NOx Values Research Articles

Pollution characteristics, sources, and photochemical roles of ambient carbonyl compounds in summer of Beijing, China

Ambient carbonyls are important precursors of radicals and ground-level ozone (O3). In this study, sources, precursors, and impacts on radicals and O3 of carbonyls were investigated based on online observations of volatile organic compounds (VOCs) at an urban site in Beijing during June 2021. Carbonyls accounted for 36% and 42% of mixing ratios and OH reactivity for total measured VOCs, respectively. Formaldehyde was the most abundant carbonyl, with the mean level of 4.13 ± 2.28 ppb. Source apportionment results based on the multi linear regression (MLR) method suggested that secondary production contributed 41%, 25%, 36%, and 30% of formaldehyde, acetaldehyde, propanal, and acetone, respectively. Key precursors of carbonyls were then identified based on the calculation of their production rates. It was found that alkenes contributed 59%–80% of aldehydes production. Impacts of carbonyls on HOx radicals (OH and HO2) and O3 production were explored using a box model based on observations (OBM). Photolysis of HONO, formaldehyde, and O3 were the dominant primary sources of HOx radicals during daytime of O3 pollution days, with average relative contributions of 52%, 28%, and 19% to the total primary production rate of HOx, respectively. Aldehydes accounted for 32% (20% from formaldehyde) of average HOx removal rates. The relative incremental reactivity (RIR) values of NOx determined by the OBM were negative, suggesting that the O3–VOCs-NOx sensitivity was in the VOCs-limited regime. Using the observed concentrations of carbonyls as constraints of OBM, the absolute values of RIR for NOx tended to increase but those for anthropogenic VOCs tended to decrease. Formaldehyde showed the largest RIR value for anthropogenic VOCs during O3 pollution days. These findings indicated the important impacts of carbonyls on O3 production and O3–VOCs-NOx sensitivity.

Optimization of common rail direct injection diesel engine performance with Melia dubia methyl ester peppermint oil blend using response surface methodology approach and investigation of hydrogen and hydroxy influence

In this study, an experimental investigation was carried out to evaluate the impact of compression ratio, exhaust gas recirculation, and the start of injection on the performance and emission of single-cylinder VCR CRDI engine fueled with Melia dubia biodiesel and peppermint oil blends. Response surface methodology (RSM) was used to evaluate the effects of these multiple factors and their interactions with response variables like brake thermal efficiency (BTE), carbon monoxide (CO), oxides of nitrogen (NOx), hydrocarbon (HC), and smoke. Model analysis was done to validate the regression model developed for all responses by using Analysis of variance (ANOVA). Compression ratios 17.5, 19.5, and 21.5, exhaust gas recirculation of 10, 15, and 20%, and 19, 21, and 23 °CA were selected for the start of injection in this study. High desirability of 0.979 was obtained at the optimum operating parameters, viz. 19.5 of compression ratio, 23 °CAbTDC of the start of injection with 15% EGR where the values of BTE, CO, HC, NOx, and smoke were found to be 30.66%, 2.66 g/kWh, 0.076 g/kWh, 7.36 g/kWh, and 40 HSU respectively. Further, hydrogen and hydroxy (simulated) gas were inducted to improve the biofuel blend's performance, and their influence was investigated. A significant improvement in performance and reduction in emissions were observed with the usage of hydrogen gases. Researchers and organizations seeking to enhance engine performance and reduce harmful environmental emissions can benefit from this study.

