This study examined the solid waste generation and recycling potential of the hotel sector in Hue City, Vietnam. The authors conducted waste measurement, waste composition, and questionnaire surveys for 45 target hotels over ten consecutive days. The waste generation rates (WGRs) by rooms, beds, guests, and workers were assessed by hotel class using the following three waste categories, considering informal waste collection: general waste (GW), separated recyclables (SRe), and separated food residue (SFR). The 5-star hotels exhibited the highest WGR per room at 1.61 kg/room/day, while 1-star hotels exhibited the lowest per-room WGR (0.39 kg/room/day). Spearman Rank correlation test revealed that hotel class and per-room, per-bed, and per-guest WGRs were significantly positively correlated (p < 0.01). The major components of GW were food waste (40.9% to 57.4%), paper (10.1% to 20.3%), and plastic (10.7% to 15.5%). The recycling and composting potentials remaining in the GW were 19.3% to 38.5% and 38.0% to 57.9%, respectively. Based on the WGRs and waste composition determined in this study, the estimated total amount of waste generated was 6.88 tons/day (6.26 to 7.62 tons/day, 95% CI), of which 4.37 (64%), 2.13 (31%), and 0.38 tons/day (6%) were GW, SFR, and SRe, respectively. The recycling and composting potentials remaining in GW were 0.94 (13%) and 2.57 tons/day (37%), respectively. High-class hotels should be considered as the highest priority targets for a “reduce, reuse, recycle” (3R) promotion campaign in the future, with estimated recycling and composting potentials of 0.27 (4%) and 1.10 tons/day (16%), respectively.
Rapid urbanization, economic growth, and changing lifestyles have drastically increased the amount and variety of municipal solid waste (MSW) in developing countries [
Municipalities in Vietnam need to establish a MSW management system that considers public health, the efficient use of organic and recyclable waste, and recycling activities by the informal sector. Williams (2005) suggested that accurate data concerning estimated present and future production and composition of different types of waste were essential for efficient and economical long-term waste management planning [
The hotel sector is a primary source of MSW [
Several studies have reported on the solid waste generation by Vietnam’s hotel sector, and two approaches have been adopted for estimating waste quantity and composition. One distributes a questionnaire survey to the waste generators, and the other directly measures waste at the point at which it is generated or at the treatment facility [
Hue City is a major tourism city in Vietnam and houses a UNESCO World Heritage Site, the Complex of Hue Monuments, inscribed in 1993. The authors selected Hue City as a study area to determine waste generation by the hotel sector. To provide scientific information for promoting the 3Rs (reduce, reuse, recycle) in the hotel sector, this study aims to determine the WGRs of hotel sector in Hue City by 3 categories: compostable, recyclable, and other materials; identify the factors influencing WGRs; and describe the waste flow in detail. To consider the amount of waste collected by the informal sector and determine differences between hotel classes, the authors determined the amount of waste, including recyclables and food residues, collected by the informal sector and surveyed 45 accommodation facilities covering all hotel classes. This study also presents an interval estimation of the total amount of waste and its’ components by Monte Carlo simulation. Uncertainty analysis was also conducted to understand the impact of the reliability of each waste flow component on the confidence interval of the total amount of waste.
Hue City, the capital city of Thua Thien Hue Province located in central Vietnam, was selected as the study area (
As a city with a UNESCO World Heritage Site, the number of tourists visiting Hue City rapidly increased at an annual growth rate of 10%, reaching 2.5 million in 2012. To fulfill the demands of the visitors, the number of accommodation
facilities also continually increased, reaching 402 facilities with 7762 rooms and 13,660 beds in 2012 [
To acquire representative samples of the hotel sector, the authors applied systematic sampling based on lists of hotels sorted by the number of beds. The lists were prepared separately for the abovementioned six classes, and the number of samples by hotel class is shown in
The survey procedure followed the methodology presented by Matsui et al. (2015) [
The authors requested the target facilities to keep their waste into the following three categories based on their typical separation manner:
− Separated recyclables (SRe): waste items separately kept for recycling, selling to the informal sector, or transferred to somewhere/someone else by the owners;
− Separated food residue (SFR): edible leftover food separately kept for feeding, collected by livestock breeders;
− General waste (GW): all remaining waste items collected daily by the formal waste collection sector, the Hue Urban Environment and Public Works State Company (HEPCO).
