Hospital waste is a burning issue that severely impacts public health. This study in three big hospitals in Lahan and Rajbiraj, Nepal, for one year (2019 March-2020 February) aims to analyze some parameters that directly help waste management properly. Field study, questionnaire, and interview methods were followed. The average moisture content of wastes of all three hospitals was 55.79%. There was no variance in the three hospitals’ moisture content values of wastes (F = 1.89 P-value = 0.165 F crit = 3.284917651). The average temperature of dumped waste was 23.23°C, and the temperature of all three hospitals was closely associated (F = 0.998, P-value 0.379, Fcrit = 3.28). The average pH value of wastes from the three hospitals was 4.44, and it from all three sites was strongly associated (F = 0.0668, P-value 0.935, Fcrit = 3.284). There was no relation between income and types of waste production (ꭕ2 = 0.8, df = 4, significance level = 0.05), but there was a high association between the level of income and amount of waste production. There was a high association between the nature of hospitals and types and the amount of waste (ꭕ2 = 77.09, df = 4, Significance level = 0.05). In Sagarmatha Choudhary eye hospital Lahan, there was no significant correlation between the number of patients and the amount of waste (Correlation = -0.187889 at 0.05% significance level). Unique Hospital Rajbiraj showed a correlation between the number of patients and the amount of waste (correlation = 0.1183 at 0.05% significance level). In Gajendra Narayan Singh Hospital, there was a correlation between the number of patients and the amount of waste (Correlation = 0.3453, at 0.05% significance level). There was no association between the qualification of respondents and their responsibilities regarding the services provided by hospitals (ꭕ2 = 1.43, df = 6, Significance level = 0.05). It is recommended for better management and installment of modern technologies for waste management.

Globally organic wastes are generated from fruits, vegetables, and their peels. It is mostly decomposed in landfills or by composting methods. Food processing industries, vegetable markets, and restaurants produce a huge amount of organic waste daily, generally disposed of in the environment or composted. Producing an eco-enzyme from organic kitchen waste was an innovative solution for domestic waste pollution. It is an enzyme solution obtained from an organic waste substance that contains organic acids, enzymes, and mineral salts. It is produced by performing a simple batch fermentation that involves a mixture of brown sugar, fruit or vegetable waste, and water in the ratio of 1:3:10. Two types of the eco-enzyme were produced by a fermentation process using vegetable and fruit peels for about 90 days involving Saccharomyces cerevisiae. The ultimate liquid or enzyme obtained was brown. Eco-enzyme 1 from (Cucurbita maxima) contained hydrolytic enzymes like amylase and lipase. The microbial diversity was observed, and bacteria like Yersinia sp., Bacillus sp., and fungi like Trichoderma sp. and Penicillium sp. No enzymes and microorganisms were observed in Eco-enzyme 2 (Citron). Eco-enzyme 1 with 50% dilution effectively reduced various parameters like BOD, COD, TDS, Nitrate, Nitrite, and Ammonium in the effluent. Also, it promoted plant growth within 10 days compared to the control. Therefore, the present study outlines how the eco-enzyme could be used to treat industrial effluent cost-effectively and environmentally friendly.

In the present study, we studied the concentrations and proportions. We identified the potential sources and health risks of 12 probably carcinogenic polycyclic aromatic hydrocarbons (PAHs) in rice grain from 31 sites in Thailand and Myanmar. The findings showed that PAH concentrations in rice grain samples from Thailand and Myanmar were in the range of 0.09 to 37.15 ng.g-1 with an average value of 18.22 ± 11.76 ng.g-1 and 0.07 to 150.73 ng.g-1 with an average value of 34.70 ± 40.57 ng.g-1, respectively. The majority group of PAHs in the rice grain samples from Thailand were the five-ring PAHs (78%), followed by four-rings (12%) and three-ring PAHs (9.5%), respectively, while for Myanmar was the five-ring PAHs were the majority (64.02%), followed by six-rings (15.22%) and four-ring PAHs (13.58%), respectively. The diagnostic ratio analysis suggested that pyrogenic origin is a major source of PAHs, and principal component analysis (PCA) identifies the incomplete combustion of fuel as likely the primary source of emissions source of PAHs contamination in rice grain samples. The total values of incremental lifetime cancer risk (ILCR) of PAH content of rice grain for children and adults were 1.95 × 10-8 and 1.44 × 10-8, respectively, for Thailand and 1.83×10-7 and 1.35×10-7 for Myanmar, which showed that the incremental lifetime cancer risk from rice grain was lower than the baseline set is considered to be safe levels.

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.