The present study aimed to evaluate the possible impact of noise pollution. This study was conducted in Raipur, the capital of Chhattisgarh state, India, to analyze the relationship between noise pollution and health complaints. A total of 18 locations were selected for monitoring noise pollution levels in the morning (9:00-10:30 AM) and evening (7:00-8:30 PM). Noise maps were prepared for both the time interval, and it was found that the highest equivalent noise level (Leq)of 81.31 dBA was observed at location L3 whereas the lowest Leq of 63.25 dBA was observed at L16 in the morning and in the evening 77.33 dBA at L3 and 60.14 dBA at L16 were observed. A questionnaire survey was performed on the population (n = 400) exposed to noise and analyzed through a variance-based partial least square (PLS) structural equation model (SEM). From the survey, it was found that most of the respondents are exposed to higher noise levels and are facing health issues of “pain in the ear,” “rise in blood pressure,” “loss of sleep,” “whistling and buzzing” in their ear, “headache,” “heaviness” and “efficiency problem.” A total of 109 hypotheses were proposed and analyzed through bootstrapping with a subsample size of 5000 in SmartPLS software. 18 hypotheses were found to be significant in the proposed model. SEM analysis revealed an interrelation between noise pollution and health effects. It is recommended that strict regulation in nearby sensitive areas must be imposed and an awareness drive on a large scale shall be conducted to enlighten the city’s population regarding noise effects as well as various measures for controlling.

Plastics are the most rapidly growing materials in terms of production and consumption. The durability, inertness, light weight, flexibility, and low cost are the key characteristics that make plastic suitable for application in various fields, including the construction, automotive, electronics, and packaging industries. Due to widespread usage in daily life and many industrial processes and operations, more than 300 million tons of plastic waste are produced globally annually. Indiscriminate use of plastics such as polyethylene causes environmental pollution and impacts human health due to irreversible changes in the ecological cycle. Due to its low biodegradability, polyethylene accumulation has recently emerged as a momentous environmental concern. The conventional methods, such as recycling or disposing of polyethylene, are exorbitant, and incineration results in the emission of toxic chemical compounds. Therefore, the most recent research progressively focused on the biodegradation of polyethylene with the application of bacteria as novel approaches to counteract plastic waste. This review summarizes the type of polyethylene and the environmental issues. It also briefly discussed the genes and enzymes of bacteria involved in the degradation of polyethylene. In addition, it attempts to address factors influencing degradation and techniques used for monitoring degradation.

The present study analyzed the spatio-temporal variations in the Land Use Land Cover types within Ranipet Municipal town in Ranipet District, Tamil Nadu State, India, using two different platforms (QGIS and IDRISI Selva v.17.0). The possible parameters driven the net changes in the Land Use Land Cover (LULC) types were also incorporated for the analysis. Results revealed the positive net changes in the built-up area are about 26.8%, and combined other classes like vegetation, barren land, and water bodies have net negative changes during 1997-2019. Particularly barren land was found to have a reduction of 17.4% due to the massive industrialization in the study area. Further, the LULC maps were used for future prediction (2029) using the dynamic models of CA-ANN (Cellular Automata and Artificial Neural Network) and CA-Markov. Predicted maps yielded a kappa index of 81.6% and 82.6% for CA-ANN and CA-Markov, representing their respective accuracy levels. The CA-Markov model is extended for determining the probable long-term changes for 2080 in LULC with a kappa index of 76.2%. Compared to the CA-ANN model using the QGIS platform, CA-Markov provided better analysis, particularly from one cell to the other. According to the survey and the ground truth in the locality, industrialization and occupational shift were the most influential drivers of LULC dynamics. Moreover, the results of this study assist the stakeholders in the decision-making process for future sustainable land use management.

The rapid depletion of the world’s fossil fuel reserves and global warming issues have promoted the search for sustainable alternative energy resources. In the present investigation, large-scale cultivation of naturally isolated freshwater microalgae Asterarcys quadricellulare strain was carried out using tertiary treated municipal wastewater as a growth medium in an open HRP pond for bioethanol production. A total of 12.091 kg of dry biomass was obtained at the end of the study. The lipid extracted carbohydrate rich spent microalgae biomass was converted to bioethanol by ethanolic fermentation. The biomass was first pre-treated with different concentrations of H2SO4 and HCL hydrolysis with different temperatures and reaction times. The biomass treated with a 2.0% concentration of H2SO4, showed maximum yields of glucose 308.38 mg.g-1 at 100°C with 180 min reaction time. The hydrolysates derived from the hydrolysis of microalgae biomass were used as a substrate for fermentation by using S. cerevisiae. The obtained bioethanol was analyzed using HPLC and the purity of ethanol was 90%.

Laguna de Bay is the largest lake in the Philippines. It is surrounded by developing cities that pollute the lake with plastics from different industrial and domestic activities. In the study, microplastics were collected from the lake’s surface water through three (3) collection points within the lake. The collection of microplastics was conducted from August 2018 to October 2018. About eight-hundred ninety (890) microplastics were collected and cataloged. Among the collection sites, ‘Brgy. Sampiruhan’ has the most microplastics, with a median of 15 ranging from 11-24 microplastics per 1000 L of lake water. On the other hand, ‘Brgy. Napindan’ has a median of 4 which ranges from 2-6 microplastics per 1000 L, and ‘Brgy. San Isidro’ has a median of 6 which ranges from 4-24 microplastics per 1000 L. Image analysis revealed that microplastics from this site were larger and angular. The color analysis shows signs of whitening and yellowing of the plastic materials, which suggests that the microplastics undergo photodegradation. Fourier-transform infrared spectroscopy (FTIR) found that most of the microplastics in the lake are made of polyethylene and its derivatives. Microplastics in Laguna de Bay show the continuous plastic pollution in the Philippines’ largest lake.

