Search Results (15)

Numerous studies have shown negative health effects related to exposure to ambient particulate matter (PM), likely due to induced oxidative stress. In this study, we have examined ambient PM samples from Birr, a small (~5000 inhabitants) town in central Ireland, for their water-soluble DTT-based oxidative potential (OP_DTT) with a resolution of 6 h, together with online chemical characterization measurements, to assess the OP of organic aerosols, in particular from residential solid fuel burning. The OP_DTT normalized by the volume of sampled air shows a high variability, ranging from <0.1 to 3.8 nmol min⁻¹ m⁻³, and a high correlation with PM mass. A lower variability was associated with the mass-normalized OP. Nevertheless, both tended to present higher values during night-time pollution episodes. Simple and multivariate linear regression approaches linked OP_DTT to residential solid fuel burning, and in particular to wood (~87%) and peat (~13%) combustion. The results of the present study show how residential solid fuel burning can have a severe impact on air quality, even in small towns, with potential negative health effects on the exposed population. Full article

Rice cultivation stands as the primary agricultural activity in Asia, generating a substantial amount of agricultural waste. Unfortunately, this waste is often disposed of through burning, contributing to severe environmental, health and climate issues. This study presents the characterization of PCDD/Fs, PCBs and PAHs. The emissions were quantified using a fixed-grid-system biomass plant and measuring the macro-pollutants online and sampling the organic micro-pollutants and metals in isokinetic mode, followed by ISO and CEN standards methods. Additionally, the role of agrochemicals was monitored in terms of metal catalysis resulting in POP emissions. This study provides the comprehensive characterization of the most relevant groups of pollutants (metals, PCDD/Fs, PCBs and PAHs) resulting from agricultural waste combustion. Prominent catalytic metals quantified were Cu (22–48 µg/Nm³) and Fe (78–113 µg/Nm³). Rice straw samples from AJK exhibited higher values of organochlorine micro-pollutants compared to those from Punjab and Sindh, i.e., ∑PCDD/F (2594 > 1493 > 856 pg/Nm³) and ∑PCB (41 > 38 > 30 pg/Nm³), respectively, whereas the organic micro-pollutants ∑c-PAH, indicators of incomplete combustion (PICs), were recorded high in the samples from Sindh followed by Punjab and AJK. The average EF is 100 pg/kg, 2.2 pg/kg and 1053.6 µg/kg for ∑PCDD/F, ∑PCB and ∑c-PAH. This study supports the idea that the phenomena leading to the formation of dioxin and dioxin-like compounds are influenced not only by poor combustion but also by the presence of metal catalysts in the burned fuel. Full article

Ship emissions are a major cause of global air pollution, and in particular, emissions from the combustion of bunker fuels, such as heavy fuel oil (HFO), show strong impacts on the environment and human health. Therefore, sophisticated measurement techniques are needed for monitoring. We present here an approach to remotely investigating ship exhaust plumes through onboard measurements from a research vessel in the Baltic Sea. The ship exhaust plumes were detected from a distance of ~5 km by rapid changes in particle number concentration and a variation in the ambient particle size distribution utilizing a condensation particle counter (CPC) and a scanning mobility particle sizer (SMPS) instrument. Ambient single particles in the size range of 0.2–2.5 µm were qualitatively characterized with respect to their chemical signature by single-particle mass spectrometry (SPMS). In particular, the high sensitivity of the measurement method for transition metals in particulate matter (PM) was used to distinguish between the different marine fuels. Despite the high complexity of the ambient aerosol and the adverse conditions at sea, the exhaust plumes of several ships could be analyzed by means of the online instrumentation. Full article

