The air filter element of the engine can purify the air entering the combustion chamber to ensure the reliable operation of the engine, but at the same time, the pressure drop generated by the filter element also has a significant influence on the engine performance. In current work, a novel air filter element from wood fiber (AFW) was proposed. With the pressure drop across the AFWF as the optimization target, three different shapes of AFW were considered, namely flat shape, W shape, and sine wave shape. The geometrical parameters of the AFW were optimized by numerical approach, and the influence of optimal AFW and traditional pleated filter element on engine performance was tested through engine bench experiment, the results of which showed that: the sine wave-shaped AFW with filling rate of 0.05, tₛ = 20 mm, A = 10 mm, and S = 100/3 mm is the optimal AFW; under the engine torque of 40 N·m and engine speed of 2000 RPM, the specific fuel consumption of the engine equipped with optimal AFW is 0.0884 kg/kW·h lower than that of pleated filter element; compared with pleated filter element, the engine equipped with optimal AFW has lower exhaust temperature at the same engine speed.

Aulacoseira granulata (Ehrenberg) Simonsen 1979 are considered as the eco-variable species which varies in density and diversity along with their morphological traits with the interference of environmental changes, so it is considered as one of the major ecological indicators of the water quality of lotic as well as lentic aquatic ecosystems. To assess major environmental factors which contribute to A. granulata bloom in the riverine system, a study was carried out from 2018 to 2019 comprising four different seasons at 11 sampling sites of river Ganga in the middle and lower stretch of river Ganga comprising freshwater and estuarine zones. For the analysis, different univariate, as well as multivariate, analytical tools such as principal component analysis (PCA) and water pollution index (WPI) were used. In the finding, it was observed that the average abundance of A. granulata was found maximum during the winter season. Among all the studied sites, the maximum average abundance was at Balagarh (71,576 cell l⁻¹) and minimum at Diamond Harbour (68 cell l⁻¹). The environmental factors such as dissolved oxygen, depth, and altitude showed a significant influence on the growth of A. granulata, while the water temperature negatively influenced the growth rate of A. granulata. The WPI showed a significantly negative correlation with cell length. Finally, the study concludes that the blooming of A. granulata is highly influenced by varied environmental conditions along the river Ganga, suggesting possible eutrophication. Therefore, a certain minimum flow and depth especially during the lean season have to be maintained for the sustenance of planktonic biota in the river Ganga.

The objective of this research was to evaluate anaerobic co-digestion of guinea pig manure (GP) with Andean agricultural residues such as amaranth (AM), quinoa (QU) and wheat (TR) in batch biodigesters under mesophilic conditions (37 ⁰C) for 40 days. As microbial inoculum, sewage treatment sludge was used in two inoculum/substrate ratios (ISR of 1 and 2). In terms of methane production, the best results occurred in treatments containing AM and QU as co-substrate and an ISR of 2. Thus, the highest methane production yield in the GP:AM biodigesters (25:75) and GP:QU (25:75) with 341.86 mlCH₄/g VS added and 341.05 mlCH₄/g VS added, respectively. On the other hand, the results showed that methane production with an ISR of 2 generated higher yields for guinea pig waste and the methane fraction of the biogas generated was in a range from 57 to 69%. Methane production kinetics from these raw materials was studied using five kinetic models: modified Gompertz, logistic equation, transfer, cone and Richards. The cone model adjusted best to the experimental values ​​with those observed with r² of 0.999 and RMSE of 1.16 mlCH₄/g VS added. Finally, the highest biodegradability (experimental yield/theoretical yield) was obtained in the GP-AM biodigesters (25:75) with 67.92%.