Optimization of port injection of n‐decanol in a PCCI engine using response surface methodology

AbstractThis work aims to define the optimum n‐decanol fraction in the inlet port and the corresponding engine load for the better emissions and performance characteristics of a partially premixed charged compression ignition (PCCI) engine by response surface methodology (RSM). The numerical model based on multi‐linear regression was established using experimental data. For this, the influence of various proportions of n‐decanol through intake port including 10%, 20%, 30%, and 40% were experimentally investigated besides the primary injection of neem oil biodiesel in the volumetric ratio of 80% diesel and 20% neem biodiesel, namely NB20. The optimization using RSM is exploited to capitalize the brake thermal efficiency (BTE) and diminish the emissions including oxides of nitrogen (NOx), carbon monoxide (CO) emission, smoke opacity, and hydrocarbon (HC) emission. The n‐decanol fraction in the port injection of 31.43% and the engine load in terms of brake power of 2.950 kW were found to be optimum parameters with the maximum desirability of 0.752. The optimal responses for brake‐specific fuel consumption (BSFC), BTE, CO, HC, smoke, and NOx under these operating conditions were found to be 0.305 kg/kWh, 28.8%, 0.145%, 19.61%, 54.85 ppm, and 837.7 ppm, respectively. Likewise, the correlation coefficient R2 values for BSFC, BTE, CO, HC, smoke and NOx have been found to be 99.85%, 99.95%, 93.58%, 90.32%, 99.97%, and 99.93%, respectively. According to the study's findings, the RSM is a realistic method for calculating and enhancing a diesel engine's emission and performance values operating in PCCI mode and using n‐decanol and NB20 as fuels.

Experimental Investigation of Acoustic Forcing on the Combustion Effect of Propane - Methane Mixtures

Today, the ever-increasing energy resource needs are of great importance for all countries in the global sense. Countries have recently been developing important policies to meet their energy needs and to use existing energy resources efficiently. In addition, in order to minimize the emissions that harm the nature as a result of the burning of energy sources, they have turned to alternative energy sources that are less harmful to the environment. In order to be an alternative energy source, in this study, the effect of enriching propane gas with methane gas on combustion in a Tubitak supported combustor was experimentally investigated. The enrichment of methane gas was determined at the rates of 10%, 20% and 30%, and the effects of acoustic stress on combustion, emission values and the effects on the flame were investigated. The thermal power was 7 kW and the equivalence ratio (Փ) was 1.2, and the experiment was carried out with a constant eddy value (1.0). When the experiment was carried out without acoustic stress, it was determined that the temperature, flame brightness and light intensity increased as the methane ratio increased, the dynamic pressure value almost did not change, the NOx value was negligibly small, and the CO value decreased depending on the oxygen amount as the methane ratio increased. In the experiments carried out under 90 Hz, 185 Hz and 330 Hz acoustic stress, as the forcing value increases, the temperature and flame brightness increase; It was observed that the NOx value was negligibly small, and the CO value decreased compared to the experiment performed without acoustic stress.

Numerical Investigation of a Reactivity-Controlled Compression Ignition Engine Fueled with N-Heptane and Iso-Octane

In this numerical study, the effects of the premixed ratio, intake manifold pressure and intake air temperature on a four-cylinder, four-stroke, direct injection, low-compression-ratio gasoline engine, operated in reactivity-controlled compression ignition (RCCI) combustion mode at a constant engine speed of 1000 rpm, were investigated using Converge CFD software. The results of numerical analyses showed that the maximum in-cylinder pressure and heat release rate (HRR) increased and the combustion phase advanced depending on the rise in both intake manifold pressure and intake air temperature. The CA50 shifted by 18.5 °CA with an increment in the intake air temperature from 60 °C to 100 °C. It was observed that the combustion duration dropped from 44 °CA to 38 °CA upon boosting the intake manifold pressure from 103 kPa to 140 kPa. Moreover, a delay in the combustion phase occurred at a constant intake air temperature with an increasing premixed ratio. The maximum value of in-cylinder pressure was recorded as 36.15 bar (at 11 °CA aTDC) with the use of PRF20. Additionally, as the content of iso-octane in the fuel mixture was increased, combustion delay occurred, and the maximum value of in-cylinder temperature obtained was 11 °CA aTDC using PRF20 fuel at the earliest point. While HC and CO emissions reached the highest values at a 60 °C intake air temperature, NOx and soot emission values were detected at quite low levels at this temperature. The values of all these emissions increased with rising intake manifold pressure and reached their highest values at 140 kPa. In addition, while the highest HC and CO emission values were observed with the use of PRF60 fuel, the results revealed that the control of the combustion phase in the RCCI strategy is notably affected by the premixed ratio, intake manifold pressure and intake air temperature.

