Particulate emissions from biodiesel fuelled CI engines

Energy demand, decreasing fossil fuel reserves, and health-related issues about pollutants have led researchers to search for renewable alternative fuels to either partially or fully replace fossil fuels. Among many alternative fuels, biodiesel became one of the most popular choices due to similar properties to that of conventional diesel. Biodiesel produces slightly lower brake thermal efficiency compared to that of conventional biodiesel, but has an advantage of reduced emissions of CO2, CO, HC, and smoke. However, biodiesel shows higher NOx emission which, when used in increased biodiesel market, may become a serious problem. Various strategies were attempted by different researcher to reduce NOx emissions. In this paper, various strategies, adapted for reducing NOx emissions of biodiesel fuel used in diesel engines for automobile applications, are reviewed and discussed. The strategies are grouped into three major groups, namely combustion treatments, exhaust after-treatments, and fuel treatme...

Various strategies for reducing Nox emissions of biodiesel fuel used in conventional diesel engines: A review

Enhanced diesel emissions at low ambient temperature: hazardous materials in fine particles.

Characterization of Criteria and Organic Matter Emissions from a Nonroad Diesel Engine Equipped with a Selective Catalytic Reduction System

Compression ignition engine ─ solutions for reducing pollutant emissions

The effects of a diesel oxidation catalytic (DOC) converter on diesel engine emissions were investigated on a diesel bench at various loads for two steady-state speeds using diesel fuel and B20. The DOC was very effective in hydrocarbon (HC) and CO oxidation. Approximately 90%–95% reduction in CO and 36%–70% reduction in HC were realized using the DOC. Special attention was focused on the effects of the DOC on elemental carbon (EC) and organic carbon (OC) fractions in fine particles (PM2.5) emitted from the diesel engine. The carbonaceous compositions of PM2.5 were analyzed by the method of thermal/optical reflectance (TOR). The results showed that total carbon (TC), OC and EC emissions for PM2.5 from diesel fuel were generally reduced by the DOC. For diesel fuel, TC emissions decreased 22%–32% after the DOC depending on operating modes. The decrease in TC was attributed to 35%–97% decrease in OC and 3%–65% decrease in EC emissions. At low load, a significant increase in the OC/EC ratio of PM2.5 was observed after the DOC. The effect of the DOC on the carbonaceous compositions in PM2.5 from B20 showed different trends compared to diesel fuel. At low load, a slight increase in EC emissions and a significant decrease in OC/EC ratio of PM2.5 after DOC were observed for B20.

Effects of a diesel oxidation catalyst on gaseous pollutants and fine particles from an engine operating on diesel and biodiesel

Prediction of municipal solid waste (MSW) generation plays an essential role in effective waste management. The main objectives of this study were to develop models for accurate prediction of MSW generation (MSWG) and analyze the influence of dominant variables on MSWG. To elevate the model’s prediction accuracy, more than 50 municipal variables were considered original variables, which were selected from 12 categories. According to the screening results, the dominant variables are classified into four categories: urban greening, population size and residential density, regional economic development and resident income and expenditure. Among the seven machine learning methods, back propagation (BP) neural network has the best model evaluation effect. The R2 of the BP neural network model of Jiangsu, Zhejiang and Shandong provinces were 0.969, 0.941 and 0.971 respectively. The prediction accuracy of Shandong province (93.8%) was the best, followed by Jiangsu province (92.3%) and Zhejiang province (72.7%). The correlation between dominant variables and the MSWG was mined, suggesting that regional GDP and the total retail sales of consumer goods were the most important dominant variables affecting MSWG. Moreover, the MSWG might not absolutely associate with the population size and residential density. The method used in this study is a practical tool for policymakers on regional/local waste management and MSWG control.

Prediction of municipal solid waste generation and analysis of dominant variables in rapidly developing cities based on machine learning - a case study of China.

Energy production and consumption are dominant sources of CO2 emissions. Investigating the amount and characteristics of CO2 emission sources can aid in reducing CO2 emissions from energy-related sectors, which could lead to the development of advanced technologies and ideas for abatement. Cities play a significant role in CO2 emissions, representing a distinctive unit with a specialized energy consumption structure, meteorology, economy, agriculture, forest acreage, etc. Those properties interact and influence CO2 emissions. The city-level emission inventory is an important scientific database helping to investigate emission abatement technologies and establish control strategies. In this study, city-level CO2 emissions and ecological absorption of China’s coldest province are quantified. In the targeted region, winter lasts for about 6 months. Sectors of industry, thermal power generation, and domestic heating are dominant contributors to the total emissions. The provincial CO2 emissions from energy consumption increased gradually, reaching 327.61 million tons in 2019. Cities with strong industrial activities produced higher CO2 emissions. Moreover, the targeted region is a strong agriculture province, with the largest contribution to grain production in China. The absorption of farmland and forest was quantified, at 343.91 and 69.3 million tons in 2019, respectively. The total absorption was higher than the energy-related emissions. This indicated that the targeted region would provide a considerable carbon sink, attributed to the properties of its ecological system. From 2017 onwards, small boilers (single boilers smaller than 32 steam tons) were removed, and hence the emissions were lower than the original value. This study presents the characteristics of CO2 emissions, and reveals the co-benefit of air pollution control on CO2 reduction.

/pdf/emissions-and-absorption-of-co2-in-chinas-cold-regions-398pqom1.pdf

Emissions and Absorption of CO2 in China’s Cold Regions

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Effects of a diesel oxidation catalyst on gaseous pollutants and fine particles from an engine operating on diesel and biodiesel

Prediction of municipal solid waste generation and analysis of dominant variables in rapidly developing cities based on machine learning - a case study of China.

Emissions and Absorption of CO2 in China’s Cold Regions