ASSESSMENT OF WASTE STATUS ON CERTAIN LAND USE TYPES IN CÁI RĂNG DISTRICT, CẦN THƠ CITY

ASSESSMENT OF WASTE STATUS ON CERTAIN LAND USE TYPES IN CÁI RĂNG DISTRICT, CẦN THƠ CITY

ASSESSMENT OF WASTE STATUS ON CERTAIN LAND USE TYPES IN CÁI RĂNG DISTRICT, CẦN THƠ CITY

Nguyễn Văn Dũng

Natural Resources and Environment Division of Cái Răng District, Cần Thơ City

Nguyễn Văn Phô

Project Management Board for Investment and Construction of Civil and Industrial Works in Bạc Liêu Province

Võ Quang Minh

Phạm Cẩm Đang

Department of Land Resources, Faculty of Environment and Natural Resources, Cần Thơ University

Abstract:

The research aims to evaluate the status of waste on certain land use types in Cái Răng District, Cần Thơ City. The study employs secondary data collection methods through interviews with 35 forms/type of land use; reliability analysis (CA) and exploratory factor analysis (EFA); and the hierarchical method (AHP) to evaluate impact factors. The group of non-agricultural business land, especially commercial service land, has the largest amount of solid waste, followed by agricultural land and residential land.

Solid waste is stored in trash bins and plastic bags and is collected, mostly with waste sorting. Reliability analysis and exploratory factor analysis identified 3 main factors and 13 sub-factors. Impact assessment shows that the main factor of human has the strongest impact weight, followed by policy and financial factors being the weakest. Among the sub-factors, the decision-maker has the strongest impact on both human and financial aspects. Overall, the decision-maker factor has the strongest impact. The remaining factors have a weak impact.

Keywords: Reliability Analysis (CA), Waste, Cái Răng District.

I. INTRODUCTION

Environmental pollution continues to occur in many areas due to limitations in waste control and management, leading to low collection and treatment rates of household solid waste, which do not meet practical requirements (Ministry of Natural Resources and Environment, 2019). Indiscriminate waste disposal and inadequate sanitation during solid waste collection and transportation are causing negative impacts on residents’ lives and urban aesthetics (Trần Kiên, 2021). Additionally, the costs of collecting and treating solid waste are burdensome for the state budget, as the funding for these activities mainly comes from the state (Ministry of Natural Resources and Environment, 2017).

According to statistics, the amount of solid waste generated in Cần Thơ City is approximately 650 tons/day, of which Cái Răng District accounts for about 80 tons/day (60% is treated by incineration and 40% by landfill). The collection and treatment rate of household solid waste only reaches about 91% (Ministry of Natural Resources and Environment, 2019).

Along with population growth, the process of industrialization and urbanization is strongly taking place, leading to an increase in both the volume and types of solid waste (Thắng N.T and colleagues, 2019). Cái Răng District, one of the three central districts of Cần Thơ City, is developing industrially and strongly promoting trade services oriented towards regional logistics services, while also developing new urban areas of the city (Cái Răng District Electronic Portal, 2023).

Different socio-economic entities have various characteristics regarding solid waste in terms of rate, type, quantity, toxicity, and recyclability. Therefore, the management of solid waste by district entities faces many difficulties and limitations. The locality needs to find and implement comprehensive solid waste treatment solutions by region or by land use type to serve the management and treatment of household solid waste.

Based on this situation, the study “Assessment of Waste Status on Certain Land Use Types in Cái Răng District, Cần Thơ City” is the basis for proposing suitable solutions to improve the efficiency of waste management, collection, and treatment in Cái Răng District.

II. RESEARCH METHODS

1. Secondary Data Collection Method

Collect documents, information, and published research results related to solid waste management. Gather information on natural, socio-economic conditions, environmental data, and development policies and strategies of Cái Răng District for the period 2015 – 2020 from the People’s Committee of Cái Răng District along with relevant departments in Cần Thơ City. Collect data on the collection, transportation, and collection routes of the functional unit. The documents and research related to current waste management and treatment technologies in provinces/cities are used as a basis to propose suitable household solid waste treatment solutions for the study area.

2. Primary Data Collection Method

Determine the investigation subject and sample size based on Yamane’s 1967 formula and the number of households from the Cái Răng – Phong Điền Statistics Department (2022) n = N/(1+N.e²) = 33,000/(1 + 33,000 x 0.12) = 110 survey samples. Conduct surveys on 3 subject groups: urban residential land (ODT), agricultural production land (SXNN), and commercial service land (TMDV), distributing 35 questionnaires per group.

