost comparison of filtration systems for household water treatment

E-GDMGDM-1GDM-2Biosand filterCeramic pot filterPersonal membrane filter
Capital cost (US$) 50 265.5 69.09 12–40 7.5–9.5 19.95 Replacement cost (US$) – 130.1 – – 2.5 –
Filtration cost per 1,000 L (US$/1,000 L) 0.63 39.56 3.84 – 1.2 4.99 Annual cost per household (US$/year/household) 5.71 360.99 35.02 5.48 11 45.51
E-GDMGDM-1GDM-2Biosand filterCeramic pot filterPersonal membrane filter
Capital cost (US$) 50 265.5 69.09 12–40 7.5–9.5 19.95 Replacement cost (US$) – 130.1 – – 2.5 –
Filtration cost per 1,000 L (US$/1,000 L) 0.63 39.56 3.84 – 1.2 4.99 Annual cost per household (US$/year/household) 5.71 360.99 35.02 5.48 11 45.51

The cost was also compared to those of other filtration systems for household water treatment. A biosand filter is one of simple water treatment systems for household water treatment. The capital cost has been estimated to range from US$12 to US$40 at an annual cost of US$5.48/household (Clasen 2009; Carvalho et al. 2011). The capital cost for a ceramic pot filter is relatively low compared to those of other filtration systems. However, it is fragile and has a flow rate of 1–3 L/h, even for low turbid water (Brown & Sobsey 2007). The annual cost was estimated to be US$11/household; however, with filter replacement instead of the purchase of a new filter, the estimated annual cost was US$2.5/household. The capital cost of a commercial personal membrane filter was US$19.95. The annual cost was estimated to be approximately US$45.51 in such a case, which is 4.14 times higher than that of the ceramic pot filter. The annual cost of a biosand filter was similar to that of the E-GDM system; however, the costs of the ceramic pot and the personal membrane filter were 2 and 8.3 times higher, respectively. The purchasing power of low- and middle-income countries The purchasing power per capita per year for safe drinking water was calculated from GDP data as mentioned above. Briefly, most of the people living in sub-Saharan Africa require US$2–US$25/capita/year to purchase safe drinking water. For the West, Middle and East Africa regions, people spend US$2–US$10/capita/year. In India and in Southeast Asia, people spend US$10–US$50/capita/year. For Latin America and the Caribbean, US$25–US$100/capita/year are required (see Figure S2 in the Supporting Information). Table 4 shows the average drinking water purchasing power by region. Sub-Saharan Africa can be classified into two groups due to the large GDP deviations by country. Class I is the group of countries for which the GDP is less than US$1,000, and class II is the group of countries for which the GDP ranges widely from US$1,000 to US$10,000. Countries for which the purchasing power exceeded US$100 were excluded for greater accuracy of the estimation during the classification step because most of these countries were those for which national incomes from tourism or oil accounted for the largest portion. The average drinking water purchasing power amounts for sub-Saharan Africa classes I and II are US$6.2 and US$26.5/capita/year, respectively. Thus, the average purchasing power amounts for a household (five people) were calculated and found to be US$31.2 and US$32.5/household/year, respectively. For Middle East Asia, North Africa, and Afghanistan, and for low- and middle-income countries in Asia and Oceania, the average purchasing power amounts were similar at US$162.5/household/year. For Latin America and the Caribbean, and for low- and middle-income countries in Europe, the average purchasing power amounts were US$277.5 and US$322.0/household/year, respectively.

Table 4

Average purchasing power by regional groupa

RegionSub-Saharan Africa
Middle East Asia, North Africa, and AfghanistanLow- and middle- income countries in Asia and OceaniaLatin America and the CaribbeanMiddle-income countries in Europe
Class IbClass IIc
Average purchasing power per year per capita (US$/capita/year) 6.2 26.5 32.4 32.6 55.5 64.4 ADWPPH (US$/household/year) 31.2 132.5 162.0 163.0 277.5 322.0
Group
RegionSub-Saharan Africa
Middle East Asia, North Africa, and AfghanistanLow- and middle- income countries in Asia and OceaniaLatin America and the CaribbeanMiddle-income countries in Europe
Class IbClass IIc
Average purchasing power per year per capita (US$/capita/year) 6.2 26.5 32.4 32.6 55.5 64.4 ADWPPH (US$/household/year) 31.2 132.5 162.0 163.0 277.5 322.0
Group

aExcluded countries (with purchasing power exceeding US$100): (1) Class I and II: Seychelles and Equatorial Guinea; (2) Middle East Asia, North Africa, and Afghanistan: Qatar, UAE, Kuwait, Bahrain, Saudi Arabia, Oman, and Lebanon; (3) Low- and middle-income countries in Asia and Oceania: Brunei Darussalam and Palau; (4) Latin America and the Caribbean: The Bahamas, St. Kitts and Nevis, Trinidad and Tobago, Barbados, Uruguay, Antigua and Barbuda, Panama, Chile, Argentina, Costa Rica, and Venezuela; (5) Middle income countries in Europe: Poland, Hungary, and Croatia. bClass I: GDP less than US$1,000.

cClass II: GDP from US$1,000 to US$10,000.