Simulation of turbulent non-premixed combustion in pulverized coal from Kalimantan Indonesia

A computational simulation was created to investigate pollutants during coal combustion in a Drop Tube Furnace using Kalimantan coal. Previous research has explored Drop Tube Furnace combustion with Kalimantan coal, but lacked an understanding of combustion phenomena and pollutants, which are challenging to observe experimentally. This study utilized three samples of Kalimantan coal, namely RP, MB, and KC, acquired from various mining sources. This research is new study of simulation combustion coal in Drop Tube Furnace using non-premixed turbulent combustion and the Probability Density Function model with structured grid. The study reports on the temperatures and mass fractions of pollutants, including NOX, SO2, and CO2, along the centerline of the domain. The findings show that RP coal produced the highest combustion temperature, while KC coal produced the lowest. MB coal had the highest CO2 mass fraction, KC coal had the highest NOx value, and RP coal had the highest SO2 value.

Investigation of simultaneous effects of noise barriers on near-road noise and air pollutants

Noise barriers are one of the common solutions to control road traffic noise. Many studies have also shown that noise barriers cause reductions in near-road air pollutant concentrations. In this study, the simultaneous effects of a specific noise barrier application on near-road noise and air pollution at a specific location were investigated. In this context, air pollution, noise, and meteorological parameters were measured simultaneously at two points, road and receptor sides of a 50 m long, 4 m high glass fiber reinforced concrete noise barrier on a highway section. Results indicated that the noise barrier has an average 23 % reduction effect on the NOx concentration in addition to the noise level reduction at the receptor side. Besides, bi-weekly average passive sampler measurement results for BTEX pollutants indicate lower values at the receptor side of the barrier compared to the free field measurement results. In addition to real-time and passive sampler measurements, NOx and noise dispersions were modeled using RLINE and SoundPLAN 8.2 software, respectively. Comparisons of the measurement results with the model results indicated strong correlations. Model-calculated NOx and noise values under the free field conditions are highly compatible with a correlation coefficient (r) of 0.78. Although the noise barrier has a reduction effect on both parameters, it has been observed that their dispersion mechanisms are different. This study showed that noise barriers considerably affect the dispersion of road-sourced air pollutants at the receptor side. Further studies are needed to optimize noise barrier designs with different physical and material properties and application scenarios considering noise and air pollutants together.

Protective effects of long-term nitrate administration against ovariectomy-induced kidney dysfunction in rats.

Menopause is associated with higher risks of chronic kidney disease. We determined the effect of nitrate on ovariectomy-induced kidney dysfunction METHODS: Control, ovariectomized (OVX), control + nitrate, and OVX + nitrate female Wistar rats (n = 10/group); sodium nitrate (100mg/L) administered in drinking water for 9months. Glomerular filtration rate (GFR) and albumin excretion rate (AER) were calculated from serum and urine parameters. At month 9, serum and kidney levels of nitric oxide (NO) metabolites (NOx), oxidative stress indices, and mRNA expression of endothelial NO synthase (eNOS) were measured; with histological analyses of the kidney. Compared to controls, OVX rats had lower GFR (31%, p = 0.0079), higher glomerular tuft volume (30%, p = 0.0402), and Bowman's capsule space (39%, p = 0.0224). OVX rats had lower serum NOx (33%, p = 0.0061) and kidney eNOS mRNA expression (34%, p = 0.0368). Nitrate administration to: (i) control rats increased serum NOx (59%, p < 0.0001), with no effect on other parameters; (ii) OVX rats increased serum (85%, p < 0.0001) and kidney (106%, p = 0.0008) NOx values, and restored kidney eNOS expression to normal value. Nitrate administration to OVX rats increased GFR (36%, p = 0.0361) and restored glomerular tuft volume and Bowman's capsule space to normal values. In OVX rats, it also increased serum catalase (CAT) activity, serum and kidney total antioxidant capacity (TAC), and decreased serum malondialdehyde (MDA). Low-dose long-term nitrate administration protects against ovariectomy-induced kidney dysfunction in rats. This effect is associated with reducing ovariectomy-induced oxidative stress and restoring eNOS-derived NO deficiency in systemic circulation and the kidney.

