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The conversion of plastic solid waste and waste cooking oil into useful alternative fuels, e.g., waste plastic fuel and biodiesel, respectively, helps mitigate waste accumulation and minimize the dependence on fossil fuels, like ultra-low sulfur diesel (aka diesel). This study aims to assess the potential environmental impacts of both waste-derived fuels with the help of a scalable Well-to-Exhaust life-cycle analysis (functional unit = 1 kg of fuel) conducted within a university campus (control volume) with well-defined boundaries. The performance of both fuels is assessed on a Well-to-Pump (fuel fabrication) and Pump-to-Exhaust (end-use) basis, and their summation is used to present the life cycle impact of each fuel comparative to diesel. The findings reveal that diesel worsens the local air quality and significantly contributes to global warming. In contrast, waste plastic fuel appears to have a relatively lower impact on the air quality index and global warming, suggesting that its production near urban areas could help mitigate plastic waste accumulation and environmental pollution while boosting the local economy. On the other hand, biodiesel emerges as a relatively cleaner fuel and shows significantly lower emissions, especially during its fabrication. Therefore, its manufacture and end-use can be decoupled to enhance the economics of the process. Finally, its lowest overall carbon dioxide emissions hint that its use could be instrumental in lowering greenhouse gas emissions.

Microplastics are a silent threat that represent a high degree of danger to the environment in its different ecosystems and of course will also have an important impact on the health of living organisms. It is evident the need to have effective treatments for their treatment, however this is not a simple task, this as a result of the behavior of microplastics in wastewater treatment plants due to their different types and nature, their long molecular chain, reactivity against water, size, shape and the functional groups they carry. Wastewater treatment plants are at the circumference of the release of these wastes into the environment. They often act as a source of many contaminations, which makes this problem more complex. Challenges such as detection in the current scenario using the latest analytical techniques impede the correct understanding of the problem. Due to microplastics, treatment plants have operational and process stability problems. This review paper will present the in-depth situation of occurrence of microplastics, their detection, conventional and advanced treatment methods as well as implementation of legislations worldwide in a comprehensive manner. It has been observed that no innovative or new technologies have emerged to treat microplastics. Therefore, in this article, technologies targeting wastewater treatment plants are critically analyzed. This will help to understand their fate, but also to develop state-of-the-art technologies or combinations of them for the selective treatment of microplastics. The pros and cons of the treatment methods adopted and the knowledge gaps in legislation regarding their implementation are also comprehensively analyzed. This critical work will offer the development of new strategies to restrict microplastics.

Colchicum luteum is currently a rare and threatened medicinal plant species in the Kashmir Himalaya. Due to the subsequent increase in anthropogenic pressure on medicinal plant species, it is imperative to understand the phytosociological and conservational status of the plant in its natural habitat. The objectives of this study were analysed in year 2018-2019 on the phytosociological data, viz. density, frequency, and abundance, as well as the rhizospheric soil microbial diversity of C. luteum in disturbed and undisturbed areas of the Kashmir Himalaya. We examined the distribution pattern, phytosociological data, and conservation status of C. luteum by analysing ecological features like abundance, frequency, and density in all three selected locations in Kashmir, Northern India and were found maximum values at Undisturbed areas. The highest values of density (3.24 ± 0.69 m

Hospital wastewater is harmful to the environment and human health due to its complex chemical composition and high potency towards becoming a source of disease outbreaks. Due to these complexities, its treatment is neither efficient nor cost-effective. It is a challenging issue that requires immediate attention. This effort focuses on the treatment of hospital wastewater (HWW) by removing two selected drugs, namely ibuprofen (IBU) and ofloxacin (OFX) using individual biological treatment methods, such as moving bed biofilm reactors (MBBR) and physicochemical treatment, such as ozonation and peroxane process. The both methods are compared to find the best method overall based on effectiveness and removal efficiency. The optimal removal for ozone dosing range was nitrate (9.00% and 62.00%), biological oxygen demand (BOD) (92.00% and 64.00%), and chemical oxygen demand (COD) (96.00% and 92.00%) that required at least 10 min to reach considerable degradation. The MBBR process assured a better performance for ibuprofen removal, overall. The IBU and OFX removal was found to be 14.32-96.00% at a higher COD value and 11.33-94.00% at a lower COD value due to its biodegradation. This work strives to pave the way forward to build an HWW treatment technology using integrated MBBR processes for better efficiency and cost-effectiveness.

Bioenergy has obvious advantages over conventional fossil fuels owing to its renewability and huge capacity, which has dominating role in shielding the energy security that can be a favourable alternative to the disruption of food, resources and the atmosphere. In order to maintain their immediate energy levels and restore the atmosphere, coal-based countries need alternative fuels. For example, wonder inclusion to renewable energy are biofuels derived from crop residues devoid of sacrificing on food production. Annually, about 65 million tonnes (or 280 million metric tonnes) of energy crop-based ethanol are generated, which itself is equal to China's present gasoline ethanol output (2 million tonnes per year). The adverse effects of bioenergy production can vary highly depending on biological sources, land locations and management practices. Replacing fossil fuels with biofuels can significantly reduce these harmful effects arising from various fossil fuels. Identifying crop growing areas, appropriate bioenergy cultivars and appropriate management practices will contribute to the rig environment and biochemical sustainable development. Improved farm management and landscape planning are valuable for ecological services. This paper discusses several biofuels induced patterns of land managements, and generations of biofuel resources practices, cultivation of bioenergy crops environmental implications, and prospective techniques for establishing ecologically friendly biomass energy programmes.

