A laboratory approach to CO2 and CO emission factors from underground coal fires

Estimating direct CO2 and CO emission factors for industrial rare earth metal electrolysis

Correct emission factors are necessary for evaluating vehicle emissions and making proper decisions to manage air pollution in the transportation sector. In this study, using a chassis dynamometer at the Automotive Emission Laboratory, CO2 and CH4 emission factors of light-duty vehicles (LDVs) were developed by fuel types and driving speeds. The Bangkok driving cycle was used for the vehicle’s running and controlling under the standard procedure. Results present that the highest average CO2 and CH4 emission factors were emitted from LDG vehicles, at 232.25 g/km and 9.50 mg/km, respectively. The average CO2 emission factor of the LDD vehicles was higher than that of the LDG vehicles, at 182.53 g/km and 171.01 g/km, respectively. Nevertheless, the average CH4 emission factors of the LDD vehicles were lower than those of the LDG vehicles, at 2.21 mg/km and 3.02 mg/km, respectively. The result reveals that the lower driving speed emitted higher CO2 emission factors for LDVs. It reflects the higher fuel consumption rate (L/100 km) and the lower fuel economy rate (km/L). Moreover, the portion of CO2 emissions emitted from LDVs was 99.96% of total GHG emissions. The CO2 and CH4 emission factors developed through this study will be used to support the greenhouse gas reduction policies, especially concerning the CO2 and CH4 emitted from vehicles. Furthermore, it can be used as a database that encourages Thailand’s green transportation management system.

Peatfire in Indonesia recently had become an important issue regarding its global warming impact of green house gases emitted. Emission factor is one of important variables to determine total emission of carbon released by peatfire. But currently there were only a few studies about Indonesian peat fire emission factors. The previous studies of Indonesian peat fire emission factor reported the results from a very limited number of samples and during smoldering combustion stages only. Therefore this study attempts to quantify carbon dioxide (CO2) and methane (CH4) emission factors from laboratory peat combustion based on higher number of samples and taken both of combustion stages (flaming and smoldering) into consideration. Peats were sampled from five different districts in Pontianak, West Kalimantan. Ultimate analysis showed that pure peat composed of relatively high carbon content (52.85 – 59.43% dry basis). Laboratory experiments were carried out by burning small amout of peats in a mini furnace and measuring their CO2 and CH4 emission concentration during flaming and smoldering. CO2, CO and CH4 average emission factors and their related average MCE for flaming were found to be 2,088 ± 21 g/kg (n = 17), 3.104 ± 7.173 g/kg (n = 17), 0.143 ± 0.132 g/kg (n = 17) and 0.998 ± 0.005 (n = 17), respectively, while for smoldering were 1,831 ± 131 g/kg (n = 17), 138 ± 72 g/kg (n = 17), 17 ± 12 g/kg (n = 17) and 0.894 ± 0.055 g/kg (n = 17), respectively. This emission factors based on the laboratory combustion experiment can be conveniently used to estimate CO2 and CH4 emission from Indonesian peat fire. Equation models to correlate between MCE and emission factors for both flaming and smoldering were developed. MCE and CO2 emission factor during flaming was relatively higher than smoldering. On the contrary, CO and CH4 emission factors were relatively smaller during flaming than smoldering.

CO emissions in China: Uncertainties and implications of improved energy efficiency and emission control

Study on the real-world emissions of rural vehicles on different road types.

Integrated effects of SCR, velocity, and Air-fuel Ratio on gaseous pollutants and CO2 emissions from China V and VI heavy-duty diesel vehicles

Purpose. Development and verification of a method for calculating and forecasting CO2 emissions from coal combustion at thermal power plants based on proximate analysis data. Calculation of gross and specific CO2 emissions per unit of output energy and mass of coal consumed at Ukrainian thermal power plants (TPPs). Methodology. Methods of mathematical statistics were used for processing the data of ultimate and proximate analysis of 170samples of A, L, G, and LFG coal ranks with low heat value on operating state in the range of 17.2 to 31.0 MJ/kg and ash content on dry state (Ad) in the range of 3.8 to 38.0% to determine relationships between carbon emission factors (kc), calorific value, and ash content. Findings. The values of emission factors and gross CO2 emissions for mixtures of coals of grades A and L, G and LFG at Ukrainian TPPs in 20172021 were calculated. For 2021, the average value of for coals of grades G and LFG was 94,128 g/GJ, and for coals of grades A and L it was 104,987 g/GJ. Gross CO2 emissions at Ukrainian TPPs have been in the range of 3849million tons in recent years, and their annual reduction is due to a decrease in energy production and fuel consumption at TPPs, primarily of grades A and L. Originality. Empirical dependencies kc for steam coal of different ranks are determined in the form of The coefficients a, b, and c are determined for grades A, L, G, and LFG and their mixtures. The relationship between the carbon content in coal and the low heat value for coal is linear: where K is a coefficient depending on the coal grade. The values of K are determined for coal of grades A, L, G, and LFG. Practical value. Verification of the created method shows that the calculation error is less than 1.0%. This is in line with the requirements of the Monitoring Procedure and Directive 2003/87/EC. In 2021, the specific CO2 emission per unit of output energy at TPPs in Ukraine was 1,084 g/kWh for all ranks of steam coal. The values of specific CO2 emissions per unit mass of consumed coal were 1.94 t/t for coals of all grades, 1.91 t/t for grades G and LFG, and 2.21 t/t for grades A and L. The official annual reports of the Ministry of Energy of Ukraine contain information on the amount of produced electricity, consumed coal, and forecast balances of electricity production at TPPs, therefore, the values of specific emissions established by us are convenient to use for estimating and forecasting carbon dioxide emissions.