Multi-Optimization of Injection Parameters Affecting Emissions in a Diesel Engine Fueled with Fischer-Tropsch Fuel Based on NSGA-II.

In this paper, an electronically controlled diesel engine fueled with Fischer-Tropsch fuel was selected to optimize soot and NOx emissions. First, the effects of injection parameters on exhaust performance and combustion properties were studied on an engine test bench and then a prediction model based on a support vector machine (SVM) was established according to the test results. On this basis, a decision analysis of soot and NOx solutions assigned with different weights was performed based on the TOPSIS analysis method. It turned out that the "trade-off" relation between soot and NOx emission was improved effectively. As a matter of fact, the Pareto front selected by this method showed a significant decline compared with the original operating points, in which soot declined by 3.7-7.1% and NOx declined by 1.2-2.6%. Finally, the experiments were used to confirm the validity of the results, which indicated that the Pareto front corresponded well with the test value. The maximum relative error between the soot Pareto front and the measured value is 8% while it is 5% for NOx emission, and the R2 values of soot and NOx under various conditions are more than 0.9. This instance proved that research on diesel engine emission optimization based on the SVM and NSGA-II is feasible and valid.

Effect of the hydrogen/kerosene blend on the combustion characteristics and pollutant emissions in a mini jet engine under CDC conditions

In this CFD study conducted with the geometry of a mini gas turbine engine using kerosene as fuel, colorless distributed combustion conditions were achieved by increasing the N2 ratio in the air. Then, H2 was added to the kerosene fuel in order to increase the combustion performance and the combustion chamber temperature distributions, NOx, CO, and CO2 values were examined. In the simulations using the simplified GTM-120 geometry, the combustion chamber outlet temperatures at 80 k, 100 k, and 120 k rpm were compared with the experimental results in the literature by changing the ratio of fuel and air for the validation study. Standard k-ε and Discrete Ordinates were chosen for turbulence and radiation models, respectively. In the study conducted with the non-premixed combustion model, simulations were made at O2 rates of 21%, 19%, 17%, and 15% for the formation of colorless distributed combustion conditions. For enrichment with hydrogen, H2 was added from 0% to 50% with 10% increments. HEF (Hydrogen energy fraction) has been used as the hydrogen addition rate. In light of the analyses made, it was seen that the colorless distributed combustion regime reduced the flame temperature from 2292 K to 1912 K and the NOx amount from 2.85 ppm to 0.0086 ppm. On the other hand, it is seen that this regime increased the CO emissions from 6.9 ppm to 38.67 ppm and the mole ratio of CO2 from 6.25% to 6.94%. It was observed that these findings prepared the ground for increasing the amount of hydrogen in the fuel, which increases the flame temperature and, accordingly, NOx emissions. By adding 50% H2 to kerosene under standard atmospheric conditions, the average NOx emission at the combustion chamber outlet increased from 2.85 ppm to 7.97 ppm, while the average CO emission decreased from 6.9 ppm to 1.08 ppm. As a matter of fact, by the addition of 50% H2 to the kerosene with air that contains 15% O2, which is the most extreme combustion situation in this study, the flame temperature decreased to 1912 K, and NOx rose to 0.0713 ppm. However, the CO emissions at the combustion chamber outlet decreased to 1.83 ppm and the CO2 ratio to 3.48%. Thus, with this study, it has become possible to use hydrogen as an alternative fuel in a real engine geometry by using CDC and hydrogen enrichment together, both in terms of pollutant emissions and combustion performance.

