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Incineration has become increasingly important in many large cities around the world because of fast urbanization and population growth. The benefits of energy production and large reduction in the waste volume to landfills also contribute to its growing adaptation for solid waste management for these cities. At the same time, the environmental impact of the pollutant gases emitted from the incineration process is a common concern for various stakeholders which must be properly addressed. To minimize the pollutant gas emission levels, as well as maximize the energy efficiency, it is critically important to optimize the combustion performance of an incinerator freeboard which would require the development of reliable approaches based on computational fluid dynamics (CFD) modeling. A critical task in the CFD modeling of an incinerator furnace requires the specification of waste characteristics along the moving grate as boundary conditions, which is not available in standard CFD packages at present. This study aims to address this gap by developing a numerical incinerator waste bed model.

A one-dimensional Lagrangian model for the incineration waste bed has been developed, which can be coupled to the furnace CFD model. The changes in bed mass due to drying, pyrolysis, devolatilization and char oxidation are all included in the model. The mass and concentration of gases produced in these processes through reactions are also predicted. The one-dimensional unsteady energy equations of solid and gas phases, which account for the furnace radiation, conduction, convection and heat of reactions, are solved by the control volume method.

The Lagrangian model is validated by comparing its prediction with the experimental data in the literature. The predicted waste bed height reduction, temperature profile and gas concentration are in reasonable agreement with the observations.

The simplicity and efficiency of the model makes it ideally suitable to be used for coupling with the computational furnace model to be developed in future (so as to optimize incinerator designs).

This research assesses the economic impact of biomass plant installations on Brazilian municipalities, focusing on (1) labor income, (2) sectoral labor income and (3) income inequality.

Municipal data from the Annual Social Information Report, the National Electric Energy Agency and the National Institute of Meteorology spanning 2002 to 2020 are utilized. The Synthetic Difference-in-Differences methodology is employed for empirical analysis, and robustness checks are conducted using the Doubly Robust Difference in Differences and the Double/Debiased Machine Learning methods.

The findings reveal that biomass plant installations lead to an average annual increase of approximately R$688.00 in formal workers' wages and reduce formal income inequality, with notable benefits observed for workers in the industry and agriculture sectors. The robustness tests support and validate the primary results, highlighting the positive implications of renewable energy integration on economic development in the studied municipalities.

This article represents a groundbreaking contribution to the existing literature as it pioneers the identification of the impact of biomass plant installation on formal employment income and local economic development in Brazil. To the best of our knowledge, this study is the first to uncover such effects. Moreover, the authors comprehensively examine sectoral implications and formal income inequality.

Purpose – The purpose of this research is to study the process conditions that give best yield and expected compositions of liquid smoke products that result during the pyrolisis process relying on predetermined variables.

Design/Methodology/Approach – Pyrolisis process running times are varied, that is, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, and 6 hourly. Condensing temperature maintained remained 25–30 °C. Products identification was applied by using gas chromotography mass spectroscopy.

Findings – Based on the research output, it was concluded that process conditions which give maximum yield were achieved when using double unit condenser (DUC) and time optional four hours, and it provides maximum volume liquid smoke product, and compositions of pyrolisis products. The process also created seven components, namely nepthalene, propanoic acid, 3,7 nanodiena, 2 metilguaiakol, 2-metoksi 4-methyl phenol, 4 ethyl-2 metoksil phenol, oxybanzene. Applying DUC during condensation phase may increase condensing force thereafter obtaining resulted products between 200% and 300% rather than using single unit condenser (SUC).

Research Limitations/Implications – This research was conducted on a fixed batch reactor made of a metal plate with a thickness of 3.0 mm. It carries 200 kg in capacity. In this phase, the moisture of candlenut shells might be kept in 10–12.5% wt. Process temperature applied ranged within 350–500 °C.

Originality/Value – In addition the study increased the theorical of understanding about pyrolisis process and Improving the production of liquid smoke from candlenut shell by pyrolisis process using the method of vapor condensation (Double unit condensor).

A significant number of studies have been conducted to analyze and understand the relationship between gas emissions and global temperature using conventional statistical approaches. However, these techniques follow assumptions of probabilistic modeling, where results can be associated with large errors. Furthermore, such traditional techniques cannot be applied to imprecise data. The purpose of this paper is to avoid strict assumptions when studying the complex relationships between variables by using the three innovative, up-to-date, statistical modeling tools: adaptive neuro-fuzzy inference systems (ANFIS), artificial neural networks (ANNs) and fuzzy time series models.

