A ridge regression approach to estimate the relationship between landfill taxation and waste collection and disposal in England

Characterization of municipal solid waste in Kuwait: Sector-specific composition analysis and implications

Municipal solid waste (MSW) characterization plays a pivotal role in devising effective waste management strategies conducive to fostering a circular economy. This study presents composition analysis across twenty-four subcategories sourced from residential, commercial, and industrial sectors in Kuwait. The study is conducted in accordance with the Standard Test Method for Determination of the Composition of Unprocessed Municipal Solid Waste (ASTM D5231). The results indicate that organic waste comprises 45.3%, followed by paper waste (19.9%) and plastics (19.8%). The remaining waste comprises glass waste (3.5%), diapers (2.7%), textiles (2.6%) and other waste. Paper waste (19.9%) consists mainly of mixed paper (12.1%), cardboard (3.7%), newspaper (3.3%), printer printouts (0.6%) and other office paper (0.2%). Plastic waste (19.8%) consists mainly of film (11.2%), PET (3.1%), HDPE (1.1%) and other mixed plastics (4.4%). Residential and mixed areas have the highest proportion of organic waste. Commercial areas produce the highest proportion of wastepaper (22.4%) and textiles (3.7%). Industrial areas produce the highest proportion of plastic waste (29.1%), most of which is film (17.3%). The study also provides an overview of the MSW management system in the country, an overview over the legislative framework, and forecasts of future waste generation rates with comparison to historical baselines.Implications: The precise and up-to-date characterization of municipal solid waste is imperative for scholarly journal submissions, as it establishes a foundational understanding of waste composition, aiding researchers and policymakers in the development of effective waste management strategies, resource recovery initiatives, and sustainable solutions to address the evolving challenges in waste management systems.This study provides detailed composition analysis for twenty-four municipal solid waste (MSW) subcategories collected across different sources: residential, commercial, industrial, and mixed areas. Time series forecasting is applied to predict MSW generation based on historical data obtained through the local municipality over the past decade. Factorial analysis is applied to investigate changes across source areas, and a hypothesis test is used to compare the current MSW composition against previous baselines. The results demonstrated significant variation across most waste categories. The plastic waste proportion has increased by 48.5% compared to 2013 data, despite awareness campaigns. Paper waste has also increased in proportion from 6.8% to 16.2%; this increase is associated with the mixed paper subcategory, which is mostly used for packaging. The composition data provided in this study are necessary for long-term monitoring, strategy assessment, and legislation associated with waste reduction and remediation.

Risk Management for Whole-Process Safe Disposal of Medical Waste: Progress and Challenges

Over the past decade, the global outbreaks of SARS, influenza A (H1N1), COVID-19, and other major infectious diseases have exposed the insufficient capacity for emergency disposal of medical waste in numerous countries and regions. Particularly during epidemics of major infectious diseases, medical waste exhibits new characteristics such as accelerated growth rate, heightened risk level, and more stringent disposal requirements. Consequently, there is an urgent need for advanced theoretical approaches that can perceive, predict, evaluate, and control risks associated with safe disposal throughout the entire process in a timely, accurate, efficient, and comprehensive manner. This article provides a systematic review of relevant research on collection, storage, transportation, and disposal of medical waste throughout its entirety to illustrate the current state of safe disposal practices. Building upon this foundation and leveraging emerging information technologies like Internet of Things (IoT), cloud computing, big data analytics, and artificial intelligence (AI), we deeply contemplate future research directions with an aim to minimize risks across all stages of medical waste disposal while offering valuable references and decision support to further advance safe disposal practices.

Food wastes for bioproduct production and potential strategies for high feedstock variability

Unavoidable food wastes could be an important feedstock for industrial biotechnology, while their valorization could provide added value for the food processor. However, despite their abundance and low costs, the heterogeneous/mixed nature of these food wastes produced by food processors and consumers leads to a high degree of variability in carbon and nitrogen content, as well as specific substrates, in food waste hydrolysate. This has limited their use for bioproduct synthesis. These wastes are often instead used in anaerobic digestion and mixed microbial culture, creating a significant knowledge gap in their use for higher value biochemical production via pure and single microbial culture. To directly investigate this knowledge gap, various waste streams produced by a single food processor were enzymatically hydrolyzed and characterized, and the degree of variability with regard to substrates, carbon, and nitrogen was quantified. The impact of hydrolysate variability on the viability and performance of polyhydroxyalkanoates biopolymers production using bacteria (Cupriavidus necator) and archaea (Haloferax mediterranei) as well as sophorolipids biosurfactants production with the yeast (Starmerella bombicola) was then elucidated at laboratory-scale. After which, strategies implemented during this experimental proof-of-concept study, and beyond, for improved industrial-scale valorization which addresses the high variability of food waste hydrolysate were discussed in-depth, including media standardization and high non-selective microbial organisms growth-associated product synthesis. The insights provided would be beneficial for future endeavors aiming to utilize food wastes as feedstocks for industrial biotechnology.