Randomly survey residents in the district about the following topics: source of solid waste, type of solid waste, methods of sorting and collection, difficulties and limitations, and suggestions. The study interviews 9 experts who are local management officers involved in or directly or indirectly related to solid waste management in the district. Design survey questionnaires using the pairwise comparison method (AHP) to evaluate and compare the impact levels among primary factors (human, policy, and finance) and secondary factors in the research.

3. Data Compilation and Processing Method

The data collected from the subjects is compiled and processed using Microsoft Excel according to the subjects. SPSS 20 software is used in descriptive statistics and reliability analysis with Cronbach’s alpha, and exploratory factor analysis (EFA) in SPSS to identify and evaluate impact factors.

4. Data Analysis Method

Conduct Cronbach’s alpha scale reliability test to determine whether the surveyed subjects understand the same information about the factors in solid waste management. This method is performed before EFA to remove garbage items as they may create artificial factors in subsequent analyses. The goal is to determine the correlation between variables in the data set. This analysis provides a factor structure (a group of variables based on close correlations).

5. Hierarchical Method

AHP is a decision-making method that provides an order of criteria, enabling the decision-maker to make the most reasonable final decision (Liu et al., 2007). The hierarchical analysis method (AHP) is used in the study to determine the levels of factors as a basis for selecting the most suitable effective solutions.

Analysis from AHP results includes:

– Impact factors at different levels (with 5 impact factors having equivalent solutions based on AHP analysis results).

6. Evaluation Method and Solution Proposal

Based on the research analysis results evaluating the status of solid waste on various land use types. Assess the factors affecting solid waste management such as educational level, gender ratio, or waste sorting capability. From there, along with AHP analysis results, propose suitable solutions.

III. RESULTS AND DISCUSSION

1. Evaluation of Waste Status on Different Land Use Types in Cái Răng District

From the aggregated results of household survey interviews, the discrepancy in solid waste among three land use types is shown in (Figure 1). Depending on living and family activities, each of the three land use types has different amounts of solid waste disposal. Among them, the commercial service group has the highest amount of solid waste compared to the other two groups. This is because these households are engaged in various commercial activities and daily habits involve the use of many products generating solid waste.

For urban residential land and commercial service land, their living activities differ. Urban residential land often involves spending most time at workplaces, whereas agricultural production land mainly involves agricultural activities and rural living habits, resulting in less solid waste disposal for these two groups.

Urban residential land generates an average of 4.3 kg of solid waste per household per month. Of this, organic waste accounts for the largest portion at 1.7 kg/month/household, followed by glass bottles at 1.1 kg/month/household, plastic bottles at 1 kg/month/household, and other plastics at 0.5 kg/month/household. This shows that urban residential land generates the highest amount of organic waste, due to habits of using many types of organic food and substantial leftover food waste.

Figure 1. Solid Waste Levels of Different Land Use Types

For commercial service land use, the total solid waste generated is significantly higher than the other two groups, averaging 29.3 kg per household per month. Among this, organic waste is the largest at 20 kg per month, and other types such as plastic bottles and other plastics also have relatively high disposal amounts at 4.5 kg and 4 kg per month, respectively. Glass bottles have the least disposal amount.

For agricultural land use, the total solid waste generated is low (4.4 kg per month). Among this, organic waste still accounts for the highest amount at 1.5 kg per month, followed by glass bottles at 1.3 kg per month, plastic bottles at 1 kg per month, and other plastics at 0.6 kg per month. This may be because agricultural households use agricultural materials for production, so solid waste from pesticide bottles are contained in glass bottles, and they mainly use home-grown food with minimal leftover food waste.

2. Assessment of Impacts on Solid Waste Management in Cái Răng District

Based on survey results from relevant management officers and the actual management status of solid waste in Cái Răng District, the study applied statistical reliability analysis (CA) and exploratory factor analysis (EFA). As a result, the study identified the main impact factors on waste management, including three primary factors: human (decision-maker, management capacity, public awareness, and community implementation capability), policy (central government policy, local policy, sanction policy, environmental investment policy, implementation mechanism, investment call policy), and finance (central government environmental budget, local government environmental budget, public financial capacity, and international organization investment).

2.1. Results of Cronbach’s Alpha Reliability Test

The study applied reliability analysis using the Cronbach’s Alpha test in SPSS software for each impact factor. Each sub-factor is an observed variable for the main factor groups, and the main factors are dependent variables for the observed variables within that factor.