Atmospheric aerosols, produced as a consequence of different anthropogenic and natural processes, impart significant control over the global energy budget, climate, and human–environmental health. Their size varies across the nano–micrometer scale. Based on their origin, they may be classified into primary or secondary aerosols. Biomass burning, incomplete combustion of fossil fuels, volcanic eruptions, and traffic-related and wind-driven suspensions contribute to primary aerosol emissions. In contrast, gas-to-particle conversion within the atmosphere leads to secondary particle production. The study of atmospheric aerosols is vital to the field of atmospheric research. The dynamic nature (highly variable concentration composition and size with space and time) of aerosols makes them difficult to investigate. Today, aerosol research involves the application of various spectrometric and spectroscopic techniques. The single-particle analysis of aerosols is yet a challenge. In this review, the merits and demerits of various offline and online techniques used for aerosol research are discussed in a nutshell. Mass spectrometric techniques fail in distinguishing certain species. However, Raman spectroscopy’s emergence for the compositional analysis of aerosols resolves most of the present characterization challenges. This review focuses on Raman spectroscopy applications, the merits of this technique, and its immense scope for the measurement of various types of aerosols and their properties. Surface-enhanced Raman spectroscopy (SERS) has an advantage over conventional micro-Raman spectroscopy (MRS). The review depicts the dominance of SERS, specifically in the context of the measurement of ambient atmospheric aerosols. This review discusses two important components, namely laboratory simulation and ambient aerosol studies. Full article

Alkali metal compounds are released during the thermal conversion of biofuels and fossil fuels and have a major impact on the efficiency of conversion processes. Herein, we describe a novel method for the simultaneous characterization of alkali release and mass loss from materials used in combustion and gasification processes including solid fuels, fluidized bed materials, and catalysts for gas reforming. The method combines the thermogravimetric analysis of selected samples with the on-line measurement of alkali release using a surface ionization detector. The technique builds on the careful treatment of alkali processes during transport from a sample to the downstream alkali monitor including the losses of alkali in the molecular form to hot walls, the formation of nanometer-sized alkali-containing particles during the cooling of exhaust gases, aerosol particle growth, and diffusion losses in sampling tubes. The performance of the setup was demonstrated using biomass samples and fluidized bed material from an industrial process. The emissions of alkali compounds during sample heating and isothermal conditions were determined and related to the simultaneous thermogravimetric analysis. The methodology was concluded to provide new evidence regarding the behavior of alkali in key processes including biomass pyrolysis and gasification and ash interactions with fluidized beds. The implications and further improvements of the technique are discussed. Full article

Port cities are affected by a wide array of emissions, including those from the shipping, road transport, and residential sectors; therefore, the characterization and apportionment of such sources in a high temporal resolution is crucial. This study presents measurements of fine aerosol chemical composition in Piraeus, one of the largest European ports, during two monthly periods (winter vs. summer) in 2018–2019, using online instrumentation (Aerosol Chemical Speciation Monitor—ACSM, 7-λ aethalometer). PMF source apportionment was performed on the ACSM mass spectra to quantify organic aerosol (OA) components, while equivalent black carbon (BC) was decomposed to its fossil fuel combustion and biomass burning (BB) fractions. The combined traffic, shipping and, especially, residential emissions led to considerably elevated submicron aerosol levels (22.8 μg m⁻³) in winter, which frequently became episodic late at night under stagnant conditions. Carbonaceous compounds comprised the major portion of this submicron aerosol in winter, with mean OA and BC contributions of 61% (13.9 μg m⁻³) and 16% (3.7 μg m⁻³), respectively. The contribution of BB to BC concentrations was considerable and spatially uniform. OA related to BB emissions (fresh and processed) and hydrocarbon-like OA (from vehicular traffic and port-related fossil fuel emissions including shipping) accounted for 37% and 30% of OA, respectively. In summer, the average PM₁ concentration was significantly lower (14.8 μg m⁻³) and less variable, especially for the components associated with secondary aerosols (such as OA and sulfate). The effect of the port sector was evident in summer and maintained BC concentrations at high levels (2.8 μg m⁻³), despite the absence of BB and improved atmospheric dispersion. Oxygenated components yielded over 70% of OA in summer, with the more oxidized secondary component of regional origin being dominant (41%) despite the intensity of local sources, in the Piraeus environment. In general, with respect to local sources that can be the target of mitigation policies, this work highlights the importance of port-related activities but also reveals the extensive wintertime impact of residential wood burning. While a separation of the BB source is feasible, more research is needed on how to disentangle the short-term effects of different fossil-fuel combustion sources. Full article