To provide a corresponding preparation and foundation for the implementation and testing of China 6, as well as provide a strong reference for the formulation of China automotive test cycle (CATC) in the future, portable emission measurement system (PEMS) was applied to carry out CO and NOx emissions test on conventional roads for a light-duty gasoline vehicle (Toyota Levin) and a heavy-duty diesel vehicle (KING LONG bus) in Nanjing. The results showed that the CO emission rate of the Toyota car was mainly determined by the speed. As the vehicle speed increased, the CO emission rate increased rapidly while it was below 0.035 g/s. The CO emission rate of KING LONG bus accelerated with the increase of the vehicle speed at the lower speed and began to decrease when the speed reached 60 km/h. In terms of NOx emission rate, as the vehicle speed increased, the NOx emission rates of both vehicles increased. The CO and NOx emission factors of the two models showed similar patterns, both of which decreased significantly as the vehicle speed increased. Compared with the corresponding emission limits, the CO emission of both vehicles was higher, especially for light vehicle, and it was more than 3 times the limit. The NOx emission of both vehicles met the corresponding emission standards. The CO and NOx emission rates of light vehicles were positively correlated with specific power of vehicle (VSP). When VSP was less than 16, the two pollutants emission rate variation with VSP of heavy vehicle showed the same trend, while it was different when VSP was more than 16.

Intensive carbon dioxide emission of coal chemical industry in China

Evaluation of the carbon dioxide (CO2) emission factor from lime applied in temperate upland soil

The COVID-19 epidemic and the Russian–Ukrainian conflict have led to a global food and energy crisis, making the world aware of the importance of agroforestry development for a country. Modern agriculture mechanization leads to massive energy consumption and increased CO2 emissions. At the same time, China is facing serious demographic problems and a lack of consumption in the domestic market. The Chinese government is faced with the dilemma of balancing environmental protection with economic development in the context of the “double carbon” strategy. This article uses annual World Bank statistics from 1990 to 2020 to study the asymmetric relationships between agroforestry development, energy consumption, population size, and economic development on CO2 emissions in China using the partial least squares path model (PLS-PM), the autoregressive VAR vector time series model, and the Granger causality test. The results are as follows: (1) The relationship between economic development and carbon dioxide emissions, agroforestry development and carbon dioxide emissions, energy consumption and carbon dioxide emissions, and population size and carbon dioxide emissions are both direct and indirect, with an overall significant positive effect. There is a direct negative relationship between population size and carbon dioxide emissions. (2) The results of the Granger causality test show that economic development, energy consumption, and CO2 emissions are the causes of the development of agroforestry; economic development, agroforestry development, population size, and CO2 emissions are the causes of energy consumption; energy consumption is the cause of economic development and CO2 emissions; and agroforestry development is the cause of population size and energy consumption. (3) In the next three years, China’s agroforestry development will be influenced by the impulse response of economic development, energy consumption, and CO2 emission factors, showing a decreasing development trend. China’s energy consumption will be influenced by the impulse response of economic development, agroforestry development, population size, and CO2 emission factors, showing a decreasing development trend, followed by an increasing development trend. China’s CO2 emission will be influenced by the impulse response of energy consumption and agroforestry development. China’s CO2 emissions will be influenced by the impulse response of energy consumption and agroforestry development factors, showing a downward and then an upward development trend.

Mercury emissions from dynamic monitoring holes of underground coal fires in the Wuda Coalfield, Inner Mongolia, China

Evaluating the emission status of light-duty gasoline vehicles and motorcycles in Macao with real-world remote sensing measurement

On-board measurement of emissions from freight trucks in urban arterials: Effect of operating conditions, emission standards, and truck size

The evaluation of coal loss caused by underground coal fire is the principal basis for the decision-making of underground coal fire extinguishing and utilization. However, the existing coal fire risk assessment method is complex, time-consuming, laborious and inaccurate, and it is difficult to meet the requirements of coal mine underground fire control and utilization. Thus, this paper systematically investigates the relationship between coal loss and the underground combustion space area of coal fires, and the synergetic relationship between combustion space area of coal fires and surface subsidence：1. The coal loss caused by underground coal fire is related to the combustion space area of coal fires. When the different types of coal spontaneous combustion form the same size fuel-burning area, the coal loss is different. The loss of coal can be calculated by the size of the combustion space area of coal fires. 2. The random medium theory, surface subsidence rule of main section and the geometric method were used to determine they synergistic relationship between the combustion space area of coal fires and the surface subsidence. Different methods have their own advantages and disadvantages and applicable scope. Then, the monitoring method of surface subsidence caused by underground coal fire was analyzed, new methods to determine the position of underground combustion space area and to evaluate coal loss caused by coal fire were proposed. The results have important theoretical and practical significance for the determination of underground hidden coal fire location and the management and utilization of underground coal fires.