With India’s population growing at a rapid pace, traditional agriculture will have a tough time meeting future food demands. Water availability and conservation are major concerns for farmers. This paper aims to discuss the aspects related to designing and fabricating an automatic irrigation system using the Internet of Things (IoT) which will save the farmer’s time and money significantly. Human intervention in fields will be reduced. Changes in soil moisture are detected by soil moisture sensors and irrigation is automated using IoT. The proposed system is most economical for underdeveloped places because it is very cost-effective. Based on the soil moisture content, the sensor detects and sends signals to the node MCU, which activates the motor. When the plants receive enough water, the motor automatically shuts off. The user will be alerted about the soil’s moisture content through his mobile phone. The proposed smart irrigation system is implemented at our campus which conserves energy and water.

The objective of the research was to evaluate the effect of geographic altitude on the carbon stock in two physiographic units of the Reserved Forest of the Universidad Nacional Agraria de la Selva, Tingo Maria-Huanuco. The methodology used was the field manual for the remeasurement and establishment of plots of the Amazon Forest Inventory Network (RAINFOR), for which 2 hectares were permanently established (one hectare in low and high hills) in which the diameter (greater than or equal to 10 cm) and the height of the trees were measured. Finally, the density of the wood was obtained from previous studies. The pantropical model formula was used to estimate the carbon stock. The results show that geographic altitude significantly affects carbon stock (p < 0.05) in low and high-hill forests, concluding that this may be due to differences in meteorological variables such as precipitation, temperature, and humidity.

Environmental pollution is a serious concern nowadays with its disastrous impact on living organisms. In several types of pollution, Air pollution takes on a crucial role by directly affecting the respiratory system and causing fatal diseases in humans. Air pollution is a mixture of gaseous and particulate matter interweaved by different sources and emanating into the atmosphere. In particular, particle pollutants are critical in growing air pollution in India’s main cities. Forecasting the particulate matter could mitigate the complications caused by it. The employment of a model to predict future values based on previously observed values is known as time series forecasting. In this paper, the PM2.5 pollutant emission data recorded at the Kodungaiyur region of Chennai city were forecasted using three-time series models. The standard ARIMA model is compared with the deep learning-based LSTM model and Facebook’s developed Prophet algorithm. This comparison helps to identify an appropriate forecasting model for PM2.5 pollutant emission. The Root Mean Squared Error (RMSE) acquired from experimental findings is used to compare model performances.

The review paper comprised the impact of geographical and environmental factors on polyploidy and vice versa. The review covers different effects of geographical factors, like spatial isolation, altitude, and local climate on polyploidy, and the behavior of polyploid(s) in abiotic factors, such as temperature and light with a few examples of northwest Himalayas. The paper concludes that polyploid plants behave differently in environmental conditions, as polyploids are more prominent in higher altitudes, colder environments, and nutrient-rich soil than diploid progenitors, but have a mixed distribution in different geographical conditions. Further, polyploidy is more common among perennials than annuals, while niche differentiation depends more on the local environment. The virtual case study results from North and North Western India have been shown with the help of ArcGIS online software. The scrutiny of spatial distribution on maps highlights the fact that polyploidy is still a complex research puzzle with interesting perspectives.

Goa is a coastal State located on the west coast of India, known for its pristine sandy beaches and environment. Ministry of Environment and Forest implemented Coastal Regulation Zone Notification in 1991 for monitoring the coastal zones for unplanned developmental activities but has been just for name-sake purposes (Mascarenhas 1999, Agarwal 2019). The regulation has been changed in recent years thereby making the coastal and the riverine ecosystem more vulnerable to human interference. In the name of development, various hap-hazardous, unplanned activities have taken place which is degrading the coastal and riverine environment, especially mangroves. This paper studies the vulnerability of mangroves to the changing regulations with respect to 1991 and the 2018 CRZ notifications considering the land use land cover changes in the regulated zones of Mandovi and Zuari rivers. Spatial analysis techniques and software such as Arc GIS 10.3, and ERDAS IMAGINE 2014 have been used for analysis and results. The findings from the study can be effectively implemented in monitoring the regulated zones and protecting mangroves efficiently.

The study assessed the status of water quality parameters for an urban water body (Hatirjheel Lake) in Dhaka, the Capital city of Bangladesh. Nine different water samples were collected from nine points of the lake during the dry season in January 2021. Water quality parameters such as pH, electrical conductivity (EC), total dissolved solids (TDS), total suspended solids (TSS), total alkalinity, total acidity, total hardness, Ca2+ hardness, free CO2, and dissolved oxygen (DO) were determined for the samples. The status of the parameters is pH (6.51-7.05), EC (510-600 μS.cm-1), TDS (450-590 ppm), TSS (0.0-0.034 mg.L-1), total alkalinity (80-392 mg.L-1), total acidity (224-500 mg.L-1), total hardness (348-452 mg.L-1), Ca2+ hardness (74-162 mg.L-1), free CO2 (730-1170 mg.L-1), DO (2.7-5.5 mg.L-1). However, the DO value at some points of the lake is too less (2.7 mg.L-1 and 3.7 mg.L-1) than the standard value (> 5-6 mg.L-1) of ECR, DoE, which might not be healthy for any water body and aquatic ecosystem. Other water quality parameters are within the permissible limit of WHO and ECR, DoE.