Experimental investigation of the performance and emission of low-speed diesel engine using various bio diesel blends at variable load conditions: (Part II)

The purpose of this study is to experimentally investigate the performance and emission of compression ignition engine using biodiesel extracted from waste cooking oils (WCO), such as (falafel frying oil; origin from palm oil , chicken frying oil; origin from soybean oil), and fresh oils such as (soybean oil, olive oil), after produce biodiesel from WCO and fresh oils, will be blending with pure diesel in two percentage are B20 ( 20% biodiesel from each type, 80% pure diesel), B10 (10% biodiesel from each type , 90% pure diesel). The biodiesel blends were used as an alternative fuel for diesel engine. After that, they were compared to pure diesel B00 (0% biodiesel, 100%pure diesel) at engine variable load from (0-6 kW) at constant speed of (2000 RPM). For engine performance, (Brake power, brake specific fuel consumption, brake thermal efficiency) were analyzed. Also, for emissions, (, exhaust gas temperatures to indicate NOx) were analyzed. The results showed that pure diesel produces higher brake force (BP) than all biodiesel blends. The highest value for BSFC is for B20-F (20% biodiesel from falafel frying oil, 80% pure diesel) is equal (0.243426 gm/kW.s). The highest value for brake thermal efficiency BTE is for B10-S (10% biodiesel from soybeans oil, 90% pure diesel) is equal 27.6%. The B10-S produces the highest value of NOx. In addition, pure diesel produces higher emissions than all biodiesel blends. All biodiesel blends produce higher emissions than pure diesel.

Maximization of bioethanol productivity from wheat straw, performance and emission analysis of diesel engine running with a triple fuel blend through response surface methodology

Due to its significant contribution to reducing pollution and crude oil use, bioethanol has been ranked as the most extensively used biofuel globally. Bioethanol was classified as a new and renewable source of fuel, which can be used as an oxygenated fuel blend for both of gasoline and diesel engines. In this work, the optimization process for bioethanol production and utilization has proceeded by Response Surface Methodology (RSM). Bioethanol production parameters such as temperature, pH, and their combined impact on bioethanol% and residual sugar have been studied. For process optimization, Box-Behnken design (BBD) based on response surface methodology (RSM) was used. For predicting bioethanol l% and residual sugar, a quadratic regression model was developed with coefficients of determination R2 of (0.9984) and (0.9883), respectively. The obtained results show that after 118.54 h, 9.33 W/V inoculum size, 31.66 °C, and 4.86 pH, bioethanol % increased to 3.5-fold to become16.92% and a minimum residual sugar concentration of 0.50 mg/ml are achieved. Also, bioethanol% and residual sugar was 16.92% and 0.50 mg/ml, respectively. However, the central composite design approach (CCD) has used to optimize the engine operating parameters were optimized to obtain the highest possible break thermal efficiency BTE% and lowest NOx emissions for a single-cylinder DI-engine running on a blend of 50% biodiesel/50% diesel combined with 10&20% bioethanol. Also, the analysis of variance was revealed by the examination of inconsistency were statistically significant. According to RSM optimizer data, the optimum NOx and BTE values were 83.72 ppm and 23.68%, respectively, at the highest concentration of bioethanol blend of 14.65% and break power of 3.21 kW.

Estimation of NOx pollutants in a spark engine fueled by mixed methane and hydrogen using neural networks and genetic algorithm

Nowadays, due to stricter pollution standards, more attention has been focused on pollutants emitted from cars. As a very dangerous pollutant, NOx has always triggered the sensitivity of the related organizations. In the process of developing and designing the engine, estimating the amount of this pollutant is of great importance to reduce future expenses. Calculating the amount of this pollutant has usually been complicated and prone to error. In the present paper, neural networks have been used to find the coefficients of correcting NOx calculation. The Zeldovich method calculated the value of NOx with 20% error. By applying the progressive neural network and correcting the equation coefficient, this value decreased. The related model has been validated with other fuel equivalence ratios. The neural network model has fitted the experimental points with a convergence ratio of 0.99 and a squared error of 0.0019. Finally, the value of NOx anticipated by the neural network has been calculated and validated according to empirical data by applying maximum genetic algorithm. The maximum point for the fuel composed of 20% hydrogen and 80% methane occurred in the equivalence ratio of 0.9; and the maximum point for the fuel composed of 40% hydrogen occurred in equivalence ratio of 0.92. The consistency of the model findings with the empirical data shows the potential of the neural network in anticipating the amount of NOx.