Hotel class | Facility | Room | Bed | Target sample |
---|---|---|---|---|
Guest house | 289 | 2511 | 4071 | 10 |
1-star hotel | 55 | 1071 | 2008 | 10 |
2-star hotel | 31 | 1156 | 2226 | 7 |
3-star hotel | 12 | 868 | 1615 | 8 |
4-star hotel | 11 | 1509 | 2750 | 7 |
5-star hotel | 4 | 648 | 990 | 3 |
Total | 402 | 7763 | 13,660 | 45 |
Source: General statistics office, 2015.
The authors assessed the waste separation rate at the target facilities based on their usual separation behavior, which was categorized into the following four patterns: 1) recyclables and food residue separation, 2) recyclables separation only, 3) food residue separation only, and 4) no separation.
Regarding the actual waste measurement survey, the surveyors daily visited all the target facilities and directly measured the amount of waste generated over 10 consecutive days. The first three days were spent preparing the surveyors and target facilities, and data from the following seven days were used for the analysis.
The waste composition survey was conducted to evaluate the recycling and composting potentials of GW. The authors selected 21 target facilities with recyclables and food residue separation. (The sample size by hotel class is shown in
− Recycling potential (Re): the recyclable portion of the discharged GW, defined based on Hue City’s current informal sector trading market in 2012;
− Composting potential (Co): the compostable portion of the discharged GW, referred from the acceptable items established by Vietnamese composting facilities;
− Non-recyclable (NRe): The remaining portions of GW after the abovementioned recycling and composting potentials were considered.
The authors also conducted a questionnaire survey at the target facilities. The attributes and influencing factors on waste generation and recycling activities were collected and used for further analytical procedures.
The WGRs were calculated by dividing the daily amount of waste generation by four business scale indicators: number of rooms, number of beds, number of
Category | Code | Details | Recycling potential | Category | Code | Details | Recycling potential |
---|---|---|---|---|---|---|---|
1. Plastic | 5. Grass and wood | ||||||
Container & Packaging | 101 | PET bottles | Re | Container & Packaging | 503 | Containers & packaging | Co |
102 | Other plastic bottles | Re | 503* | Containers & packaging | NRe | ||
103 | Tray | Re | Product & Others | 504 | Grass and wood products | Co | |
103* | Tray | NRe | 504* | Grass and wood products | NRe | ||
104 | Tube | Re | 6. Textile | ||||
104* | Tube | NRe | 601 | Clothes | Re | ||
105 | Other shapes | Re | 602 | Daily commodities | NRe | ||
105* | Other shapes | NRe | 603 | Disposed commodities | NRe | ||
106 | Shopping plastic bags | Re | 604 | Other product | Re | ||
107 | Other plastic packaging | Re | 7. Metal | ||||
108 | Other C&P | Re | Aluminum | 701 | Containers | Re | |
108* | Other C&P | NRe | 702 | Other containers and packaging | Re | ||
Product | 109 | Plastic products | Re | 702* | Other containers and packaging | NRe | |
109* | Plastic products | NRe | 703 | Products and others | Re | ||
Other plastics | 110 | Other plastics | Re | 703* | Products and others | NRe | |
110* | Other plastics | NRe | Steel | 704 | Containers | Re | |
2. Paper | 704* | Containers | NRe | ||||
Container & Packaging | 201 | Carton | Re | 705 | Other containers and packaging | Re | |
202 | Containers | Re | 706 | Products and others | Re | ||
203 | Cardboard | Re | Stainless | 707 | Products and others | Re | |
204 | Packaging | Re | Lead | 707* | Products and others | NRe | |
205 | Other C&P | Re | Other metals | 708 | Other metals | Re | |
Product | 206 | Newspaper/poster | Re | 708* | Other metals | NRe | |
207 | Books | Re | 8. Glass | ||||
208 | Notebooks | Re | Container | 801 | Returnable bottle | Re | |
209 | Photocopy | Re | 802 | Disposal bottle | Re | ||
210 | Disposal paper products | NRe | 803 | Other containers | Re | ||
210* | Nappies/Diapers | NRe | Products and others | 804 | Thermometers, fluorescent lamp | NRe | |
211 | Other paper product | Re | 805 | Products and others | NRe | ||
211* | Other paper products | NRe | 9. Ceramic | ||||
Other Paper | 212 | Other Paper | Re | 901 | Containers | NRe | |
212* | Other Paper | NRe | 902 | Products and others | NRe |
3. Kitchen waste | 10. Miscellaneous | ||||||
---|---|---|---|---|---|---|---|
Compostable | 301 | Kitchen waste | Co | 1001 | Combustibles | NRe | |
Non-compostable | 301* | Coconut/Durian shells | NRe | 1002 | Liquids_edible | Co | |
302 | Hard animal bones | NRe | 1002* | Liquids_inedible | NRe | ||
4. Rubber and leather | 1003 | Incombustibles (no ash) | NRe | ||||
401 | Rubber and leather | NRe | 1004 | Ash | NRe | ||
5. Grass and wood | 1005 | Medical care | NRe | ||||
Garden waste | 501 | Garden waste | Co | 1006 | Batteries | NRe | |
501* | Garden waste | NRe | 1007 | E-waste | NRe | ||
502 | Flower | Co | 1008 | Others | NRe |
*: Non-recyclable waste.
