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The aim of the paper is to present the results of investigations of fine particle generation by small biomass combustion and the possibility of reducing the emissions by electrostatic precipitation.

The grains, wood‐logs, wood‐, mixed‐ and straw‐pellets were combusted in two stoves and two boilers. The set‐ups were operated according to DIN‐4702. Particle number concentration in the gas flow was measured by Scanning Mobility Particle Sizer and particle mass concentration was measured according to the Guidelines VDI‐2066 upstream and downstream a novel space charge electrostatic precipitator (ESP). The ESP consists of an ioniser and a grounded brush inside of a tube form grounded collector electrode.

The ESP ensures stable operation at gas temperatures up to 350°C. The use of sharp‐points high voltage electrode ensures effective particle charging at high particle number concentrations. The combustion of wood‐pellets is characterized by lower particle mass concentrations. The highest particle mass concentrations were observed by the straw‐pellets combustion. The ESP ensures particle collection with mass collection efficiency 87±3% for wood‐logs and 82±2% for wood‐pellets combustion.

The novel ESP is recommended for exhaust gas cleaning from small scale biomass combustion facilities and domestic heating units. The use of the ESP would reduce the emissions of fine aerosol into the atmosphere and improve the air quality.

The paper presents the comparative analysis of particle size distribution and particle mass concentrations in the exhaust gas from small‐scale combustion units for different types of biomass. The study confirms the possibility to reduce particle emissions by electrostatic precipitation. The originality of the technology and apparatus is patently protected.

In the recent years the interest toward the use of biomass as a fuel for energy conversion, along with the continuous tightening of regulations, has driven the improvement of accurate design techniques which are required to optimize the combustion process and simultaneously control pollutant emissions. In this paper the use of a 3D Computational Fluid Dynamics approach is analyzed to that aim by means of an application to an existing 50 MW biomass fixed-bed combustion furnace fueled by grape marc. The paper aims to discuss these issues.

The studied furnace is an interesting example of biomass utilization as it may integrate biomass with organic residual by an industrial process. The numerical model has been implemented into an OpenFOAM solver, with an Eulerian-Lagrangian approach. In particular, the fully 3D approach here presented, directly solves for the gas and solid evolution in both the combustion bed and the freeboard. Special care has also been devoted to the treatment of radiating fluxes, having a remarkable influence, again, on the bed evolution.

Results have been compared to experimental data in terms of temperature showing a good agreement. Further comparisons have been done with literature available data for a similar power size biomass furnace showing reasonable similarities.

Emission formation processes in a biomass furnace are dealt with in this paper. The innovation lies in the use of a fully 3D numerical approach, that is validated with regard to temperature measurements gathered in a multi-MW experimental furnace.

Decreasing energy demand due to improved building standards requires the development of new biomass combustion technologies to be able to provide individual biomass heating solutions. The purpose of this paper is, therefore, the development of a pellet water heating stove with minimal emission at high thermal efficiency.

The single components of a 10 kW water heating pellet stove are analysed and partly redesigned considering the latest scientific findings and experimental know‐how in combustion engineering. The outcome of this development is a 12 kW prototype which is subsequently down‐scaled to a 6 kW prototype. Finally, the results of the development are evaluated by testing of an accredited institute.

Based on an existing pellet water heating stove, the total excess air ratio was reduced, a strict air staging was implemented and the fuel supply was homogenized. All three measures improved the operating performance regarding emissions and thermal efficiency. The evaluation of the development process showed that the CO emissions are reduced by over 90 per cent during full load and by 30‐60 per cent during minimum load conditions. Emissions of particulate matter are reduced by 70 per cent and the thermal efficiency increased to 95 per cent.

The result represents a new state of technology in this sector for minimal emissions and maximal thermal efficiency, which surpasses the directives of the Eco label “UZ37” in Austria and “Blauer Engel” in Germany, which are amongst the most stringent performance requirements in the European Union. Hence this design possesses a high potential as heating solution for low and passive energy houses.

The purpose of this paper is to assess the exposure of cooks in rural India (55 households) to the indoor air pollution levels emitted from burning of different fuels, i.e. cow dung, wood, liquefied petroleum gas (LPG) and propane natural gas(PNG) kerosene for cooking purposes.

Indoor air quality was monitored during cooking hours in 55 rural households to estimate the emissions of PM10, PM2.5, CO, NO₂, VOCs and polyaromatic hydrocarbons (PAHs). While, PM10 and PM2.5 were monitored using personal dust samplers on quartz filter paper, CO and VOCs were monitored using on line monitors. The PM10 and PM2.5 mass collected on filter papers was processed to analyse the presence of PAHs using GC.

Results revealed that cow dung is the most polluting fuel with maximum emissions of PM10, PM 2.5, VOCs, CO, NO₂ and Benzene followed by wood and kerosene. Interestingly kerosene combustion emits the highest amount of PAHs. Emissions for all the fuels show the presence of carcinogenic PAHs which could be a serious health concern. The composition of LPG/PNG leads to reductions of pollutants because of better combustion process. LPG which is largely propane and butane, and PNG which is 90 per cent methane prove to be healthier fuels. Based on the results, the authors suggest that technological intervention is required to replace the traditional stoves with improved fuel efficient stoves.

The prevailing weather condition and design of the kitchen in these rural houses severely affect the concentration of pollutants in the kitchen as winter season combined with inadequate ventilation leads to reduced dispersion and accumulation of air pollutants in small kitchens.

The present study provides a detailed analysis of impact of widely‐used cooking practices in India. Even today, countries such as India rely on biomass for cooking practices exposing the cooks to high level of carcinogenic pollutants. Further, women and girls are the most threatened group as they are the primary cooks in these rural Indian settings. Based on the results, the authors suggest that technological as well as policy intervention is required to replace the traditional stoves with improved fuel efficient stoves.