The present research aims to investigate the impact of air pollution on the number of mortalities caused by COVID-19 per Pakistani province. To do so, for each independent area of Pakistan, the observed mortality due to COVID-19 has been standardized over the entire population using standard age groups ranging from 0 to 4, 5 to 9, 10 to 14,…, 65, and above years, supported by the 2017 state people census. The impact of air pollution and COVID-19 transience among Pakistani areas, Islamabad Capital Territory (ICT), and the Federally Administered Tribal Region (FATA) was analyzed by a multiple-linear regression model, while the broad collection of attributes was observed by the resources of local spatial autocorrelation indicators, including the spatial portion of COVID-19 association. The result indicates that the observed mortality rate is much higher than predicted in certain provinces, namely, the Khyber Pakhtunkhwa and Punjab provinces, and the prevalence of PM₁₀ was independently linked to mortality due to the corona virus. Additionally, the results of the local spatial autocorrelation indicators on the standardized mortality rate and PM₁₀ define a collection of very higher ideologies in the broad range of KPK and the southern part of Punjab province, respectively, with a definite degree of connection between the two distributions in the Khyber Pakhtunkhwa region. In brief, this research seems to find a justification for confirming the existence of a correlation between the possibility of COVID-19 mortality and air pollution, more precisely considering air pollutants (i.e., particulate (PM₁₀) and land take-over. To this end, the need to mediate in favor of measures aimed at eliminating emissions in the environment will be reiterated by speeding up current proposals and policies aimed at all causes of atmospheric pollution: urbanization, water and manufacturing, home heating, and transportation.

In Frongoch Mine (UK), it is unclear the distribution of metals on indigenous algae and whether these species of algae can accumulate metals. This study aimed to investigate the role of indigenous algae for metal removal from acid mine drainage and understand if metals can be adsorbed on the surface of algae or/and bioaccumulated in algae. A sequential extraction procedure was applied for algae samples collected from acid mine drainage (AMD) water to identify the forms in which metals are found in algae. Concentrations of Fe, Pb, Zn, Cu and Cd were evaluated in the algae and AMD samples were collected in June and October 2019. AMDs samples had a pH value ranging between 3.5 and 6.9 and high concentrations of Zn (351 mg/L) and Pb (4.22 mg/L) that exceeded the water quality standards (Water Framework Directive, 2015). Algae Ulothrix sp. and Oedogonium sp. were the two main species in the Frongoch AMDs. The concentrations of metals in algae ranged from 0.007 to 51 mg/g, and the bioconcentration factor of metals decreased in the following order: Fe > > Pb > > Cu > Cd > Zn. It was found that Zn, Cu and Cd were adsorbed onto the surface of and bioaccumulated in the algae, while Pb and Fe were mainly bioaccumulated in the algae. Indigenous algae can be considered as a biogeochemical barrier where metals are accumulating and can be used in bioremediation methods. Also, indigenous algae could be used as a bioindicator to assess water pollution at Frongoch Mine and other similar metal mines.

The current research was performed to evaluate the potential protective effect of Lactobacillus paracasei ssp. paracasei, Pediococcus acidilactici, Lactococcus lactis ssp. lactis, and silymarin in the alleviation of health (hepatic and renal) complications caused by carbon tetrachloride (CCl₄) in rats. Healthy sixty albino rats were divided into six groups, the first group was control (negative), the second group (control positive) was injected CCl₄ (1 ml/kg, 1:1 v/v paraffin oil mixture, i.p. every third day for 8 weeks), the third group (CCl₄ + silymarin group) receiving both CCl₄ and daily silymarin therapy (50 mg/kg, oral), and the fourth group: CCl₄ + Lactobacillus paracasei (1 ml orally). The fifth group (CCl₄ + Pediococcus acidilactici 1 ml orally) and the sixth group (CCl₄ + Lactococcus lactis 1 ml orally) for 8 weeks per day. Biochemical markers were tested for blood, liver, and kidney tissue. Histopathological examination of the liver and kidney tissues was performed. The findings obtained have shown that Lactobacillus paracasei ssp. paracasei, Pediococcus acidilactici, and Lactococcus lactis ssp. lactis improved the disrupted biochemical parameters caused by CCl₄ therapy. Besides, the findings of the histopathology are in consistent with biochemical parameters and the protective ability of lactic acid bacteria suggesting that the best lactic acid bacteria were Pediococcus acidilactici that helped strengthen liver fibrosis caused by CCl₄ therapy, while the best bacterium for improving renal damage was Lactococcus lactis.