workers (including managers and serving workers), and number of guests as follows:
W G R i = D W A T N i (1)
where:
WGRi: Waste generation rate of each target hotel by four indicators: waste generation amount per room, that per bed, that per worker, and that per guest;
DWA: Daily amount of waste generation of each target hotel;
TNi: Total number of unit of each target hotel by four indicators: number of rooms, number of beds, number of workers, and number of guests.
To determine whether the WGRs followed a normal/Gaussian distribution, the authors applied a Shapiro-Wilk test [
In this study, the WGRs are reported as the mean with the 95% confidence interval (95% CI). Non-parametric bootstrap with replacement sampling method was applied to determine the 95% CI [
The composition of GW was analyzed using the categories and sub-categories listed in
To establish the solid waste stream from the hotel sector in Hue City, the authors estimated the total amount of generated waste, as well as its components by hotel class based on the WGR, waste separation rate, and waste composition survey results collected in this study. The detailed procedure is introduced in Section 3 after these results are elaborated.
The waste separation rates of the target samples are summarized in
W S R i j = N H S i j T N H j (2)
where:
WSRij: waste separation rate of separation pattern i of hotel class j;
NHSij: number of facilities with separation of separation pattern i of hotel class j;
TNHj: total number of facilities of hotel class j.
The results show that most of the target hotels (43 of 45 facilities) separated their waste. All 3- to 5-star hotels separated recyclables and food residue, while the waste separation rates of GH and 1-star hotels were lower. This tendency seems to be consistent with that found in a study on the hotel sector in Cairo, Egypt, which reported that high-class hotels successfully sorted waste at its source [
WGRs are reported to differ between hotel classes, services, and regions [
Waste separation activity | GH | 1-star | 2-star | 3-star | 4-star | 5-star |
---|---|---|---|---|---|---|
Sample size (n) | 10 | 10 | 7 | 8 | 7 | 3 |
Recyclables and food residue | 10% | 40% | 86% | 100% | 100% | 100% |
Recyclables only | 70% | 30% | 14% | 0% | 0% | 0% |
Food residue only | 10% | 20% | 0% | 0% | 0% | 0% |
No separation | 10% | 10% | 0% | 0% | 0% | 0% |
Category | n | Total waste | GW | SRe | SFR | ||||
---|---|---|---|---|---|---|---|---|---|
Mean | 95% CI | Mean | 95% CI | Mean | 95% CI | Mean | 95% CI | ||
Total daily waste generation amount (kg/day) | |||||||||
Guest house | 10 | 5.3 | 3.8 - 7.0 | 4.2 | 2.8 - 5.9 | 0.5 | 0.3 - 0.7 | 0.6 | 0 - 1.4 |
1-star hotel | 10 | 7.8 | 6.0 - 9.8 | 5.5 | 4.3 - 6.8 | 0.7 | 0.3 - 1.0 | 1.6 | 0.6 - 2.7 |
2-star hotel | 7 | 30.1 | 21.7 - 38.4 | 15.5 | 12.4 - 18.6 | 1.8 | 1.4 - 2.4 | 12.8 | 7.2 - 18.9 |
3-star hotel | 8 | 68.8 | 58.8 - 179.0 | 36.3 | 33.9 - 86.6 | 2.5 | 4.3 - 11.8 | 29.9 | 19.3 - 83.9 |