Optimized fluegas denitrification control strategy to enhance SCR performance during load-cycling transient processes in coal-fired power plants

Selective catalytic reduction (SCR) is a common method for controlling NOx emission via NH3 injection. Coal-fired power plants are taking load-cycling processes with increasing frequency. During load-cycling processes, NOx emissions fluctuate and NH3 escape aggravates, which increases environmental pollution and degrades equipment safety. Therefore, the NH3 injection control strategy must be optimized to enhance denitrification performance during transient processes. In this study, an integrated NOx emission model of coal-fired units is developed and verified. The model includes the thermal system simulation, NOx production, and SCR system models. On the basis of the model, load-cycling processes are simulated under the traditional denitrification control strategy, wherein excessive NH3 injection and increased NOx and NH3 emissions are observed. The typical transient processes of the SCR system and boiler are simulated with various initial operating conditions and input parameter disturbances to explore the main factors affecting denitrification performance during load-cycling processes. The analysis of dynamic characteristics reveals that the inertia of NH3 storage is an important factor of unstable denitrification performance, and the temperature and fluegas flow rate influence the delay caused by this inertia, therefore the denitrification performance shows significant difference in various load-cycling processes. Consequently, an optimized NH3 control strategy is proposed. In this strategy, the change rate of NOx concentration is predicted according to the boiler load command, and the fluegas temperature and flow rate are also taken to adjust the additional NH3 injection. The simulation of typical load-cycling processes demonstrates that the optimized control strategy comprehensively enhances denitrification performance, where the NH3 injection, NOx emission and NH3 emission are all reduced. In particular, for the low- and medium-load range, the total amount of NH3 emission can be reduced by 5.69%, and the maximum values of NOx and NH3 emissions are reduced by 7.46% and 19.26%, respectively, which benefits both air pollutants emission reduction and equipment safety.

Optimization of biodiesel/2-propanol/1-hexanol blends based on diesel engine performance using combined mixture-process design (CMPD)

The combined mixture and process design (CMPD)-based optimization tool showed precise prediction and optimized results when there were two or more mixture combinations and one or more process factors investigated. Therefore, in this study, the CMPD method was employed to optimize the mixture components of premixed 20% mango seed methyl ester mixed with 80% diesel (MB20); 2-propanol and 1-hexanol components were optimized with process factor of variable loads. The process factor load was varied from 0 to 100% at 25% intervals, whereas the amount of alcohol was not permitted to exceed 15% by volume in each case. The designed CMPD model optimized the emission parameters such as CO, CO2, O2, HC and NOx to their minimum levels to produce maximum brake thermal efficiency (BTE) from the test engine. The developed optimization model achieved a maximum regression value (R2) of 0.9826 for BTE while CO attained the lowest value (i.e. 0.9254 R2). However, the model optimized BTE, BSFC, CO, CO2, O2, NOx and HC values as 24.31%, 0.452 kg/kw.h, 0.133%, 3.397%, 15.896%, 283.268 ppm and 17.879 ppm, respectively, with the desirability of 0.884. This suggests the optimum fuel combination is 80% MB20, 5% 2-propanol, and 15% 1-hexanol with a 76.086% load.