Purpose – This chapter compares bioenergy policy developments in Germany and Denmark to better understand the responses of EU country policy regimes to global shocks; to examine potentially emerging new trends of productivist policy models; and to explore potential land use conflicts in the context of a multifunctional EU agricultural policy.

Design/methodology/approach – The chapter reviews the bioenergy policy development pathways taken by Germany and Denmark, highlighting key consequences for agricultural land use and rural development. Findings from both case studies are then compared in summary tables, followed by a discussion of the possible emergence of productivist policy approaches in the bioenergy sector in these countries.

Findings – The bioenergy policies pursued by both countries differ in key respects and yet have had the same result-an increase in the productivist orientation of agriculture, legitimised by the environmental concerns of bioenergy policy. The Danish and German case studies also demonstrate that the particular pathways taken to establish bioenergy policies in each country have been strongly influenced by local political, farming and technological dynamics.

Originality/value – This chapter presents a telling case of what Burton and Wilson (this volume) call “repositioned productivism”, where productivist approaches benefit from environmental or multifunctional policy rationale to continue at the farm level.

Brewer's spent grain (BSG) is the main by-product of the brewing industry, holding significant potential for biomass applications. The purpose of this paper was to determine the effective thermal conductivity (k_eff) of BSG and to develop an Artificial Neural Network (ANN) to predict k_eff, since this property is fundamental in the design and optimization of the thermochemical conversion processes toward the feasibility of bioenergy production.

The experimental determination of k_eff as a function of BSG particle diameter and heating rate was performed using the line heat source method. The resulting values were used as a database for training the ANN and testing five multiple linear regression models to predict k_eff under different conditions.

Experimental values of k_eff were in the range of 0.090–0.127 W m⁻¹ K⁻¹, typical for biomasses. The results showed that the reduction of the BSG particle diameter increases k_eff, and that the increase in the heating rate does not statistically affect this property. The developed neural model presented superior performance to the multiple linear regression models, accurately predicting the experimental values and new patterns not addressed in the training procedure.

The empirical correlations and the developed ANN can be utilized in future work. This research conducted a discussion on the practical implications of the results for biomass valorization. This subject is very scarce in the literature, and no studies related to k_eff of BSG were found.

This paper aims to analyze the performance of artificial neural networks with filling methods in predicting the minimum fluidization velocity of different biomass types for bioenergy applications.

An extensive literature review was performed to create an efficient database for training purposes. The database consisted of experimental values of the minimum fluidization velocity, physical properties of the biomass particles (density, size and sphericity) and characteristics of the fluidization (monocomponent experiments or binary mixture). The neural models developed were divided into eight different cases, in which the main difference between them was the filling method type (K-nearest neighbors [KNN] or linear interpolation) and the number of input neurons. The results of the neural models were compared to the classical correlations proposed by the literature and empirical equations derived from multiple regression analysis.

The performance of a given filling method depended on the characteristics and size of the database. The KNN method was superior for lower available data for training and specific fluidization experiments, like monocomponent or binary mixture. The linear interpolation method was superior for a wider and larger database, including monocomponent and binary mixture. The performance of the neural model was comparable with the predictions of the most well-known correlations from the literature.

Techniques of machine learning, such as filling methods, were used to improve the performance of the neural models. Besides the typical comparisons with conventional correlations, comparisons with three main equations derived from multiple regression analysis were reported and discussed.

This study aims to present preliminary results from an integrated evaluation of electricity supply systems for rural areas using renewable energy technologies by means of a multi‐objective decision making method

Goal programming is applied to obtain the optimal system configuration meeting the electricity demand, based on the location's resource availability and taking diesel generation as the alternative of reference. The performance of the system is evaluated through four attributes: electricity generation costs, employment and two environmental impacts (CO₂ emissions and land use). The model is designed for isolated rural area belonging to the non‐interconnected zones of Colombia.

Application of the method showed that biomass conversion technology has the highest potential and that renewable energy systems offer better performance than diesel generation. Reductions of more than 10 percent in unit electricity costs, land use rates and CO₂ emissions can be achieved.

Inclusion of additional attributes and sensitivity analysis are matters of future research.

The methodology used in this study is an alternative means to perform evaluation of electricity supply systems integrating several aspects of technology and which is flexible enough so as to enable the inclusion of a wider scope of interests towards energy access targets.

Focuses on the direct and indirect impact of environmental abuse on human wellbeing. In some instances, the impact of environmental abuse on human health is not still unknown, merely being subject to scientific suspicion. This would suggest caution and the need for preventive measures to be applied. The threat to human health from environmental factors is not an isolated problem that exists on a national level. There are environmental factors that affect human health on a global level or are so widespread as to be considered global problems. Other environmental problems cross national boundaries and achieve regional importance.

The purpose of this paper is to report a novel formulation of convective heat transfer source term for the case of flow through porous medium.

The novel formulation is obtained by analytical solution of an idealized dual problem. Computations are performed by dedicated tool for fixed bed combustion named GRATECAL and developed by the authors. However, the proposed method can also be applied to other porous media flow problems.

The new source term formulation is unconditionally stable and it respects exponential decay of temperature difference between the fluid and porous solid medium.

The results of this work are applicable in the simulation of convective heat transfer between the fluid and porous medium. Applications include e.g. fixed bed combustion, catalytic reactors and lime kilns.

The reported solution is believed to be original. It will be useful to all involved in numerical simulations of fluid flow in porous media with convective heat transfer.