This paper presents a ultrasonic-capacitive system for online analysis of the quality of fuel oils (FO), which are widely used to produce electric energy in Thermal Power Plants (TPP) due to their elevated heating value. The heating value, in turn, is linked to the quality of the fuel (i.e., the density and the amount of contaminants, such as water). Therefore, the analysis of the quality is of great importance for TPPs, either in order to avoid a decrease in generated power or in order to avoid damage to the TPP equipment. The proposed system is composed of two main strategies: a capacitive system (in order to estimate the water content in the fuel) and an ultrasonic system (in order to estimate the density). The conjunction of the two strategies is used in order to estimate the heating value of the fuel, online, as it passes through the pipeline and is an important tool for the TPP in order to detect counterfeit fuel. In addition, the ultrasonic system allows the estimation of the flow rate through the pipeline, hence estimating the amount of oil transferred and obtaining the total mass transferred as a feature of the system. Experimental results are provided for both sensors installed in a TPP in Brazil. Full article

Due to the low efficiency and high pollution of conventional internal combustion engine vehicles, the fuel cell hybrid electric vehicles are expected to play a key role in the future of clean energy transportation attributed to the long driving range, short hydrogen refueling time and environmental advantages. The development of energy management strategies has an important impact on the economy and durability, but most strategies ignore the aging of fuel cells and the corresponding impact on hydrogen consumption. In this paper, a rule-based fuzzy control strategy is proposed based on the constructed data-driven online estimation model of fuel cell health. Then, a genetic algorithm is used to optimize this fuzzy controller, where the objective function is designed to consider both the economy and durability by combining the hydrogen consumption cost and the degradation cost characterized by the fuel cell health status. Considering that the rule-based strategy is more sensitive to operating conditions, this paper uses an artificial neural network for predictive control. The results are compared with those obtained from the genetic algorithm optimized fuzzy controller and are found to be very similar, where the prediction accuracy is assessed using MAPE, RMSE and 10-fold cross-validation. Experiments show that the developed strategy has a good generalization capability for variable driving cycles. Full article

Academics and policymakers recognize the absence of empirically grounded research to support the suppositions on which terrorist focused policies are based. (Sageman, Marc. 2014. “The Stagnation in Terrorism Research”. Terrorism and Political Violence 26 (4): 565–80) We developed our project, Mapping Networks and Narratives of Online Right-Wing Extremists in New South Wales, (Department of Security Studies and Criminology. 2020. Mapping Networks and Narratives of Online Right-Wing Extremists in New South Wales. https://doi.org/10.5281/zenodo.4071472) to illuminate this space. Using the analysis of large-scale online data to generate evidence-based insights into online Right-Wing Extremism (RWE) across the state, our research focused on four key questions: (1) What is the nature of the online RWE environment in New South Wales, Australia (NSW)? (2) How is this movement distributed across NSW? (3) How are themes and narratives framed in different online contexts to mobilize support? (4) What level of risk does the online right-wing environment pose? These questions were left purposely broad to facilitate an exploratory project into what was, in 2018–2019, still a relatively little studied milieu. We combined expertise from computational science, security studies, and behavioral science. We were funded by the Department of Communities and Justice, NSW. We identified two distinct—yet connected—levels of risk. The first was a creeping threat to democracy fueled by networks and content that challenged the fundamental principles of pluralistic liberal democracy. The second was a risk of violence perpetrated by individuals and/or groups that advocate and/or support the use of violence as a tactic to achieve an ideological end. The communities we examined were primarily characterized by networks of individuals as opposed to formal groups. The role played by individual influencers has important ramifications for policy communities: attention should be paid to issues of proscription and moderation. While this milieu engaged with Australian issues and events, it was notably far more obsessed with American issues: particularly those focused on populist narratives and Trumpism. Despite being hateful and extreme, online RWE communities are, firstly, spaces of sociability for users, where social networks are maintained by shared values and norms. For those involved, these spaces engender positive experiences: individuals might share an image of their dinner cooking in their kitchen interspersed with “shitposting” and virulent hate speech. While we identified a variety of narratives that focused on the delegitimization of government and dehumanization of others, the central theme was that of “white identity under threat”. We observed five distinct stages of moderation approach and echo chamber strength. A series of issues for future consideration were identified from the analysis: (1) Awareness raising for key stakeholders across different levels of government and civil society about the revolutionary and anti-social agenda of RWE communities. (2) Building awareness about the civic underpinnings of representative liberal democracy and the threat that RWE poses. (3) Expanding current Countering Violent Extremism infrastructure provided by the NSW government to individuals and communities vulnerable to right wing extremism. (4) The local government is well positioned to deliver programs in rural communities impacted by RWE. (5) Upskilling front-line workers to recognize the risks associated with RWE, and providing pathways into CVE intervention programs for individuals identified as being at-risk. Full article