For the main factors:

Reliability analysis (CA) shows that all three main factors meet the reliability conditions of the Cronbach’s Alpha test. The test results indicate that all three factors satisfy the conditions (Min Cronbach Alpha = 0.3 < reliability < Max Cronbach Alpha). All three factors have a reliability of 0.3 or higher and are equivalent. Specifically, the human factor achieved 0.732, the financial factor achieved 0.716, and the policy factor achieved 0.710. Thus, all three factors meet the reliability conditions for analysis and impact assessment.

For the sub-factors:

For the human factor, the test results show that all four sub-factors meet the Cronbach’s Alpha reliability conditions. For the financial factor, the sub-factors show reliability ranging from 0.714 to 0.80, corresponding to 71% – 80% accuracy, and all four sub-factors meet the reliability conditions. For the policy factor, the test results show that all five sub-factors meet the reliability conditions.

2.2. Results of Exploratory Factor Analysis (EFA)

The analysis of the rotated matrix results shows that only three groups of factors were discovered. The analysis results also show that the significance of the KMO and Bartlett test is very high (0.018), and there are three factor components discovered consisting of 13 variables, with KMO coefficient = 0.652 > 0.5 and total variance explained by rotated factor loadings is 73.650 > 50%. Thus, the discovered factor groups meet the requirements for evaluation (Table 1).

The rotated matrix results categorize the variables in order of impact from strong to weaker within the same group. Additionally, the results identified three groups of factors, each comprising statistically different variables, all within the same factor. This indicates that the factors in the three main groups meet the condition > 0.5, allowing all variables to be included in the next step of the analysis.

Table 1. Rotated Factor Loadings Matrix

3. Impact Assessment of Factors on Solid Waste Management

The AHP analysis results identify the weights of the three main factors and thirteen sub-factors as shown in Table 2:

Table 2. Overall Weights of Factors

The evaluation results of the main factors indicate that the human factor has the highest weight (0.69), followed by policy (0.23), and the financial factor has the lowest weight (0.08). The expert evaluations (using the AHP method) are consistent, with a consistency ratio (CR) of less than 10%, indicating that the expert assessments of the impact on solid waste management in Cái Răng District are consistent with reality.

The assessment shows that the decision-maker sub-factor has the highest weight (0.58), followed by the management capacity of officials (0.24), public awareness (0.10), and the community’s implementation capability (0.08). The consistency of expert evaluations for these factors is also suitable, with a CR of less than 10%.

For the financial sub-factors, the highest impact is attributed to the central government environmental budget and local government environmental budget, with weights of 0.54 and 0.25 respectively. The public financial capacity and international organization investment have lower impacts, with weights of 0.11 and 0.10 respectively, and a CR of less than 10%.

The policy factor with the highest impact weight is the central government environmental policy (0.44), followed by local government environmental policies (0.30), sanction policies (0.14), environmental investment policies (0.10), and the implementation mechanism (0.07). All these factors show a CR of less than 10%.

4. Advantages and Challenges in Solid Waste Management

The survey and assessment of the impacts of factors on solid waste management in Cái Răng District, Cần Thơ City, identified the following advantages and challenges:

4.1. Advantages

Human Factors:

– Government, Ministry, and related department policies and directives; the People’s Committee of the City, and the People’s Committee of Cái Răng District have directed the enhancement of propaganda campaigns and the organization of movements to reduce waste at the source.

– Management officials have received specialized training in their fields of responsibility.

– Currently, the awareness of the community and businesses has increased, resulting in many positive outcomes.

Policy Factors:

– There are specific regulations and guidelines for solid waste management and environmental, land management.

– Strengthened inspection and violation handling.

– Implementation of central government and Cần Thơ City policies on solid waste management and the environment in the district.

– Policies supporting businesses in investing and building production facilities and solid waste treatment technologies.

– The implementation mechanism is gradually developing and becoming more effective.

Financial Factors:

– Financial resources allocated from the government.

– Environmental protection tax and fee policies have contributed to increasing the voluntary compliance of individuals and organizations.

– Residents have proactively paid for waste collection fees and invested in foam and plastic bins for waste storage, facilitating the collection process.

– There have been calls for international investors and diversification of state budget sources for managing and treating environmental waste.

4.2. Challenges

Human Factors:

– Policies are sometimes not practical, and implementation faces some difficulties.

– District-level personnel often handle land, construction, and environmental matters concurrently.

– There are limitations in the inspection and supervision staff for solid waste management and treatment activities.

– Some residents still lack environmental awareness, and a significant number of people misuse land.

– Organizing workshops and specialized conferences to raise public awareness is difficult and limited due to funding constraints.

Policy Factors:

– The organizational structure is not unified, with many gaps and unclear or overlapping task assignments.

– The implementation mechanism and policy framework are not yet complete.

– Management planning faces many difficulties.