These three approaches enabled us to effectively represent the relationship between global carbon dioxide (CO₂) emissions from the energy sector (oil, gas and coal) and the average global temperature increase. Temperature was used in this study (1900-2012). Investigations were conducted into the predictive power and performance of different fuzzy techniques against conventional methods and among the fuzzy techniques themselves.

A performance comparison of the ANFIS model against conventional techniques showed that the root means square error (RMSE) of ANFIS and conventional techniques were found to be 0.1157 and 0.1915, respectively. On the other hand, the correlation coefficients of ANN and the conventional technique were computed to be 0.93 and 0.69, respectively. Furthermore, the fuzzy-based time series analysis of CO₂ emissions and average global temperature using three fuzzy time series modeling techniques (Singh, Abbasov–Mamedova and NFTS) showed that the RMSE of fuzzy and conventional time series models were 110.51 and 1237.10, respectively.

The paper provides more awareness about fuzzy techniques application in CO₂ emissions studies.

These techniques can be extended to other models to assess the impact of CO₂ emission from other sectors.

The purpose of this article was to investigate the relationship between symptoms related to air pollution, mask-wearing, mask choices and related factors.

A cross-sectional study among outpatient department (OPD) pollution clinic patients at Nopparat Rajathanee Hospital (PCNRH) during 2019 in Bangkok, Thailand.

The most common symptom after exposure to air pollution that affects treatment in the OPD is respiratory symptoms. A total of 45.7% (107/234) of the population wears a mask, 55.1% (59/107) of the population that wears a mask wears a surgical mask, and only 10.3% (11/107) of them wear an N95 mask. Mask-wearing and air quality index (AQI) onset were associated with the respiratory symptoms group, whereas wearing an N95 mask or surgical mask was found to be a protective factor for the occurrence of respiratory symptoms (adjusted OR = 0.065, 95% CI: 0.014–0.306, p = 0.001 and adjusted OR = 0.154, 95% CI: 0.058–0.404, p < 0.001, respectively). Therefore, the best practice in the face of air pollution, while the resolution needs a long period, is to wear a mask. In this study, the results showed that the best type of mask to prevent respiratory symptoms from air pollution is the N95, followed by the surgical mask; cloth masks are not recommended to use to protect against respiratory symptoms from air pollution.

Wearing an N95 and a surgical mask can help reduce respiratory symptoms. Hence, in addition to establishing hospital measures, cooperation from local and government agencies is necessary to effectively and jointly build a national health public policy framework.

1. This study provides evidence of a correlation between symptoms associated with air pollution and related factors, in-hospital visits in Bangkok, Thailand. 2. In this study, wearing an N95 mask and a surgical mask were found to be a protective factor for the occurrence of respiratory symptoms.

The purpose of this paper is to design a contract to coordinate the biomass molding fuel supply chain consisting of a supplier with uncertain supply and a producer with cyclical demand as well as improve the profit of this supply chain.

In this paper, the supply chain model was build and all the variables and assumptions are set. Stackelberg game model was used to analyze and solve the problem. Furthermore, the authors give numerical examples and result analysis on the basis of data coming from field study and online information about a real biomass fuel supply chain.

The wholesale price with shortage penalty contract the authors proposed can coordinate the supply chain. And as the dominator of the supply chain, the producer can realize the redistribution of profits within the supply chain by determine the contract parameters.

This one-to-one supply chain is a basic of complex supply chain system. Multi-to-one, one-to-multi and multi-to-multi supply chain can be studied in the future.

The results obtained in this paper can be used as a reference for enterprises in biomass energy supply chain to make contracts and realize the long-term co-operations among supply chain members.

The present research expands the debate on environmental sustainability in the wine industry. Since the literature on sustainability and wine is relatively recent, current results do not cover all the practices that can be implemented along the wine supply chain. Thus, the paper presents a classification of environmental practices specific for the wine industry, according to the increased attention that has been paid to this topic in recent years. Moreover, it investigates the adoption level of these practices with reference to Italian wine producers.

The research presents a systematic literature review including papers published in academic journals during the past 30 years and in Italian specialised magazines. This methodology is useful to provide a clear overview of sustainable practices that can be adopted along the wine supply chain. Therefore, an empirical study based on the results of an online survey shows how wineries approach environmental sustainability.

The literature review provides a definition and classification of environmental practices in the wine industry, as well as identification of those that require further attention in the literature, suggesting future research paths. The results of the online survey give an overview of the adoption level of environmental practices and highlight widespread attention to all the listed environmental practices, including those not adopted.

