ConTraEmSis: The Congested Traffic and Emission Index Impact Analysis Amid the Large-Scale Social Restrictions (LSSR) of COVID-19 in Several Cities of West Java, Indonesia

In some metropolitan cities of West Java Province, the urban movability affects to the congested traffic. This study analyzes the congested traffic during the large-scale social re-strictions (LSSR) of the coronavirus disease 2019 (COVID-19) around some metropolitan cities of West Java Province in May-June 2020. The national government of the Republic of Indonesia declared a national’s LSSR just for some the essential and critical activities are being acquiesced still enforce. Our proposed method, namely, ConTraEmSis is contributed to analyze the congested traffic two months from May-June 2020. We exploit the geomatic of the congested traffic in the COVID-19 information & coordination center West Java province (PIKOBAR) dataset for Bogor, Depok, and Bekasi (Bodebek areas), Bandung areas, and whole West Java province areas. We exploit the road transport and traffic management center (RTTM) and area traffic control system (ATCS) and index their data for the Bodebek and Bandung areas. The ConTraEmSis demonstrates that the congested traffic the LSSR of COVID-19 reduces around 18%-49% every month. Instead, the Java government always launch the many good governance policies to support the LSSR of the COVID-19 system. proposed model shows that after the LSSR in 2019 and 2020, is reduced between 3.27% and 5.27%. On the week-day afternoon, we scale down between 4.52% and 4.74%. On the weekend morning, we cut down between 1.3% to 1.5% before and after LSSR of 2019 and 2020, respectively. The congested traffic trends get 24% and 41% in the weekdays and weekends, respectively, since the LSSRs. Onto the weekend afternoon, we perform 13.4% and 14.8% for reducing the CO2 emission index during the LSSR’s 2020. We achieve the important congestion get an emission index lower than 0.3.

Prediction of CO Emission Index for Aviation Gas Turbine Combustor Using Flamelet Generated Manifold Combustion Model

Carbon monoxide (CO) has been identified as one of the regulated pollutants and gas turbine manufacturers target to reduce the CO emission from their gas turbine engines. CO forms primarily when carbonous fuels are not burnt completely, or products of combustion are quenched before completing the combustion. Numerical simulations are effective tools that allow a better understanding of the mechanisms of CO formation in gas turbine engines and are useful in evaluating the effect of different parameters like swirl, fuel atomization, mixing etc. on the overall CO emission for different engine conditions like idle, cruise, approach and take off. In this paper, a thorough assessment of flamelet generated manifold (FGM) combustion model is carried out to predict the qualitative variation and magnitude of CO emission index with the different configurations of a Honeywell test combustor operating with liquid fuel under idle condition, which is the more critical engine condition for CO emission. The different designs of the test combustor are configured in such a way that they yield different levels of CO and hence are ideal to test the accuracy of the combustion model. Large eddy simulation (LES) method is used for capturing the turbulence accurately along with the FGM combustion model that is computationally economical compared to the detailed/reduced chemistry modeling using finite rate combustion model. Liquid fuel spray breakup is modeled using stochastic secondary droplet (SSD) model. Four different configurations of the aviation gas turbine combustor are studied in this work referring to earlier work by Xu et al. [1]. It is shown that the FGM model can predict CO trends accurately. The other global parameters like exit temperature, NOx emissions, pattern factor also show reasonable agreement with the test data. The sensitivity of the CO prediction to the liquid fuel droplet breakup model parameters is also studied in this work. Although the trend of CO variation is captured for different values of breakup parameters, the absolute magnitude of CO emission index differs significantly with the change in the values of breakup parameters suggesting that the spray has a larger impact on the quantitative prediction of CO emission. An accurate prediction of CO trends at idle conditions using FGM model extends the applicability of FGM model to predict different engine operating conditions for different performance criteria accurately.