4-star hotel | 7 | 190.5 | 151.9 - 231.7 | 102.1 | 81.4 - 126.9 | 10.8 | 7.0 - 14.9 | 77.6 | 58.5 - 97.2 |
5-star hotel | 3 | 271.8 | 223.1 - 490.6 | 162.8 | 146.5 - 220.8 | 14.9 | 9.1 - 42.1 | 94.0 | 55.4 - 234.5 |
K-W test (H value) | 38.058*** | 37.321*** | 31.669*** | 37.046*** | |||||
Spearman’s ρ | 0.917** | 0.906** | 0.813** | 0.899** | |||||
WGRs per room (g/room/day) | |||||||||
Guest house | 10 | 534 | 382 - 708 | 400 | 272 - 567 | 42 | 24 - 61 | 95 | 0 - 224 |
1-star hotel | 10 | 387 | 300 - 488 | 294 | 226 - 363 | 34 | 18 - 52 | 59 | 22 - 99 |
2-star hotel | 7 | 779 | 562 - 993 | 415 | 332 - 498 | 51 | 39 - 68 | 313 | 175 - 460 |
3-star hotel | 8 | 1155 | 987 - 3007 | 606 | 565 - 1443 | 42 | 71 - 196 | 507 | 328 - 1423 |
4-star hotel | 7 | 1455 | 1160 - 1770 | 769 | 613 - 956 | 86 | 56 - 119 | 600 | 452 - 751 |
5-star hotel | 3 | 1607 | 1319 - 2901 | 995 | 895 - 1349 | 85 | 52 - 240 | 526 | 310 - 1312 |
K-W test (H value) | 27.97*** | 22.31*** | 11.81*** | 27.49*** | |||||
Spearman’s ρ | 0.807** | 0.708** | 0.453** | 0.793** | |||||
WGRs per bed (g/bed/day) | |||||||||
Guest house | 10 | 487 | 333 - 668 | 369 | 234 - 548 | 42 | 24 - 61 | 75 | 0 - 187 |
1-star hotel | 10 | 265 | 194 - 339 | 206 | 144 - 273 | 21 | 11 - 32 | 38 | 14 - 61 |
2-star hotel | 7 | 379 | 315 - 444 | 211 | 178 - 245 | 27 | 20 - 34 | 142 | 82 - 199 |
3-star hotel | 8 | 613 | 711 - 2263 | 323 | 399 - 1110 | 22 | 48 - 150 | 268 | 254 - 1048 |
4-star hotel | 7 | 821 | 632 - 1007 | 431 | 337 - 535 | 49 | 31 - 69 | 341 | 246 - 431 |
5-star hotel | 3 | 1208 | 702 - 1528 | 757 | 445 - 710 | 63 | 28 - 126 | 388 | 165 - 691 |
K-W test (H value) | 24.31*** | 17.22** | 10.80* | 27.73*** | |||||
Spearman’s ρ | 0.779** | 0.573** | 0.291 | 0.833** | |||||
WGRs per guest (g/guest/day) | |||||||||
Guest house | 5 | 604 | 424 - 785 | 432 | 237 - 629 | 30 | 4 - 56 | 141 | 8 - 303 |
1-star hotel | 4 | 603 | 483 - 724 | 466 | 313 - 641 | 30 | 0 - 64 | 107 | 29 - 184 |
2-star hotel | 4 | 481 | 383 - 610 | 300 | 233 - 381 | 26 | 18 - 40 | 155 | 59 - 244 |
3-star hotel | 7 | 1706 | 1347 - 2136 | 963 | 754 - 1169 | 65 | 38 - 91 | 717 | 516 - 993 |
4-star hotel | 6 | 2322 | 1705 - 3112 | 1175 | 855 - 1504 | 147 | 107 - 192 | 1001 | 697 - 1456 |
5-star hotel | 3 | 6568 | 2583 - 10061 | 4162 | 1175 - 6148 | 301 | 223 - 409 | 2104 | 1185 - 3504 |
K-W test (H value) | 24.056*** | 20.108*** | 19.117** | 22.746*** | |||||
Spearman’s ρ | 0.747** | 0.645** | 0.746** | 0.809** |
WGRs per worker (g/worker/day) | |||||||||
---|---|---|---|---|---|---|---|---|---|
Guest house | 10 | 2144 | 1455 - 3170 | 1756 | 1057 - 2706 | 216 | 107 - 357 | 172 | 0 - 411 |
1-star hotel | 10 | 786 | 635 - 941 | 604 | 466 - 751 | 65 | 33 - 97 | 117 | 37 - 215 |
2-star hotel | 7 | 1431 | 904 - 2002 | 756 | 536 - 1016 | 88 | 68 - 111 | 587 | 247 - 934 |
3-star hotel | 7 | 1403 | 1075 - 6289 | 738 | 605 - 2957 | 53 | 15 - 338 | 611 | 576 - 3092 |
4-star hotel | 7 | 1151 | 892 - 1413 | 606 | 470 - 758 | 68 | 43 - 94 | 476 | 351 - 600 |