Get the win-win: Sustainable circular model of 'generation-value-technology' of industrial solid waste management

The management of industrial solid waste (ISW) and promoting sustainable circular development of the industrial economy is an urgent priority today. Therefore, this article constructs a sustainable circular model of 'generation-value-technology' of ISW management through the lens of industrial added value (IAV) and technology level. Also, the importance of the role of government is considered in the model. Based on actual data of China, this article simulates the future trend of the model using a system dynamics approach. The chief findings of the study are as follows: (1) under the current policy, China's future industrialization is increasing and the technological level of industrial enterprises is rising, but this is accompanied by a climb in ISW generation. (2) The win-win situation of ISW decrease and IAV increase can be achieved through enhanced information disclosure, technology innovation and government incentives. (3) Government subsidy should be oriented towards supporting technology innovation in industrial enterprises while reducing the proportion of incentives for ISW management results. Based on the results, this study proposes targeted policy implications for government and industrial enterprises.

Municipal solid waste management instruments that influence the use of the refuse as fuel in developing countries: A critical review

Landfills are the destination of most of the refuse generated whereas composting, material recycling, and Waste-to-Energy (WtE) technologies are not commonly employed in developing countries. However, the destination for energy purposes could be supplied with this refuse, improving the viability of energy use. Thus, this article raises some questions to identify aspects that could encourage its use as refuse-derived fuel (RDF) in these countries. Among them, does environmental education affect the municipal solid waste (MSW) source separation with emphasis on a destination? Can selective collection and extended producer responsibility (EPR) affect the MSW for energy recovery? Is there competition between the recycling market and the energy market for RDF? A systematic review of the literature was conducted to gather data and provide answers to such questions. This enabled to observe that EPR, selective collect expansion and source separation influence the quantity and quality of waste sent for energy use. Both internal and external factors impact on source separation. Additionally, there is evidence to support that despite several studies showing their technical, economic, environmental and social viability, the methods of energy usage of the refuse still need to improve their deployment in developing countries. In addition to identifying the main research gaps to be filled in future studies, the article also identified the instruments of MSW management that are to be applied in developing countries to divert recyclable and organic waste from landfill.

Post-closure Cost Efficiency in Public Versus Private Landfills: The Case of Emilia-Romagna (Italy)

Waste management systems have developed in recent years toward the adoption of sustainable management principles and practices, such as circular economy, zero waste, resource efficiency, waste avoidance, re-use, and recycling. Nevertheless, landfills continue to be used for waste disposal despite their risks related to contamination and effects on urban development. Most research on landfills focuses on their operational and technical aspects, while the performance and cost efficiency in managing landfills is less commonly studied, especially their post-closure management. However, improving efficiency is very relevant in the context of scarce public sector resources. This paper, therefore, analyzes the efficiency of post-closure management of landfills. Drawing on agency and stewardship theories, we focus on the difference in efficiency between public and private management of post-closure landfills. We use a linear mixed regression model to analyze data from 2015 to 2018 relating to 54 landfills (79% of which are privately managed) in the Emilia-Romagna region of Italy. The results show that public management is more efficient than private management. Results contribute to defining drivers of cost and confirming a disparity in the performance of private and public management. Our results cast doubt on the assumption, which is prevalent in new public management theory, that private operators are more efficient than public ones. We conclude by highlighting that to reach efficiency, it is better to increase the effectiveness of regulation in terms of value for money, without pre-determined preferences for the type of management.

How have waste management policies impacted the flow of municipal waste? An empirical analysis of 14 European countries

Waste management policies aim to divert waste from lower positions on the waste hierarchy such as landfill and incineration to higher positions in the hierarchy such as energy recovery and recycling. However, empirical evaluations of such policies are scarce. This study highlighted the effect of waste management policies on the amount of waste treated with landfill, incineration, energy recovery and recycling by analysing a panel dataset consisting of 14 European countries and the period 1996 to 2018. Findings from a seemingly unrelated regression model suggest that the landfill ban is associated with a decrease in landfill waste, but an increase in incineration, energy recovery and recycling waste. The landfill tax is also correlated with an increase in energy recovery waste but, in contrast, it is associated with a reduction in incineration and recycling waste. Meanwhile, the deposit refund scheme is associated with a decrease in the amount of landfill waste. Concerning the effects on total waste generated, regression results from a fixed effects model indicate that the landfill tax and the deposit refund scheme are both correlated with a reduction in the amount of waste generated. These findings contribute to the scarce academic literature evaluating waste management policies and may better inform policy makers on their longer-term implications.