The heterogeneity of biogenic fuels, and especially biogenic residues with regard to water and ash content, particle size and particle size distribution is challenging for biomass combustion, and limits fuel flexibility. Online fuel characterization as a part of process control could help to optimize combustion processes, increase fuel flexibility and reduce emissions. In this research article, a concept for a new sensor module is presented and first tests are displayed to show its feasibility. The concept is based on the principle of hot air convective drying. The idea is to pass warm air with 90 °C through a bulk of fuel like wood chips and measure different characteristics such as moisture, temperatures and pressure drop over the bulk material as a function over time. These functions are the basis to draw conclusions and estimate relevant fuel properties. To achieve this goal, a test rig with a volume of 0.038 m³ was set up in the laboratory and a series of tests was performed with different fuels (wood chips, saw dust, wood pellets, residues from forestry, corn cobs and biochar). Further tests were carried out with conditioned fuels with defined water and fines contents. The experiments show that characteristic functions arise over time. The central task for the future will be to assign these functions to specific fuel characteristics. Based on the data, the concept for a software for an automated, data-based fuel detection system was designed. Full article

To expand markets for plug-in electric vehicles (EVs) beyond enthusiastic early adopters, investments must be strategic. This research characterizes a segment of EV adoption that points the way toward the mainstream: EV consumers with low or no initial interest in EVs, or “EV Converts.” Logistic regression is utilized to profile EV Convert demographic, household, and regional characteristics; vehicle-transaction details; and purchase motivations—based on 2016–2017 survey data characterizing 5447 rebated California EV consumers. Explanatory factors are rank-ordered—separately for battery EVs (BEVs) and plug-in hybrid EVs (PHEVs), to inform targeted outreach and incentive design. EV Converts tend to have relatively “lower” values on factors that might have otherwise “pre-converted” them to EV interest: hours researching EVs online; motivation from environmental impacts and carpool-lane access; and solar ownership. PHEV Converts more closely resemble new-car buyers than other EV adopters, and BEV Converts actually tend to be younger and less-frequently white/Caucasian than new-car buyers. BEV Converts also tend to: lack workplace charging, be moderately motivated by energy independence, and reside in Southern California or the Central Valley. Predictors that not only help target consumers, but also help convert them, include rebates for BEV consumers and, modestly, fuel-cost savings for PHEV consumers. Full article

In many industrial fields, there is a need to design and characterize on-line and on-board hydrogen monitoring tools able to operate under extreme conditions. One of these applications is in future nuclear fusion reactors, which will use hydrogen isotopes as a plasma fuel. In this context, the measurement of the concentration of these hydrogen isotopes will be of interest to ensure the correct operating conditions for such reactors. Hydrogen sensors based on solid-state electrolytes will be the first step in the development of new analytical tools able to quantify deuterium and tritium in aggressive environments. In the present work, amperometric hydrogen sensors were constructed and evaluated using two solid-state electrolytes, BaCe_0.6Zr_0.3Y_0.1O_3-α and Sr(Ce_0.9Zr_0.1)_0.95Yb_0.05O_3-α. Prototype sensors were built in order to study their sensitivity in on-line measurements. The experiments were performed in a reactor with a hydrogen-controlled environment. The sensors were evaluated at 500 and 600 °C in amperometric mode by applying 2 and 4 V voltages between electrodes. Both sensors showed increases in sensitivity when the temperature or voltage were increased. Full article