Based on the sand volume and sedimentation volume data for different particle size (PS) groups, the relationship between the annual scouring and silting amount of the Juliu River-Liujianfang section and the yearly sediment volume entering the downstream river channel was established. The critical values of sediment storage and release for the downstream river channel were obtained. It was found to decrease with an increase in the sediment particle size. The correlation coefficient between the annual scouring and silting amount of the Juliu River-Liujianfang section and the annual sediment volume entering the downstream river channel increased with the coarsening of sediment PS. It indicated that the sediment size was proportional to the sediment amount (SA) entering the river channel. As the sediment size increased, the deposition amount increased due to the variation of unit sediment amount. Based on the treatment and achievement of source areas with sediment sizes larger than 0.05 mm, it is significant to concentrate on treatment areas with sediment sizes larger than 0.10 mm.

The requirement for a renewable and environmentally gracious alternative resource of energy has grown in recent years as a result of increased knowledge of the negative impacts of petroleum-based fuels on the environment and the regular rise in crude oil prices. Biodiesel has been proven to be the ideal replacement for diesel because of its unique qualities, such as a huge decrease in greenhouse gas emissions, nonparticulate matter pollutants, non-sulfur emissions, less toxicity, and degradability. This article examines the pre-treatment stage, the physiological and chemical features of WCO, transesterification, esterification, and the manufacturing of biofuel from waste-cooked oil using several techniques and catalyst types. The elements that influence the stated process parameters are investigated, with a particular focus on the methanol to oil ratio (molar ratio), time of reaction, the temperature of the reaction, catalyst percentage, and yield of biodiesel. After the production of biodiesel, we can optimize the process parameters, for example, methanol to oil ratio, the temperature of the reaction, duration of reaction, and catalyst percentage, and also optimize the yield of biofuel generation with the CCD design of the Response surface methodology (RSM) algorithm using Design Expert software.

Taking Zhahan village in Qiongzhong County, Hainan, as an example, and based on its 160,000 tourist arrivals in 2019 and taking into account the real circumstances of Hainan, this research composes the emission models of carbon emissions from tourism transportation, tourism accommodation, tourism catering, other tourism activities and pollutants in this village. The outcomes indicate that Zhahan village's tourism catering consumes the most energy and emits the most carbon, accounting for 53.95% of all carbon emissions. Furthermore, the emission of tourism accommodation is the second, occupying 24.13%. Then, its tourism waste emission is the third, constituting 13.61%. In addition, its annual sewage discharge from tourism activities amounts to 15,144 t. This article promoted 1MW photovoltaic and 10 square solar hot water in the entire village, scientifically developing the evaluation system of rural tourism carbon emission, and making a low carbon brand of emission reduction coupling. The research and operation can be replicated and extended to enable the harmonious development of tourism development and organic unity of energy resource utilization.

The present study evaluated lead biosorption by Enterobacter cloacae WW1 isolated from tannery wastewaters under different initial Pb2+ concentrations, biomass concentrations, and contact times. The results showed that at an initial Pb2+ concentration of 80 mg.L-1, the optimal conditions for living cells were a biomass concentration of 7 g.L-1 and a contact time of 120 min. For non-living cells, biomass was a biomass concentration of 4 g.L-1 and contact time of 45 min, which provided removal efficiencies of 92.03 ± 0.10% and 99.51 ± 0.01%, respectively. The maximum biosorption capacity obtained for non-living cells using an initial Pb2+ concentration of 640 mg.L-1 was 76.65 ± 0.05 mg.g-1. The equilibrium data followed the Langmuir and Freundlich models for living cells, and the data for non-living cell biosorbents fit the Langmuir model. The biosorption kinetics for living and non-living cells fit well with a pseudo-second-order kinetic equation. SEM-EDX analysis clearly showed the morphology and presence of Pb2+ particles on non-living cell surfaces after biosorption. In addition, the results revealed that functional groups such as hydroxyl, amino, carboxyl, amide, and phosphate groups on the bacterial cell surface detected by FTIR were associated with the binding of Pb2+ ions. The results indicated that E. cloacae WW1, a lead-resistant bacterium, can be used as an alternative biosorbent for lead removal from wastewater.