Effect of geographical factors on reference values of creatine kinase isoenzyme

The aim of this study was to investigate the geographical spatial distribution of creatine kinase isoenzyme (CK-MB) in order to provide a scientific basis for clinical examination. The reference values of CK-MB of 8697 healthy adults in 137 cities in China were collected by reading a large number of literates. Moran index was used to determine the spatial relationship, and 24 factors were selected, which belonged to terrain, climate, and soil indexes. Correlation analysis was conducted between CK-MB and geographical factors to determine significance, and 9 significance factors were extracted. Based on R language to evaluate the degree of multicollinearity of the model, CK-MB Ridge model, Lasso model, and PCA model were established, through calculating the relative error to choose the best model PCA, testing the normality of the predicted values, and choosing the disjunctive kriging interpolation to make the geographical distribution. The results show that CK-MB reference values of healthy adults were generally correlated with latitude, annual sunshine duration, annual mean relative humidity, annual precipitation amount, and annual range of air temperature and significantly correlated with annual mean air temperature, topsoil gravel content, topsoil cation exchange capacity in clay, and topsoil cation exchange capacity in silt. The geospatial distribution map shows that on the whole, it is higher in the north and lower in the south, and gradually increases from the southeast coastal area to the northwest inland area. If the geographical factors are obtained in a location, the CK-MB model can be used to predict the CK-MB of healthy adults in the region, which provides a reference for us to consider regional differences in clinical diagnosis.

Development of an extended STIRPAT model to assess the driving factors of household carbon dioxide emissions in China

Although the past twenty years have witnessed China's remarkable economic development, the cost in terms of greenhouse gas emissions and a deteriorating environment has been enormous. Numerous studies have revealed the influence of household factors on household carbon dioxide emissions (HCEs) and called for a reduction of HCEs to mitigate climate change, but few have focused on assessing the most significant household driving factors of HCEs. Using statistical data between 2005 and 2019 in Jiangsu, China, this study developed an extended stochastic impact by regression on population, affluence, and technology (STIRPAT) model to assess the most significant driving factors of HCEs. The results show that the most significant driving factors are household size, total population, unemployment, and urbanisation rate. The study found that HCEs are positively impacted by household size while negatively impacted by the unemployment rate. Based on the study's findings, the following suggestions are proposed to lower HCEs: (i) establish an optimal consumption concept to guide residents towards consuming reasonably; (ii) cultivate a low-carbon concept among residents and promote low-carbon emissions living; and (iii) pay close attention to population structure factors and formulate effective measures accordingly. The study provides insightful information on the key driving factors of HCEs, which can facilitate achieving carbon emissions neutrality.

Current state of building demolition and potential for selective dismantling in Vietnam

In Vietnam, an increase in construction activities together with the absence of recycling-oriented demolition techniques is giving rise to an alarming generation of construction and demolition waste. This study scrutinized the current state of building demolition approaches in Hanoi, Vietnam and evaluated the potential for the selective dismantling, or deconstruction, of reinforced-concrete (RC) houses. Site observations, direct measurement, and interviews were conducted to obtain information on technical, environmental, and economic characteristics of three residential housing sites, each representing a typical current demolition technique (manual, hybrid, and mechanical demolition). A selective dismantling site is proposed based on the collected survey data and published case studies. Our findings confirmed the unsustainability of RC-building demolition practices in Hanoi, which have an average reuse/recycling rate of roughly 3%. The application of selective dismantling will boost the recycling rate to a remarkable 90%, associated with a 55% decrease in greenhouse gas emissions. Even though selective dismantling is more time-consuming and therefore more costly, it results in double the resale value and an eight-fold decrease in disposal costs. The results of a sensitivity analysis indicate that increasing the current disposal fee will significantly improve the feasibility of selective dismantling, suggesting a need for stricter disposal charging mechanisms along with other interventions such as the development of recycling facilities to promote the introduction of this building removal alternative in Vietnam.

Quantitative Evaluation of Waste Separation Management Policies in the Yangtze River Delta Based on the PMC Index Model

Numerous policies have been formulated and implemented to strengthen waste separation management activities in many countries. Waste separation management policies (WSMPs) must be evaluated as the precondition for reducing deviations from policy implementation and improving waste separation performance. Based on text mining technology and the construction of a policy modeling consistency (PMC) index model, we conducted a quantitative evaluation of 22 WSMPs issued by central governmental departments and provinces in the Yangtze River Delta, China from 2013 to 2021 and analyzed their optimization paths. The results suggest that the PMC index of the selected WSMPs has an upward trend. The average PMC index of 22 WSMPs was 6.906, indicating good quality in the policy texts. The PMC index identified seven, nine, five, and one of the policies as being perfect, excellent, good, and acceptable, respectively. The characteristics of WSMPs were further illustrated through PMC surface charts. Based on this, optimization paths for WSMPs with lower PMC indexes are proposed, which indicate that existing WSMPs have great potential for optimization in terms of harsher constraint regulations, context-appropriate incentives, and cultivation of market participants. Finally, this study provides a beneficial reference for similar cities or countries to improve their performance in the management of waste separation and environmental protection.