From a theoretical point of view, this paper fills a literature gap in terms of the definition and classification of environmental practices that cover all wine supply chain processes, also providing a useful instrument for wine companies' managers. Moreover, the results of the empirical research give an overview of the adoption level of environmental practices in one of the most relevant countries in terms of wine production and highlight widespread attention to all the listed environmental practices, including those not adopted.

This systematic review examined the emerging threat of indoor and outdoor pollutants to public health in Latin America and the Caribbean (LAC).

Pollutants and pollution levels are becoming an increasing cause for concern within the LAC region, primarily because of the rapid increase in urbanization and the use of fossil fuels. The rise in indoor and outdoor air pollutants impacts public health, and there are limited regional studies on the impact of these pollutants and how they affect public health. A comprehensive literature search was conducted using Google Scholar, PubMed, Scopus, EBSCOhost, Web of Science and ScienceDirect databases. Significant search terms included “indoor air pollution,” “outdoor air pollution,” “pollution,” “Latin America,” “Central America,” “South America” and “Caribbean was used.” The systematic review utilized the Rayyan systematic software for uploading and sorting study references.

Database searches produced 1,674 results, of which, after using the inclusion–exclusion criteria and assessing for bias, 16 studies were included and used for the systematic review. These studies covered both indoor and outdoor pollution. Various indoor and outdoor air pollutants linked to low birth weight, asthma, cancer and DNA impairment were reported in this review. Even though only some intervention programs are available within the region to mitigate the harmful effects of pollution, these programs need to be robust and appropriately implemented, causing possible threats to public health. Significant gaps in the research were identified, especially in the Caribbean.

Limitations of the study include limited available research done within LAC, with most of the research quantifying pollutants rather than addressing their impacts. Additionally, most studies focus on air pollution but neglect water and land pollution’s effects on public health. For this reason, the 16 studies included limited robustness of the review.

Although available studies quantifying pollution threats in LAC were identified in this review, research on the adverse impacts of pollution, especially concerning public health, is limited. LAC countries should explore making cities more energy-efficient, compact and green while improving the transportation sector by utilizing clean power generation. In order to properly lessen the effects of pollution on public health, more research needs to be done and implemented programs that are working need to be strengthened and expanded.

The main purpose of this study resides essentially in the development of a new tool to quantify the biomass in the bioreactor operating under steady state conditions.

Modeling is the most relevant tool for understanding the functioning of some complex processes such as biological wastewater treatment. A steady state model equation of activated sludge model 1 (ASM1) was developed, especially for autotrophic biomass (XBA) and for oxygen uptake rate (OUR). Furthermore, a respirometric measurement, under steady state and endogenous conditions, was used as a new tool for quantifying the viable biomass concentration in the bioreactor.

The developed steady state equations simplified the sensitivity analysis and allowed the autotrophic biomass (XBA) quantification. Indeed, the XBA concentration was approximately 212 mg COD/L and 454 mgCOD/L for SRT, equal to 20 and 40 d, respectively. Under the steady state condition, monitoring of endogenous OUR permitted biomass quantification in the bioreactor. Comparing XBA obtained by the steady state equation and respirometric tool indicated a percentage deviation of about 3 to 13%. Modeling bioreactor using GPS-X showed an excellent agreement between simulation and experimental measurements concerning the XBA evolution.

These results confirmed the importance of respirometric measurements as a simple and available tool for quantifying biomass.

This paper aims to assess agri-environment (AE) scheme options on cultivated agricultural land in England for their impact on agricultural greenhouse gas (GHG) emissions. It considers both absolute emissions reduction and reduction incorporating yield decrease and potential production displacement. Similarities with Ecological Focus Areas (EFAs) introduced in 2015 as part of the post-2014 Common Agricultural Policy reform, and their potential impact, are considered.

A life-cycle analysis approach derives GHG emissions for 18 key representative options. Meta-modelling is used to account for spatial environmental variables (annual precipitation, soil type and erosion risk), supplementing the Intergovernmental Panel on Climate Change methodology.

Most options achieve an absolute reduction in GHG emissions compared to an existing arable crop baseline but at the expense of removing land from production, risking production displacement. Soil and water protection options designed to reduce soil erosion and nitrate leaching decrease GHG emissions without loss of crop yield. Undersown spring cereals support decreased inputs and emissions per unit of crop yield. The most valuable AE options identified are included in the proposed EFAs, although lower priority is afforded to some.

Recommendations are made where applicable to modify option management prescriptions and to further reduce GHG emissions.

This research is relevant and of value to land managers and policy makers. A dichotomous key summarises AE option prioritisation and supports GHG mitigation on cultivated land in England. The results are also applicable to other European countries.