The impact of turbulence and combustion models on flames and emissions in a low swirl burner

Since natural gas fuel boilers are environmentally friendly and efficient, they are widely used in heating systems today. Improvements are continuing in the combustion efficiency and emissions of these boilers. Due to the high costs and long manufacturing times, experimental studies are progressing slowly. For this reason, studies with CFD simulations are also preferred. For realistic CFD results, it is important to correctly choose the turbulence and combustion models. This study conducted an experimental study to obtain temperature and emission measurements from a low-swirl natural gas boiler. Then, CFD simulations were made under the same conditions using the 3D model prepared for the same boiler. In simulation studies, different turbulence and combustion models were investigated. The turbulence models used in the simulations are Standard k-ε, Realizable k-ε, RNG k-ε, and Reynolds Stress Model (RSM), respectively. Combustion models are Eddy Dissipation (ED), Finite Rate/Eddy Dissipation (FR/ED), Eddy Dissipation Concept (EDC), Non-Premix Combustion (NPC) and Partial-Premix Combustion (PPC). When the results obtained by numerical simulations are compared with the experimental data, it is understood that the Realizable k-ε turbulence model provides better convergence than other turbulence models, while PPC and ED provide better convergence in combustion models. Since the two-step chemical mechanism for natural gas used in EDC and FR/ED models neglects the formation of many intermediate products, higher NOx values were obtained than the experimental for these combustion models. Different results were obtained from the standard k − ε in terms of temperature and CO2, H2O, O2, CO, NOx results than other turbulence models.

Long-term atmospheric pollutant emissions from a combined cycle gas turbine: Trend monitoring and prediction applying machine learning

Carbon monoxide (CO) and oxides of nitrogen (NOx) are noxious pollutants associated with combined cycle gas turbine (CCGT) power plants that require careful monitoring and control. A publicly available dataset links five years of hourly CCGT emissions to nine recorded operational/environmental variables. This study applies twelve multi-linear regression (MLR) and machine learning (ML) models to rigorously predict CO and NOx for that dataset with a novel analytical sequence. Statistical distributions of the data reveal time shifts in the CO and NOx values that cannot be explained by the recorded variables. The relative variable weights applied to the variables by the certain MLR/ML models identifies that their relative importance in influencing CO and NOx predictions varies substantially. Multi-K-fold cross validation is applied to establish the prediction accuracy of each model and indicate the most suitable data-record splits for training and validation. Trained K-nearest neighbour (KNN) and extreme gradient boosting (XGB) ML models consistently provide the most reliable CO and NOx emission predictions with least errors when applied to unseen test data. Consideration of mean errors and predicted versus measured data trends make it possible to identify and partially correct MLR/ML predictions for systematic time shifts in the CO and NOx data. The best performing KNN models generate mean average errors of 0.8458 mg/m3 for CO (∼1.9 % of the CO data range) and 5.1234 mg/m3 for NOx (∼5.5 % of the NOx data range) for a two year period separate from the model’s training/validation period.

Impact on air quality from increasing cruise ship activity in Copenhagen port

The impact of the growing cruise ship industry on air quality levels was investigated at the port of Copenhagen, Denmark. In 2018, 345 cruise ships visited Copenhagen, emitting 291 tons of NOx near the city centre. A spatiotemporal cruise ship emission inventory was developed for 2018 based on port list information, engine data, main and auxiliary engine power functions, and NOx emission factors, and was implemented in the OML-Multi atmospheric dispersion model. Evident plume effects from the cruise ships, which were traced by introducing the concept of likely concentration contribution, were obtained in the modelled and measured concentrations at Langelinie Quay, which is the busiest cruise ship terminal in Copenhagen port. Hourly peak values of NOx well above 200 μg m−3 were obtained at the top of a residential building at Langelinie Quay. The emissions from cruise ships were increasing the annual concentration of NO2 in the port area by up to 31% at ground level, and 86% 50 m above the ground in comparison to the urban background level. No exceedance of the European annual limit value of NO2 was obtained. The short-term impact of cruise ships was more pronounced with local exceedances of the hourly European limit value for NO2. Increasing cruise ship activity in Copenhagen port leads to air quality deterioration on short time scales with implications for human health.