Tools for a circular economy: Assessing waste taxation in a CGE multi-pollutant framework

Economic theory states that incineration and landfill taxation can effectively diminish the environmental impacts of pollution and resource use by reducing their associated pollutants while stimulating the reuse and recycling of materials, and therefore, fostering a circular economy. The aim of this research is to assess the economic and environmental effects of these taxes in Spain in different scenarios with a detailed dynamic computable general equilibrium (CGE) model, as there are no studies analyzing this in detail. We focus on the economic impact on GDP and sectorial production and the environmental impact on different categories: global warming potential, marine eutrophication potential, photochemical ozone formation potential, particulate matter, human toxicity (cancer and noncancer), ecotoxicity, and depletion of fossil resources. We find in all scenarios that these taxes have a limited economic impact while reducing all of the environmental impact categories analyzed. The study reinforces the theory that policy makers need to impose taxes on landfill and incineration to reinforce the circularity of the economy and reduce environmental burdens, but also demonstrates that they can improve their design without additional costs.

Slow Time-Varying Batch Process Quality Prediction Based on Batch Augmentation Analysis

In this paper, focusing on the slow time-varying characteristics, a series of works have been conducted to implement an accurate quality prediction for batch processes. To deal with the time-varying characteristics along the batch direction, sliding windows can be constructed. Then, the start-up process is identified and the whole process is divided into two modes according to the steady-state identification. In the most important mode, the process data matrix, used to establish the regression model of the current batch, is expanded to involve the process data of previous batches, which is called batch augmentation. Thus, the process data of previous batches, which have an important influence on the quality of the current batch, will be identified and form a new batch augmentation matrix for modeling using the partial least squares (PLS) method. Moreover, considering the multiphase characteristic, batch augmentation analysis and modeling is conducted within each phase. Finally, the proposed method is applied to a typical batch process, the injection molding process. The quality prediction results are compared with those of the traditional quality prediction method based on PLS and the ridge regression method under the proposed batch augmentation analysis framework. The conclusion is obtained that the proposed method based on the batch augmentation analysis is superior.

A Smart Helmet-Based PLS-BPNN Error Compensation Model for Infrared Body Temperature Measurement of Construction Workers during COVID-19

In the context of the long-term coexistence between COVID-19 and human society, the implementation of personnel health monitoring in construction sites has become one of the urgent needs of current construction management. The installation of infrared temperature sensors on the helmets required to be worn by construction personnel to track and monitor their body temperature has become a relatively inexpensive and reliable means of epidemic prevention and control, but the accuracy of measuring body temperature has always been a problem. This study developed a smart helmet equipped with an infrared temperature sensor and conducted a simulated construction experiment to collect data of temperature and its influencing factors in indoor and outdoor construction operation environments. Then, a Partial Least Square–Back Propagation Neural Network (PLS-BPNN) temperature error compensation model was established to correct the temperature measurement results of the smart helmet. The temperature compensation effects of different models were also compared, including PLS-BPNN with Least Square Regression (LSR), Partial Least Square Regression (PLSR), and single Back Propagation Neural Network (BPNN) models. The results showed that the PLS-BPNN model had higher accuracy and reliability, and the determination coefficient of the model was 0.99377. After using PLS-BPNN model for compensation, the relative average error of infrared body temperature was reduced by 2.745 °C and RMSE was reduced by 0.9849. The relative error range of infrared body temperature detection was only 0.005~0.143 °C.

A hybrid mathematical modelling approach for energy generation from hazardous waste during the COVID-19 pandemic

The COVID-19 virus in a short time has caused a terrible crisis that has been spread around the world. This crisis has affected human life in several dimensions, one of which is a sharp increase in urban waste. This increase in waste volume during the pandemic, in addition to the intense increase in costs associated with the risks of virus contagion through infectious waste. In this study, a hybrid mathematical modelling approach including a Bi-level programming model for infectious waste management has been proposed. At the higher level of the model, government decisions regarding the total costs related to infectious waste must be minimized. At this level, the collected infectious waste is converted into energy, the revenue of which is returned to the system. The lower level relates to the risks of virus contagion through infectious waste, which can be catastrophic if ignored. This study has considered the low, medium, high and very high prevalence scenarios as key parameters for the production of waste. In addition, the uncertainty in citizens' demand for waste collection was also included in the proposed model. The results showed that by energy production from waste during the COVID-19 pandemic, 34% of the total cost of collecting and transporting waste can be compensated. Finally, this paper obtained useful managerial insights using the data of Kermanshah city as a real case.