– Sanction policies, such as administrative violation handling, exist but are almost unenforceable due to many objective factors.

– Businesses are not fully supported.

Financial Factors:

– Financial resources are still limited.

– Waste treatment technology is outdated and inefficient.

– A small number of residents participate in household waste collection and sorting services, and commercial service businesses arrange their own waste sorting bins at the source as required.

– There are not many organizations investing in waste treatment plants, wastewater treatment, and infrastructure for the city.

– Attractive policies to attract investment are lacking.

– International cooperation is ineffective.

5. Proposed Waste Management Solutions for Cái Răng District

The research proposes solutions to enhance the efficiency and effectiveness of solid waste management in Cái Răng District, Cần Thơ City:

Human Factors:

– Enhance training and specialized courses in natural resources and environmental sectors.

– Promote awareness and mobilize the community to raise consciousness about environmental protection in general and household solid waste management in particular.

– Introduce and promote the use of environmentally friendly, naturally decomposable products, and limit products generating non-decomposable waste.

– Most importantly, implement waste sorting at the source. However, the pilot models being implemented are limited in feasibility for each type of emitter and in funding when implemented. Therefore, solutions that bring socio-economic-environmental efficiency should be researched and expanded.

– Businesses are responsible for monitoring, supervising the collection and storage of solid waste at their facilities, and recording and reporting accurate waste data based on actual generation.

– Utilize easily decomposable organic waste to produce fertilizer through biological methods, incinerate waste to recover energy, and reuse plastic or inorganic materials to save environmental protection costs and improve economic efficiency.

– Provide tools and protective gear for sanitation workers and ward waste collection teams to ensure their health and safety.

Policy Factors:

– The locality should develop preferential policies to support businesses and individuals in building waste treatment facilities.

– Encourage businesses/households to operate towards clean, sustainable production.

– Develop and issue mechanisms and policies to call for investment, attract, and socialize investment in solid waste collection, transportation, and treatment.

– Encourage and support motivation for organizations and individuals to invest in waste treatment using advanced technologies, with energy recovery and reduced landfill.

– Review, supplement, and complete relevant mechanisms and policies under authority for solid waste management.

– Strengthen inspection and strict handling of intentional violations in solid waste management.

– Utilize social resources, enhance exchange and cooperation with countries, international organizations, and non-governmental organizations for capacity building, learning experiences in plastic waste reuse and recycling, to transfer and apply existing, environmentally friendly technologies.

Financial Factors:

– Strengthen financial resources and investment for the locality, such as completing rural waste collection, transportation, and treatment systems.

– Encourage private facilities to participate in pollution treatment through tax reduction and preferential loans.

– Develop plans, prioritize reasonable allocation, and diversify financial investment sources for solid waste management from the State budget, domestic and international projects, and programs, mobilizing funds from the community (private businesses)…

In line with the overall development of the city, region, and nation, Cái Răng District should research and develop according to the following current orientations:

– Application of digital science and technology results that have changed the lifestyles of consumers and businesses. Smart cities will significantly alter how public services such as education, healthcare, and entertainment are provided, enhance the quality of life for residents, and support sustainable urbanization by improving city management, such as water and waste management, with smart sensors and big data capabilities (Borowski et al., 2018; Fialová et al., 2021).

– Development of eco-urban areas: focusing on the use of clean energy, promoting the entire green ecosystem from architecture to engineering and other products. Designing green networks can improve biodiversity protection, quality of life, and urban resilience (Valente et al., 2022).

– Circular economy is gradually becoming an inevitable trend globally. Developing a circular economy brings many benefits, maximizes resource utilization, limits waste, and reduces environmental harm. The circular economy model is viewed as a closed loop connecting exploitation, production, distribution, use, and recycling (Mai Thanh Dung et al., 2023). This brings sustainable development efficiency in economic, social, and most importantly, increases the feasibility of environmental problem-solving models.

IV. CONCLUSION

The research indicates that the waste status in commercial service land use types has the highest total solid waste generation, followed by agricultural production land use types and urban residential land use types. In particular, commercial service land use types have the highest amount of organic waste, while agricultural production land use types have the highest amount of glass bottle solid waste.

The study’s reliability analysis and exploratory factor analysis identified 3 main factors and 13 sub-factors. Among these, the human factor (Level 01) plays a crucial role with a weight of 0.69 in solid waste management specifically, and environmental management in general. Within this, the decision-maker (Level 02) is the most important sub-factor with a weight of 0.58.

The study identified the advantages and challenges in solid waste management for each factor (human, financial, policy). It also proposed waste management solutions for Cái Răng District according to each factor.

References

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