Regions can be grouped according to the purchasing power. One group is sub-Saharan Africa class I, referred to here as the low purchasing power group (Group A, Table 4). This group requires, on average, US$31.2/household/year for safe drinking water. A second group is class II of sub-Saharan Africa, Middle East Asia, North Africa, and Afghanistan, as well as low- and middle-income countries in Asia and Oceania. This is referred to here as the moderate purchasing power group (Group B, Table 4). Group B spends an average of US$152.5/household/year on safe drinking water. A third group consists of Latin America and the Caribbean and middle-income countries in Europe, which is referred to here as the high purchasing power group (Group C, Table 4). Group C spends on average US$299.75/household/year for safe drinking water. For group A, three types of household water treatments can be used: a biosand filter, a ceramic pot filter, and the E-GDM system. The annual cost per household for GDM-1 and GDM-2 was higher than the purchasing power of Group A. For Group B, all types of water treatment systems can be used, except the GDM-1 and personal membrane filter. For Group C, all types of water treatment methods are feasible except the GDM-1. A consumer in this group can use two or more water treatment methods, such as chlorination (about US$2.28 to US$57.03/household/year, Carvalho et al. 2011) and filtration. Therefore, people in Group C are more likely to acquire safe drinking water. With regard to the capital cost of the GDM systems, the people in Group A cannot easily purchase the E-GDM, GDM-1, and GDM-2 systems directly. However, those in Group B have the potential to buy the E-GDM and GDM-2 systems directly. Only those in Group C can purchase all these systems given their spending power. The prevalence of an inexpensive household water treatment system would help families save money, rather than having to purchase the more expensive bottled water in low- and middle-income countries. The annual cost of bottled water from a water vendor is estimated to range from US$1.3 to US$32.0/household, and the average cost has been determined to be US$16.3/household for low- and middle-income countries (Manda 2009; World Bank 2009; Ahmad 2017). According to the results here, it appears to be possible to achieve levels of the UN Sustainable Development Goals 3.3, 3.9, and 6.1 by providing low- and middle-income countries with inexpensive household water treatment systems, including the E-GDM system. This can also help to ensure better child education and improve women's human rights by reducing the time required to fetch clean water.

CONCLUSIONS

Comparative filtration tests were carried out using a kaolin suspension and a WWTP influent with the E-GDM system and two commercialized GDM systems (GDM-1 and GDM-2) for household water treatment. The E-GDM system demonstrated the highest average permeability and flow rate among the GDM systems tested for both feed water cases. For filtration of the kaolin suspension, the E-GDM, GDM-1, and GDM-2 system met the daily minimum water requirement for a five-person family with daytime operation. For the WWTP influent, the E-GDM and GDM-2 systems met the minimum water requirement, whereas GDM-1 did not. The E-GDM system could produce turbid- and E. coli-free water to meet WHO guidelines, even for the WWTP influent. The ADWPPH varied regionally from US$31.2 to US$320 per year in low- and middle-income countries. Based on the purchasing power analyzed, together with the annual costs of the GDM systems, the E-GDM system with a biosand filter and a ceramic pot filter can be purchased by those in low-income countries classified according to their low purchasing power. GDM-2 can be purchased by countries with moderate to high purchasing power and GDM-1 can be purchased only by countries with high purchasing power. Therefore, the E-GDM system introduced here is competitive in terms of performance and cost compared to other commercialized GDM filters. In future, the E-GDM and other water treatment systems should be further tested at actual sites in low- and middle-income countries to confirm (1) the reduction in waterborne diseases, (2) the improvement of health and hygiene environments, and (3) the actual purchasing power of the water treatment systems for household drinking water.

ACKNOWLEDGEMENTS

This work was financially supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP), the Ministry of Trade, Industry, & Energy (MOTIE) of the Republic of Korea (No. 20184030202240), and also by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (2016R1C1B1009544).

SUPPLEMENTARY MATERIAL

The Supplementary Material for this paper is available online at https://dx.doi.org/10.2166/ws.2020.007.

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