5-star hotel | 3 | 1263 | 949 - 2498 | 757 | 588 - 1161 | 70 | 38 - 206 | 436 | 249 - 1130 |
K-W test (H value) | 18.87** | 13.87* | 9.12 | 18.05** | |||||
Spearman’s ρ | −0.049 | −0.353 | −0.297 | 0.638** |
K-W test: H value by Kruskal-Wallis test by ranks; Spearman’s ρ: Rank correlation coefficient by Spearman method; *: p < 0.05; **: p < 0.01; ***: p < 0.001.
guest, and worker.
Regarding the difference between hotel classes, the rank correlations between total daily amounts of waste generated and WGRs and room, bed, and guest were significantly positive (excluding the WGR of SRe per bed). The 5-star hotels exhibited the highest total daily waste generation (271.8 kg/day), followed by 4-star hotels (190.5 kg/day), 3-star hotels (68.8 kg/day), 2-star hotels (30.1 kg/day), 1-star hotels (7.8 kg/day), and GHs (5.3 kg/day). The daily waste generation and WGRs increased as the hotel increased. The results were consistent with those in past studies on the hotel sector [
For the per-guest WGRs, 5-star hotels generated an average of 6.57 kg/guest/day, followed by 4-star hotels (2.32 kg/guest/day), 3-star hotels (1.71 kg/guest/day), 2-star hotels (0.48 kg/guest/day), 1-star hotels (0.60 kg/guest/day), and GHs (0.60 kg/guest/day).
According to some previous studies on the WGRs of the hotel sector in Asia [
The per-worker WGRs of GW and SRe were not significantly rank correlated with hotel class, and those by GHs were highest. The number of workers employed by GH was generally much smaller than that employed by higher-class hotels, which could have caused the increased per-worker WGRs at GHs. The GW and SRe WGRs of 2- to 5-star hotels were similar, despite higher-class hotels employing greater numbers of workers. This could be attributed to the higher WGRs per room, bed, and guest exhibited by higher-class hotels.
The SFR WGRs was significantly rank correlated with hotel class. Most 3-5-star some 2-star, and a few 1-star hotels and GHs provide food and beverage services, such as restaurants and coffee shops/bars, which could be a possible reason for the higher SFR WGRs of higher-class hotels.
Based on the results of the Kruskal-Wallis H test, there were significant differences in the total per-room WGRs between hotel classes ( χ 2 ( 5 ) = 27.97 , p < 0.001 ) , and significant differences were also detected for other WGRs per bed, guest, and worker. To clarify the significant differences between hotel classes, a Mann-Whitney U test was conducted by comparing all WGR pairs. The results suggested that hotel classes could be re-grouped into: 1) Low (guest house and 1-star hotel); 2) Middle (2- and 3-star hotels); and 3) High (4- and 5-star hotels) classes. The WGRs were recalculated by these three hotel classes and presented in
The authors also examined the influences of factors such as food service (breakfast, dining) and events (wedding party, conference) on WGRs. The Mann Whitney U test for each class indicated that there was no significant difference (p > 0.05) between hotels with and without food services/events.
