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Rising pollution levels resulting from vehicular emissions and the depletion of petroleum-based fuels have left mankind in pursuit of alternatives. There are stringent regulations around the world to control the particulate matter (PM) emissions from internal combustion engines. To this end, researchers have been exploring different measures to reduce PM emissions such as using modern combustion techniques, after-treatment systems such as diesel particulate filter (DPF) and gasoline particulate filter (GPF), and alternative fuels. Alternative fuels such as biodiesel (derived from edible, nonedible, and waste resources), alcohol fuels (ethanol, n-butanol, and n-pentanol), and fuel additives have been investigated over the last decade. PM characterization and toxicity analysis is still growing as researchers are developing methodologies to reduce particle emissions using various approaches such as fuel modification and after-treatment devices. To address these aspects, this review paper studies the PM characteristics, health issues, PM physical and chemical properties, and the effect of alternative fuels such as biodiesel, alcohol fuels, and oxygenated additives on PM emissions from diesel engines. In addition, the correlation between physical and chemical properties of alternate fuels and the characteristics of PM emissions is explored.

As a biofuel feedstock, microalgae has good scalability and potential to supply a significant proportion of world energy compared to most types of biofuel feedstock. Hydrothermal liquefaction (HTL) is well-suited to wet biomass (such as microalgae) as it greatly reduces the energy requirements associated with dewatering and drying. This article presents experimental analyses of chemical and physical properties of bio-crude oil produced via HTL using a high growth-rate microalga Scenedesmus sp. in a large batch reactor. The overarching goal was to investigate the suitability of microalgae HTL bio-crude produced in a large batch reactor for direct application in marine diesel engines. To this end we characterized the chemical and physical properties of the bio-crudes produced. HTL literature mostly reports work using very small batch reactors which are preferred by researchers, so there are few experimental and parametric measurements for bio-crude physical properties, such as viscosity and density. In the course of this study, a difference between traditionally calculated values and measured values was noted. In the parametric study, the bio-crude viscosity was significantly closer to regular diesel and biodiesel standards than transesterified (FAME) microalgae biodiesel. Under optimised conditions, HTL bio-crude’s high density (0.97–1.04 kg·L−1) and its high viscosity (70.77–73.89 mm2·s−1) had enough similarity to marine heavy fuels. although the measured higher heating value, HHV, was lower (29.8 MJ·kg−1). The reaction temperature was explored in the range 280–350 °C and bio-crude oil yield and HHV reached their maxima at the highest temperature. Slurry concentration was explored between 15% and 30% at this temperature and the best HHV, O:C, and N:C were found to occur at 25%. Two solvents (dichloromethane and n-hexane) were used to recover the bio-crude oil, affecting the yield and chemical composition of the bio-crude.

Over the past few decades, biodiesel produced from oilseed crops and animal fat is receiving much attention as a renewable and sustainable alternative for automobile engine fuels, and particularly petroleum diesel. However, current biodiesel production is heavily dependent on edible oil feedstocks which are unlikely to be sustainable in the longer term due to the rising food prices and the concerns about automobile engine durability. Therefore, there is an urgent need for researchers to identify and develop sustainable biodiesel feedstocks which overcome the disadvantages of current ones. On the other hand, artificial neural network (ANN) modeling has been successfully used in recent years to gain new knowledge in various disciplines. The main goal of this article is to review recent literatures and assess the state of the art on the use of ANN as a modeling tool for future generation biodiesel feedstocks. Biodiesel feedstocks, production processes, chemical compositions, standards, physio-chemical properties and in-use performance are discussed. Limitations of current biodiesel feedstocks over future generation biodiesel feedstock have been identified. The application of ANN in modeling key biodiesel quality parameters and combustion performance in automobile engines is also discussed. This review has determined that ANN modeling has a high potential to contribute to the development of renewable energy systems by accelerating biodiesel research.