Insect pest control is one of the major issues facing the agriculture sector because of the need for new agrochemicals and biocontrol agents that are environmentally friendly, economically affordable, and safe for human health. Spodoptera frugiperda (fall armyworm) is one of the insect pests that causes huge damage to various crops around the globe due to its generalist nature. In the present study, three selected Embelia ribes Burm F (Myrsinaceae) constituents, which include embelin, 5-O-methylembelin, and vilangin; one semi-synthetic compound (potassium embelate); three synthetic compounds, namely coenzyme Q10, dopaquinone, and idebenone; and two reference compounds (azadirachtin and amitraz) were assessed on the docking behavior of S. frugiperda (beta glycosidase and caspase-1. The docking studies showed that coenzyme Q10 exhibited the highest binding energies (-130.61 and -434.56 kcal.mol-1) for the target enzymes S. frugiperda (beta glycosidase and caspase-1, respectively). Thus, the present investigation provides new knowledge in understanding Embelia ribes Burm F (Myrsinaceae) constituents as possible inhibitors against S. frugiperda (beta glycosidase and caspase-1) enzyme activities. Furthermore, the present work can help to develop new insecticides and pesticides against S. frugiperda and other related insect pests.

Globally, vehicular pollution is one of the greatest concerns in urban areas. Several studies on air pollution have been conducted using deterministic, statistical, and soft computing methods. However, there has been little research on how soft-computing methods like Artificial Neural Networks (ANN) can help us comprehend vehicular pollution’s non-linear and highly complex dispersion. This study uses an ANN-based vehicular pollution model to investigate the effect of vehicular traffic on PM2.5 concentrations in built-up and open terrain-surrounding environments. Five distinct pollution models were developed for two locations in Delhi, considering PM2.5 pollutants, meteorological variables, traffic flow, and traffic composition into account. The results concluded that under open terrain conditions, the significance of the traffic variable in its association with PM2.5 is almost half the significance observed under built-up conditions. Also, in terms of PM2.5 reductions, the maximum reduction observed at Location-1 (built-up environment), and Location-2 (open terrain environment) is 1.85 and 2.44 times the percent reduction in traffic during peak hours, respectively. The study’s findings have significant ramifications for the current practices of ignoring the contribution of traffic and the built environment to pollution and adopting measures like an odd-even rule and high fuel and parking prices to combat pollution.

Shoreline change is a process that occurs due to the impact of natural factors and human activities. Geographically, the coastal area of North Central Timor Regency (NCT) is in the northern part of the island of Timor, East Nusa Tenggara Province (ENT). Physically, the area is affected by the oceanographic dynamics of the Sawu Sea waters and aquaculture activities, which impact the damage to coastal ecosystems. This study aims to analyze shoreline change in the northern coastal area of NCT Regency. The data used are Landsat 8 images from 2015-20221 to describe current conditions. Meanwhile, Landsat 5 imagery data from 1990 - 2000 was used to describe the initial conditions. The satellite imagery is analyzed to map shoreline changes that experience accretion or abrasion. The results show that the shoreline of the study area has experienced changes in accretion and abrasion. Based on the area of change in the northern coastal area of NCT Regency, the dominant accretion area was 1108.07 m2 with a rate of change of 20.19 m.year-1, as long as 1021 meters, while the abrasion was 845.43 m2 at a rate of 12.65 m.year-1 as long as 36520 meters. The average shoreline change distance in accretion conditions was 11.3 meters, while the abrasion was 7.93 meters. The shoreline shift due to the highest abrasion in Ponu was -16.08, while accretion in North Oepuah was 35.63 meters. The results of this research will contribute to planning the management of the coastal area of NCT Regency.

The increase of nitrogen and phosphorus causes eutrophication in water bodies. Using submerged plants to decrease the pollution from water bodies is an effective way. In this research, three common submerged plants (Vallisneria natans, Hydrilla verticillata, and Ceratophyllum demersum) and their combinations were used to purify eutrophic water. The control treatment did not contain any plants. The removal effects and dynamic regulations of the three plants with their combinations of nutrients (such as nitrogen and phosphorus) in water were analyzed. All three species and their combinations above could grow in the eutrophic water and efficiently remove aquatic nutrients. All the treatment groups had a higher pollutant removal rate for total nitrogen (TN) and total phosphorus (TP) than that of the blank control. In these treatment groups, treatment F (50 g Vallisneria natans plus 50 g Ceratophyllum demersum) had the highest removal rate of TP at 57.53%; treatment B (100 g Vallisneria natans) had the best removal rate of TN at 92.04 %. Among these plants and their combinations, Vallisneria natans and Ceratophyllum demersum showed better purification ability; the combination of these two submerged plants and the combination of three submerged plants were more applicable for the restoration of eutrophic water.

A state-of-the-art review of biomimetic nanoparticle synthesis is presented. The technique’s origin has been traced to the studies, started over 150 years ago, on the hyperaccumulation of certain metals by different species of plants. How the initial intracellular method of nanoparticle synthesis evolved into the now widely used extracellular route has been described. The review then covers the gist of all the studies reported on the biomimetic synthesis of nanoparticles of different metals using extracts of different botanical species (plants). The synthesis mechanism is discussed, and the factors influencing the nanoparticles’ extent, shapes, and sizes are identified.