Plastic containers and packaging, paper containers and packaging, and paper products were the major three components that could be recycled, accounting for over half of the recycling potential for most hotel classes (excluding 2-star hotels). Plastic containers and packaging accounted for a major proportion of the recycling potential at low-class hotels (10.2%). In contrast, paper products
Category | n | Total waste | GW | SRe | SFR | ||||
---|---|---|---|---|---|---|---|---|---|
Mean | 95% CI | Mean | 95% CI | Mean | 95% CI | Mean | 95% CI | ||
WGRs per room (g/room/day) | |||||||||
Low-class hotels[ | 20 | 461 | 371 - 585 | 347 | 295 - 486 | 38 | 30 - 55 | 77 | 9 - 104 |
Middle-class hotels[ | 15 | 980 | 769 - 1205 | 517 | 413 - 621 | 46 | 34 - 59 | 417 | 299 - 544 |
High-class hotels[ | 10 | 1501 | 1251 - 1772 | 837 | 666 - 1048 | 86 | 61 - 111 | 578 | 470 - 689 |
K-W test (H value) | 25.582*** | 19.075*** | 10.304*** | 26.138*** | |||||
Spearman’s ρ | 0.843** | 0.764** | 0.493** | 0.824** |
[
Component | Hotel class | ||||||||
---|---|---|---|---|---|---|---|---|---|
GH | 1-star | 2-star | 3-star | 4-star | 5-star | Low[ | Middle[ | High[ | |
Sample size (n) | 8 | 4 | 3 | 3 | 2 | 1 | 12 | 6 | 3 |
Plastic | 15.5 | 12.0 | 10.7 | 11.8 | 11.5 | 12.5 | 14.4 | 11.2 | 11.9 |
Paper | 13.5 | 23.9 | 16.7 | 14.8 | 20.3 | 10.1 | 17.0 | 15.8 | 16.9 |
Food waste | 57.4 | 51.0 | 40.9 | 48.4 | 44.1 | 56.6 | 55.2 | 44.7 | 48.3 |
Rubber & leather | 0.3 | 0.2 | 2.8 | 0.7 | 0.2 | 0.0 | 0.2 | 1.8 | 0.2 |
Grass & wood | 2.0 | 7.2 | 10.7 | 8.5 | 6.4 | 7.0 | 3.7 | 9.6 | 6.6 |
Textile | 2.4 | 2.2 | 7.7 | 1.6 | 4.0 | 0.9 | 2.3 | 4.7 | 3.0 |
Metal | 1.3 | 0.2 | 1.7 | 0.7 | 0.4 | 0.3 | 1.0 | 1.2 | 0.3 |
Glass | 3.8 | 1.0 | 3.3 | 0.3 | 1.4 | 1.1 | 2.9 | 1.8 | 1.3 |
Ceramic | 0.6 | 0.0 | 0.0 | 0.3 | 0.6 | 7.4 | 0.4 | 0.1 | 2.9 |
Miscellaneous | 3.2 | 2.4 | 5.5 | 12.9 | 11.0 | 4.2 | 2.9 | 9.2 | 8.7 |
Composting potential | 57.9 | 43.9 | 38.0 | 52.4 | 48.7 | 48.8 | 53.2 | 45.2 | 48.7 |
Food waste | 56.0 | 41.0 | 27.9 | 44.8 | 42.5 | 45.7 | 51.0 | 36.3 | 43.6 |
Garden waste | 1.9 | 2.9 | 10.2 | 7.6 | 6.2 | 3.0 | 2.2 | 8.9 | 5.2 |
Recycling potential | 33.5 | 31.5 | 38.5 | 28.6 | 35.1 | 19.3 | 32.8 | 33.6 | 29.8 |
Plastic―C&P a | 11.1 | 8.6 | 6.9 | 8.1 | 7.1 | 4.5 | 10.2 | 7.5 | 6.2 |
Plastic―Product | 2.7 | 1.1 | 1.5 | 2.3 | 1.4 | 1.1 | 2.1 | 1.9 | 1.3 |
Plastic―Other | 0.0 | 0.6 | 0.9 | 0.0 | 0.6 | 0.0 | 0.2 | 0.5 | 0.4 |
Paper―C&P a | 4.6 | 7.4 | 4.1 | 5.1 | 4.1 | 3.3 | 5.5 | 4.6 | 3.8 |
Paper―Product | 7.4 | 8.4 | 7.2 | 8.2 | 14.3 | 5.7 | 7.7 | 7.7 | 11.5 |
Paper―Other | 1.6 | 1.0 | 1.8 | 0.5 | 0.8 | 1.0 | 1.4 | 1.1 | 0.9 |
Other material | 6.0 | 4.3 | 16.1 | 4.4 | 6.8 | 3.7 | 5.6 | 10.2 | 5.7 |
Non-recyclable | 8.6 | 24.6 | 23.5 | 19.0 | 16.2 | 31.9 | 13.9 | 21.2 | 21.4 |
aC & P: containers and packaging. [
dominated the recycling potential at high-class hotels (11.5%). Although the hotel sector in Hue City conducts recycling using informal sectors such as junk-buyers and livestock breeders, substantial amounts of compostable and recyclable waste still remain in GW. Recycling activities tend to focus on materials that are easily separated and high value, such as beverage containers, while items that are not easily separated, such as a small amount of recyclables and smelly organic waste, are often put into GW without separation.