Although it has been proven that the addition of shear-thinning polymers can lead to an improvement in the sweeping efficiency of the remedial agent in heterogeneous aquifers, the related mechanisms require further investigation. This study revealed the mechanisms associated with the improvement of fluid sweeping uniformity. Under the assumption of no transverse flow existed between layers, the variation patterns of the fluid sweeping uniformity in strip layered heterogeneous media (RP/RK) with the change of the fluid hydraulic conductivity were investigated. The outcomes showed that, for the hydraulic conductivity dominated fluid sweeping uniformity control, the performance was satisfactory only when the ratio of the hydraulic conductivities of viscous fluid in porous media (PM) layers (K₁P/K₂P) is less than 2.5 times that of pure oxidant solution (K₁K/K₂K), and PM combinations with higher permeability contrast usually present a wider applicability and better performance. In addition, transverse fluid movement was more likely to occur in layers with low permeability contrasts (2.3–5) than in those with relatively higher permeability contrasts (> 11). The observed transverse pressure difference directly confirmed the hypothesis of the dynamics of the cross-flow mechanism that existed during viscous fluid flow, and the relationships between the fluid fronts and the pressure head difference at each point (Px) were proposed. Our study exemplifies an effective strategy for determining the most economically effective co-injection concentration of xanthan to achieve highly efficient delivery of remedial agents.

Presently, the rapid pace in the discovery of emerging aquatic pollutants is increasing the demand for the remediation and treatment of our natural resources. Regarding this, nanotechnology is being considered the potential solution for contaminated water remediation with techniques such as filtration, adsorption, catalysis, and desalination. For this purpose, zerovalent iron (ZVI) is being widely used in the remediation of environmental pollutants due to its large specific surface area and high reactivity. However, ZVI is easy to agglomerate and oxidize, limiting its application in the real environment. Therefore, the present study was designed to discuss the preparation and characterization methods of ZVI composite materials, factors affecting adsorption, the removal effect, and adsorption mechanism of different pollutants by Fe–C materials because the optimization and modification of nano-zero-valent iron is a hot research topic nowadays in this field. Moreover, this paper does also analyze the possibility of the practical application prospects of the team’s technology for preparing iron-carbon materials. Thus, this information will be helpful for the development and application of Fe–C-based technologies for water and soil remediation and the prediction of the future research direction of Fe–C composite materials.

This study investigates the effect of income inequality and institutional quality on carbon emission in 180 countries of the world from 2002 to 2019. The study employed OLS, fixed effect, and system generalized method of moments (SGMM), and the results show that income inequality, institutional quality, financial development, and economic growth have a direct significant and positive effect on carbon emission while trade openness and renewable energy significantly reduce carbon emission. VOA, ROL from the legal system, and GOV from the political system negatively affect carbon emission while the interaction term between GDP and GINI is found negative for carbon emission while the interaction of FD and GINI, INST and GINI, FD, and GDP are positively linked with carbon emission. The EKC hypothesis has been evidenced in the analysis with all INST indices. Our findings have considerable policy implications for the sample countries regarding the income inequality and institutions’ development toward environmental quality enrichment.

Green innovation is becoming more common among researchers and practitioners around the world due to environmental and social issues. Green innovation minimizes wastes and pollution, and also leads to financial gains and better image if implemented effectively. Nowadays, developing countries pay greater emphasis on environmental issues as their manufacturing industries are considered major contributors to pollution. Considering the case of a developing country (Pakistan), the study empirically identified the drivers of green innovation in the manufacturing industry. A hybrid methodology—Fuzzy Delphi method (FDM), interpretive structural modeling (ISM), and cross-impact matrix multiplication applied to classification (MICMAC)—was used to develop a novel framework for analyzing the green innovation drivers. At first, green innovation drivers were selected from past studies; they were further screened by applying Fuzzy Delphi approach. The MICAMAC and ISM results indicate that “cost reduction” and “government support” are the most important drivers motivating green innovation implementation in the Pakistani manufacturing industry, while a green image appeared as the least significant driver of green innovation adoption. The study’s findings have significant implications for managers and policymakers to develop green strategies for manufacturing sector.