The Influence of Diesel–Ethanol Fuel Blends on Performance Parameters and Exhaust Emissions: Experimental Investigation and Multi-Objective Optimization of a Diesel Engine

Compression combustion engines are a source of air pollutants such as HC and Co, but are still widely used throughout the world. The use of renewable fuels such as ethanol, which is a low-carbon fuel, can reduce the emission of these harmful gases from the engine. A fundamental analysis is proposed in this research to experimentally examine the emission characteristics of diesel–ethanol fuel blends. Furthermore, a multi-objective genetic algorithm (e-MOGA) was developed based on the experimental data obtained to fine the most effective or Pareto set of engine emission and performance optimization solutions. So, the optimization problem had two inputs and seven objectives. For this purpose, input variables for the search space were S (rpm) varied in the range of (1600–2000) and E (%) varied in the range of (0–12). These design variables were chosen to be varied in a prespecified range with a lower and upper band as same as experimental conditions. A diesel engine using (DE2, DE4, DE6, DE8, DE10, and DE12) diesel–ethanol fuel blends, at the various speed of 1600 to 2000 rpm, was utilized for the experiment. The findings showed that the use of diesel–ethanol fuel blends decreased the concentration of CO and HC emissions by 3.2–30.6% and 7.01–16.25%, respectively, due to the high oxygen content of ethanol. As opposed to CO and HC emissions, the NOx concentration showed an increase of 7.5–19.6%. This increase was attributed to the high combustion quality in the combustion chamber, which resulted in a higher combustion chamber temperature. The optimization results confirmed that the shape of the Pareto front obtained from multi-objective ϵ-Pareto optimization could be convex, concave, or a combination of both. A new parameter was introduced as emission index or EI for selection of the best solution among the Pareto set of solutions. This parameter had a minimum value of 4.61. The variables levels for this optimum solution were as follows: engine speed = 1977 rpm, ethanol blend ratio = 10%, CO = 0.27%, CO2 = 6.81%, HC = 3 ppm, NOx = 1573 ppm, SFC = 239 g/kW·h, P = 56 kW, and T = 269.9 N·m. The EI index had a maximum value of 8.26. Conclusively, we can say that the optimization algorithm was successful in minimizing emission index for all ethanol blend ratios, especially at higher engine speeds.

Modeling CO2 Emissions from Trips using Urban Air Mobility and Emerging Automobile Technologies

Urban air mobility (UAM) operations provide the potential for more, or more attractive, trips in a metropolitan area relative to wholly surface-based transportation. But the emissions produced by a UAM mode must be studied in relation to these benefits. In this paper, an emissions model for the UAM context using electric vertical takeoff and landing (eVTOL) aircraft is developed that incorporates CO2 gases emitted from the electricity production required to charge the vehicle batteries. The model quantifies trip emissions using UAM for part or all of the trip and compares these with automobile-based trips. The estimations consider using gasoline and electric automobiles, with the impact of autonomy and average ground speeds in traffic. Trip case studies in the Chicago and Dallas metropolitan areas showcase the regional differences when using UAM and different automobile technology scenarios. In particular, differences stemming from how electricity generation from power grids (i.e., grid emission index) contributes to CO2 emissions of eVTOL trips and electric automobile trips in the Chicago and Dallas metropolitan areas are computed. This paper introduces trip properties called the surface-to-air distance ratio and the detour ratio to understand how they influence the CO2 emissions of a trip. Results from the simulation on identified trip cases in Chicago and Dallas illustrate the significant impact of the grid emission index of a region’s power plant on the emissions of electric vehicles.

Developing a comprehensive GIS tool to evaluate representative parameters regarding life comfort

In this paper, we present a tool dedicated to assessing life quality according to the notion of comfort which can link three aspects of noise, light, and air pollution with two aspects of thermal and odour discomfort because the beforementioned aspects are using different calculation methods of the parameters which are distinct and some of them are defined in the national or EU legislation. The authors developed a compressive database to evaluate representative quantities of energy loses. There were considered some performance indicators as: energy class, total specific energy consumption, CO2 equivalent emission index, the overall heat transfer coefficient of the building and characteristic temperatures, the corrected number of degrees days, and the duration of the heating season - at locality level.

On the issue of determining the main factors of gas hazard in coal mines of Ukraine

The main sources of methane emission are located in the undermined coal-bearing strata, which is not taken into account by the requirements of regulatory documents when determining the category hazard of coal mines. Gas emission from each undermined source is not equally dependent on the tons of coal mined. The relative gas emission changes during the cleaning work and cannot be a criterion for assessing the gas hazard of the entire mine. The volatility of the gas emission index per unit area of the underworked space, which was formed because of monthly movements of the working faces, was established. In essence, this indicator repeats the dependence of the relative gas content per ton of coal mined, since the area of the underworked space is functionally related to the amount of coal mined for a certain period. Without coal mining, the rate of movement of the working face is equal to zero, and gas emission from a unit area continues for several months. As a result, the considered indicators do not have their specific meaning and, due to their inconstancy, they cannot reliably reflect the gas hazard of mines.