The estimation procedure followed the methodology reported by Matsui et al. (2018) [
For the facilities separating both recyclables and food residue, the total waste generation could be divided into the following five components based on the waste’s composition and waste measurement survey data: recycling potential, composting potential, non-recoverable, separated recyclables, and separated food residue. For the facilities with other types of separation procedures, such as “recyclables only”, “food residue only”, and “no separation”, the authors estimated the amounts of waste generated for the five components using the waste composition data of facilities conducting “recyclables and food residue separation” according to assumed component allocations, as shown in
Based on the waste composition data of facilities separating “recyclables and food residue”, the total waste generation and its five components for each hotel class was calculated using the following equations:
Low-class[a] | Middle-class[b] | High-class[c] | |
---|---|---|---|
Waste separation status | |||
Sample size (n) | 20 | 15 | 10 |
Recyclables and food residue | 25% | 93.5% | 100% |
Recyclables only | 50% | 6.5% | 0% |
Food residue only | 15% | 0% | 0% |
No separation | 10% | 0% | 0% |
Number of hotels in Hue City | |||
Facilities | 344 | 43 | 15 |
Rooms | 3582 | 2024 | 2157 |
[a]Low-class hotel: Guesthouse and 1 star hotels; [b]Middle-class hotel: 2 and 3 star hotels; [c]High-class hotel: 4 and 5 star hotels. Source: General statistics office, 2015.
Separation status | Rate | General waste | Separated recyclables | Separated food residue | ||
---|---|---|---|---|---|---|
Recycling potential | Composting potential | Non-recoverable | ||||
Recyclables and food residue separation | a1 | Re | Co | NRe | SRe | SFR |
Recyclables separation only | a2 | Re | Co + SFR | NRe | SRe | - |
Food residue separation only | a3 | Re + SRe | Co | NRe | - | SFR |
No separation | a4 | Re + SRe | Co + SFR | NRe | - | - |
Recycling potential = n i ∗ [ ( a 1 + a 2 ) ∗ Re + ( a 3 + a 4 ) ∗ ( Re + SRe ) ]
Composting potential = n i ∗ [ ( a 1 + a 3 ) ∗ Co + ( a 2 + a 4 ) ∗ ( Co + SFR ) ]
Non-recyclable = n i ∗ ( a 1 + a 2 + a 3 + a 4 ) ∗ NRe
Separated recyclables = n i ∗ ( a 1 + a 2 ) ∗ SRe
Separated food residue = n i ∗ ( a 1 + a 3 ) ∗ SFR
Total waste generation I = Recycling potential + Composting potential + Non-recyclable + Separated recyclables + Separated food residue.
Where ni is the total number of rooms in Hue City by each hotel class (Low-class, Middle-class, High-class).
To estimate the 95% CI of the total waste generation and its five components from the hotel sector in Hue City, the Monte Carlo simulation by non-parametric bootstrap method with return was applied [
The results of the total waste generation and its components by the Hue hotel sector are shown in
High-class hotels contributed the highest amount of waste to the total amount generated by the hotel sector, at 3.24 tons/day (47%), followed by middle-class hotels at 1.98 tons/day (29%), and low-class hotels at 1.66 tons/day (24%). The recycling potential was highest for low-class hotels at 0.4 tons/day (6%), and the composting potential was highest for high-class hotels at 1.10 tons/day (16%).