Predictive combustion models assess engine performance for given setpoints by determining the rate of heat release that is governed by the fuel mass burned. Often, simple mathematical functions such as the Wiebe function are used in simulations to provide mass fraction burned values at each integrated step. Despite its popularity, a limitation of the Wiebe function is that it generally does not take operating conditions into account. Therefore, there is a need for an adaptive Wiebe function that can be scaled for a given fuel and run-time conditions. Here, this is accomplished for methane-air combustion in a spark-ignition (SI) engine. A linear regression analysis was used to fit the adaptive Wiebe model to experimental data with an average R2 value of 0.965. The scaling process was expanded to include oxy-methane combustion for specialized SI applications, e.g., for stationary or mobile power generation in environments such as Mars. This was accomplished through an analysis of the laminar and turbulent flame speeds that dominate the combustion process and the charge burnup time. The results show that a relative increase in the turbulent flame speeds during oxy-methane combustion shrinks the combustion duration between 10% and 90% mass fraction burned by approximately 87% relative to air. Comparing these results with literature reveals that the scaled Wiebe function follows theory closely and is a reasonable tool for burnt mass and combustion duration predictions.

Current unmanned aerial vehicle (UAV) propulsion technologies includes hydrogen fuel cells, battery systems, and internal combustion engines (ICE). However, relying on a single propulsion technology might result in a limited operational range. This can be mitigated by utilizing a hybrid configuration involving a battery pack and an ICE or a fuel cell for charging. Due to its significant weight advantage and high mass-specific energy content, hydrogen (H2) is an ideal fuel for both power plant options. However, use of H2 with an ICE requires precise operational control through combustion process simulation with the predictive approximation of the mass fraction burned profile. In this area, the relatively simple single-Wiebe function is widely deployed for a variety of different fuels, as well as combustion regimes. In general, the description of the single-Wiebe function includes the extent of complete combustion (a), magnitude of the maximum burn rate (m), and combustion duration (θd). However, the literature often provides values for these parameters without necessarily relating them to operational characteristics that can influence ICE power. As a result, it is critical to correlate the burn rate of the fuel to ICE operating parameters, such as the engine compression ratio, inlet pressure, mean piston speed, exhaust gas recirculation level, equivalence ratio, and spark timing. Therefore, in an attempt to physically define these parameters, this effort performs a sensitivity analysis using linear regression (least squares method) to assess the impact of engine operating conditions on the Wiebe function in comparison to experimental data for port-fuel injected hydrogen ICEs. The result is a model that can estimate the values of a, m, and θd in combination with a relatively high coefficient of determination (R2) when compared to the experimental mass fraction burned profiles. Finally, others can expand this methodology to any experimental data for engine and fuel-specific Wiebe parameter determination.

Increased black-box software use without adequate software literacy can lead to improper results and potentially disastrous consequences. Furthermore, such software is often expensive and comes with limited flexibility making it prohibitive for learning purposes. Therefore, this effort highlights the development of an adaptable, user customizable, and free open-source software tool to evaluate reaction kinetics in combustion models. Here, the software undergoes verification and validation to ensure proper operation over the intended domain of its application. The conceptual model is derived from the basic governing equations of thermodynamics simulating zero-dimensional constant pressure combustion with chemical kinetics based on a homogeneous hydrogen-oxygen reaction mechanism. Then, the computerized model is developed using a top-down programming technique for quick identification and elimination of coding errors. Operational validation occurs by comparing results with Chemkin and Cantera that reveals absolute and relative tolerances of 1E−12 and 1E−3, respectively, are sufficient for convergence at all specified initial conditions. In addition, the open-source software is computationally less intensive with average time savings of 33.69% and 48.88% versus Chemkin and Cantera, respectively. Subsequently, model results are time-shifted to the 50% fuel-burned mark and compared with experimental results for validation. This ensures that the created software is correct and useful for classroom instruction. Finally, the customizability of the open-source software instills confidence in students to develop custom chemical reaction mechanisms.

The relatively low energy density of lithium ion (Li-ion) batteries that power small Unmanned Aerial Vehicles (UAVs) limits their operating range. The use of hydrogen can provide a significant range improvement given its magnitude increase in mass and volume specific energy over Li-ion batteries. As a result, this effort investigates the potential of hydrogen-fueled power plants for small UAVs. Here, five powertrain options are simulated, namely Li-ion battery (LiNiCoAlO2 and Li-air), internal combustion engine (ICE) with integrated generator, parallel hybrid ICE, free piston engine (FPE) with integrated linear generator, and proton exchange membrane fuel cell (PEMFC). The three major outcomes of this study include: (1) Though the performance characteristics of an ICE are superior to a FPE, the ICE has a relatively high manufacturing cost due to a more complex architecture, whereas a FPE can directly convert thermal energy to electricity; (2) PEMFCs can be readily integrated into an UAV since they provide electric power directly without a convoluted energy conversion system, reducing the overall weight of an UAV; and (3) Theoretically, the use of a Li-air battery pack would result in a longest flight time and simplest configuration; however, the necessary chemistry is still years away from practical implementation.