Online/on-board diagnosis would help to improve fuel cell system durability and output power. Therefore, it is a feature the manufacturers may wish to provide for final users to increase the attractiveness of their product. This add-on requires suitable stack models, parametric identification tools and diagnostic algorithms to be run on low-cost embedded systems, ensuring a good trade-off between accuracy and computation time. In this paper, a computational approach for the impedance parameter identification of polymer electrolyte membrane fuel cell stack is proposed. The method is based on an evolutionary algorithm including sub-population and migration features, which improves the exploration capability of the search space. The goal of the evolutionary algorithm is to find the set of parameters that minimizes an objective function, representing the mismatch between two impedance plots in a normalized plane. The first plot is associated with experimental impedance and the second is computed on the basis of the identified parameters using a circuit model. Three kinds of impedance models, characterized by increasing computational complexity, are used, depending on the experimental data—a linear model made of resistors and capacitors, the Fouquet model and the Dhirde model. Preliminary analysis of the experimental impedance data may evidence correlations among parameters, which can be exploited to reduce the search space of an evolutionary algorithm. The computational approach is validated with literature data in a simulated environment and with experimental data. The results show good accuracy and a computational performance that fits well with the commercial embedded system hardware resources. The implementation of the approach on a low-cost off-the-shelf device achieves small computation times, confirming the suitability of such an approach to online/on-board applications. From a diagnostic perspective, the paper outlines a diagnostic approach based on the identified impedance parameters, on the basis of a small set of experimental data including fuel cell stack faulty conditions. Full article

Glycerol remains a bottleneck for the biodiesel industry as well as an opportunity from the biorefinery perspective, having a notable reactivity as a platform chemical. In particular, glycerol ketals can be envisaged as oxygenates for fuel formulation. In this study, we have focused on the green synthesis of glycerol ketals by reacting glycerol with acyclic (acetone, butanone) and cyclic (cyclohexanone) ketones in the presence of an acid activated clay Tunisian AC in homogeneous systems under quasi-solventless conditions. These reactions were followed by on-line Fourier Transform Infrared Spectroscopy (FTIR) (namely, ReactIR 10). Firstly, the contacting time was selected studying the activity, stability and chemical characteristics of a set of catalysts. The 1-h activated clay AC was further characterized by X-Ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electronic Microscopy with Energy Dispersive Spectroscopy (SEM/EDS). Finally, the effect of the main operational variables (catalyst concentration, reagents molar ratio, time and temperature) were checked and we reflected on adequate second-order kinetic models with partial first-order deactivation. Full article

Bio-electrochemical systems such as microbial fuel cells and microbial electrosynthesis cells depend on efficient electron transfer between the microorganisms and the electrodes. Understanding the mechanisms and dynamics of the electron transfer is important in order to design more efficient reactors, as well as modifying microorganisms for enhanced electricity production. Geobacter are well known for their ability to form thick biofilms and transfer electrons to the surfaces of electrodes. Currently, there are not many “on-line” systems for monitoring the activity of the biofilm and the electron transfer process without harming the biofilm. Raman microscopy was shown to be capable of providing biochemical information, i.e., the redox state of C-type cytochromes, which is integral to external electron transfer, without harming the biofilm. In the current study, a custom 3D printed flow-through cuvette was used in order to analyze the oxidation state of the C-type cytochromes of suspended cultures of three Geobacter sulfurreducens strains (PCA, KN400 and ΔpilA). It was found that the oxidation state is a good indicator of the metabolic state of the cells. Furthermore, an anaerobic fluidic system enabling in situ Raman measurements was designed and applied successfully to monitor and characterize G. sulfurreducens biofilms during electricity generation, for both a wild strain, PCA, and a mutant, ΔS. The cytochrome redox state, monitored by the Raman peak areas, could be modulated by applying different poise voltages to the electrodes. This also correlated with the modulation of current transferred from the cytochromes to the electrode. The Raman peak area changed in a predictable and reversible manner, indicating that the system could be used for analyzing the oxidation state of the proteins responsible for the electron transfer process and the kinetics thereof in-situ. Full article