The 95% CI of the total waste generation by the hotel sector was 6.28 - 7.62 tons/day, and the 95% CIs of the separated recyclable and separated food residue were 0.32 - 0.45 and 1.78 - 2.45 tons/day, respectively.
To estimate the impact of each parameter used for the confidence interval estimation of total waste generation, the authors also conducted sensitivity analysis by squaring the Spearman’s Rank Coefficients of each parameter, summing the results, and adjusting them to 100% [
This study assessed the solid waste generation and recycling potential of the hotel sector in Hue City, Vietnam. The authors analyzed waste generation rates (WGRs) and composition in detail for 45 targeted establishments. The WGRs were also categorized considering the amount of waste collected by informal
sectors: general waste (GW), separated recyclables (SRe), and separated food residue (SFR). Some key findings of this study are outlined below.
1) Participation in waste separation by the hotel sector in Hue City was very high; 95.56% of the target establishments separated waste at its source. Food waste separation was common among middle- and high-class hotels (from 2- to 5-stars) where food and beverage services (such as restaurants or café bars) were provided.
2) The average total daily waste generation per facility was highest at 5-star hotels (271.8 kg/day), followed by 4- (190.5 kg/day), 3- (68.8 kg/day), 2- (30.1 kg/day), and 1-star hotels (7.8 kg/day), and guest houses (5.3 kg/day).
3) The total per-room WGRs were highest for 5-star hotels at 1.61 kg/room/day, and lowest for 1-star hotels (0.39 kg/room/day). In addition, the total per-guest WGRs were highest for 5-star hotels at 6.57 kg/guest/day, and lowest for 1-star hotels and guest houses (0.6 kg/guest/day). The rank correlations between the hotel classes and WGRs per room, bed, and guest (excluding the WGR of SRe per bed) were significantly positive.
4) Food waste constituted the largest proportion of GW within a range of 40.9% -57.4%. The composting and recycling potentials were within ranges of 38.0% - 57.9% and 19.3% - 38.5%, respectively. Plastic containers and packaging, paper containers and packaging, and paper products were the three major components, accounting for over half of the recycling potential of most hotel classes. Plastic containers and packaging accounted for a major proportion of the recycling potential at low-class hotels (10.2%), while paper products were dominant at high-class hotels (11.5%).
5) The total waste generation of the hotel sector in Hue City was estimated to be 6.88 tons/day (6.28 - 7.62 tons/day, 95% CI). The remaining recycling and compostable potentials of GW accounted for 0.87 tons/day (0.63 - 1.35 tons/day, 95% CI) and 2.57 tons/day (1.78 - 3.14, 95% CI), respectively. Therefore, the total amount of non-recyclable waste delivered to landfill sites can be reduced from the current 4.37 tons/day (3.90 - 5.06 tons/day, 95% CI) to 0.94 tons/day (0.61 - 1.54 tons/day, 95% CI).
6) The recycling potential of GW was highest for low-class hotels at 0.4 tons/day (0.27 - 0.64 tons/day, 95% CI), and the composting potential of GW was highest for high-class hotels at 1.10 tons/day (0.45 - 1.58 tons/day, 95% CI). High-class hotels should be considered as priority targets for a 3R promotion campaign in the future.
7) Based on the sensitivity analysis, the GW produced by high-class hotels had the highest influence (38.2%) on the estimated total waste generation, followed by GW produced by low-class hotels (22.3%), SFR from middle-class hotels (12.4%), and SFR from high-class hotels (11.7%). To improve the reliability of the estimated total waste generation, the parameters with greater impacts on uncertainty require additional data collection and/or modeling by influence factors to reduce the overall uncertainty of the results.
Son, L.H., Matsui, Y., Trangm D.T.T. and Thanh, N.P. (2018) Estimation of the Solid Waste Generation and Recycling Potential of the Hotel Sector: A Case Study in Hue City, Vietnam. Journal of Environmental Protection, 9, 751-769. https://doi.org/10.4236/jep.2018.97047