Issue 5

Soil was familiar earlier in the context of agriculture and food production, but industrialization contaminated soils around the world in last two centuries. Most of the contamination is due to the consequence of improper discharge of industrial wastewater and one such situation is witnessed in the agricultural land nearby textile hub of Tiruppur, Tamil Nadu in Southern India. It is essential to identify the contaminants depth in soil system before propose any in-situ remediation technique. There is no study reported so far to understand the transport and fate of organic and inorganic contaminants of textile wastewater in soil system. This paper investigates the transport and fate of textile wastewater in soil column of 32 cm height and 8 cm diameter. Detailed investigation demonstrates the removal of color 15-84%, organic contaminants 4-51% and inorganic contaminants 11-36% from wastewater after its transport into the soil. The reduced level of calcium, magnesium and potassium ions in soil and corresponding increase in wastewater reveals anion and cation exchange between wastewater and soil. Thus the results confirm the accumulation of residual textile dyes and inorganic salts in the soil and it is huge in surface soil of 0-15 cm depth, further it requires immediate restoration.

Water waste management is one of the major hassles which is faced by the majority of industries. The industries let the wastewater into flowing streams or rivers near them, polluting the water resources in that locality. To prevent and safeguard the water resources, the government has given much regulation on the quality of the water before it is drained into the water sources. One of the primary problems is the amount of pH which is present in the wastewater. The pH is a highly non-linear quality of the liquids, as a single drop may change the quality to either acidic or alkaline. In this paper, the different proposed methods were used for maintaining the pH of wastewater by using various intelligent controllers. The Nonlinear Autoregressive with External Controller (NARX) and Nonlinear Autoregressive (NAR) under deep neural network is proposed where the NARX model is synthesized based on two different algorithms which involve the Levenberg Marquardt (LM) and Scaled Conjugate Gradient (SCG) for maintaining pH. The controllers are implemented into the process tank of the pilot plant for the determination and neutralization of the pH. The pilot plant is interfaced MATLAB R2019b with the computer as a controller where the controller action for the neutralization is processed. The proposed NAR model did produce better results than the other models, whose settling times were 8.6 seconds and 0.5% overshoot. The NAR model has better results when compared with the other two neural models.

In recent years, the need for the rapid development of rural tourism in China has resulted in a large consumption of ecological resources, which has seriously damaged the ecological balance of travel destinations. Rural tourism in many parts of China is increasingly lacking distinctive local characteristics. It is difficult to adapt to tourists’ requirements for a deeper experience of rural travel. Some measures have been proposed to address these issues. Firstly, the connotation of “green” is reinterpreted based on relevant theoretical knowledge starting from solving the problem of rural tourism community development in China. The questionnaire method is used to screen the indicator system. An empirical analysis is carried out for actual cases. The pictures uploaded by tourists to social media are the main data source. A relatively complete and effective method system for the image research of rural tourism destinations is constructed combined with the visual analysis technology based on deep learning. A dense CNN model producing 10 output parameter combined with various factors is formed to assist the promotion by comparing the differences between the advertising pictures of the tourist destination and the pictures taken by tourists. The results show obvious consistency in the construction scene of the rural travel perception environment. Each tourist destination has its own visual characteristics, as well as differences in various sensory modality types. This research method adopts a combination of subjective and objective and comprehensively examines the scene conspicuousness, distinction, artistic quality, design quality, and time of the pictures. The formed marketing picture research method is more scientific and feasible.

The level of air pollution increased in urban areas due to local atmospheric conditions and dispersion of various air pollutants. In this study, the air quality index was carried out in four places in the urban zone and investigated the seasonal variation of PM2.5, PM10, SO2, NO2, and O3 over one year (2021) by considering the meteorological parameters in Coimbatore. Furthermore, fluidyn-PANACHE, a CFD tool, has been used to simulate the dispersion pattern of gaseous pollutants in the selected locations. To track the model, the concentration details of gaseous pollutants were collected and pollutant dispersion under numerous atmospheric conditions (Humidity, Temperature, Pressure) was identified using fluidyn-PANACHE software. From the collected air samples and dispersion pattern, SO2 and O3 show higher concentrations in summer. Particulate matter and NO2 show higher concentrations in winter due to seasonal variations in energy use and atmospheric constancy. Pearson correlation coefficients indicate most pollutants are correlated in Coimbatore except Ozone. Compared to the AQI category given by CPCB, the selected four locations are in the moderate category. However, increased PM10 levels were observed at all the selected zones in winter due to the process of inversion and environmental conditions.