Understanding the performance, emissions, and combustion behaviors of a DI diesel engine using alcohol/hemp seed oil biodiesel/diesel fuel ternary blends: Influence of long-chain alcohol type and concentration

In this study, it was aimed to examine the influences of biodiesel–diesel-higher alcohol (1-pentanol, 1-hexanol, and 1-heptanol) blends on the performance, emission and combustion behaviors of a single-cylinder diesel engine. The tests were performed at a fixed speed of 1500 rpm and variable loads (25%, 50%, 75%, and 100%). For the tests, 80% diesel and 20% hemp seed oil biodiesel were blended and called as B20. Biodiesel fuel was produced by transesterification from hemp seed oil in the presence of methanol and potassium hydroxide for the preparation of B20 binary test fuel and other ternary fuels. Furthermore, nine ternary blend fuels [20% HSOB + 70%, 60% and 50% diesel, respectively + 10%, 20% and 30% higher alcohol (pentanol, hexanol and heptanol) respectively] were prepared. The calculations made with the experimental data revealed that the minimum brake specific energy consumption values were 12,48 MJ/kW h, 13,06 MJ/kW h, 13,27 MJ/kW h, 13,35 MJ/kW h, 13,47 MJ/kW h, and 13,59 MJ/kW h, respectively, for diesel fuel at full load, for fuels B20, B20Hx10, B20Hp10, B20Hx20 and B20Pe10, the maximum brake thermal efficiency values were obtained as 28.85%, 27.56%, 27.14%, 26.97%, 26.73% and 26.49%, respectively, for the same fuels at the same load. The increment in higher alcohol concentration in the blend delayed start of combustion and therefore the ignition delay period was prolonged. In the fuel line pressure data, changes were observed depending on the amount, viscosity and density of the fuel. Furthermore, B20Hx10 and B20Hp10 fuels gave the maximum in-cylinder pressure, heat release rate, average gas temperature and pressure rise rate values after diesel and biodiesel. The addition of biodiesel and higher alcohol to diesel fuel resulted in a decrease in NOX, CO and unburned HC and smoke emissions and an increase in CO2. NOX, CO and unburned HC values of higher alcohol blended fuels at full load showed lower results, between 3.04–22.24%, 22.85–56.35% and 5.44–22.83%, respectively, compared to diesel fuel. It can be concluded that the use of hemp seed oil biodiesel and higher alcohol in the diesel engine will make a significant contribution to the reduction of NOX emissions.

The Investigation of Bioethanol as a Fuel in an SI Engine with Fuel and Ignition Systems Converted to Electronic Control

In this study; a four-stroke, air-cooled, spark-ignition engine was used. It’s aimed to improve the performance and emissions by renewing the existing ignition and fuel system of the engine in a way that can be controlled via computer. Classical ignition system was modified with an electronic ignition system and a computer-controlled system was established by using an injector instead of the carburetor. Gasoline and bioethanol fuels were compared with the original and updated version of the engine by conducting various experiments. In these experiments, engine power and torque, specific fuel consumption, thermal efficiency, exhaust emissions and combustion analysis results were examined. When the results obtained are evaluated; with the use of electronically controlled fuel and ignition system in engine torque and power, an increase of 11.58% in maximum torque obtained from gasoline and an increase of 14.4% in average power was observed compared to the standard system. Specific fuel consumption decreased by 18.32% for gasoline and 26.95% for bioethanol at full load. At full load, thermal efficiency was 22.43% for gasoline, 36.9% for bioeth-anol and in-cylinder max. pressure was a 4% increase for gasoline and an 8% in-crease for bioethanol. In the emission values, at full load, the CO value decreased by 6.2% for gasoline, 20% for bioethanol and HC value decreased by 3.8% for gasoline and 7.5% for bioethanol. CO2, NOx and O2 values increased by 4.1%, 14.9%, 0.7% for gasoline and 0.7%, 5.6%, 0.4% for bioethanol.