Pharmaceutically Active Compounds in Water Bodies—Occurrence, Fate, and Toxicity

The presence of pharmaceutically active compounds (PhACs) in water bodies has been considered an issue of global concern due to their high consumption and release into the environment, especially under pandemic conditions such as current COVID-19 situations. Additionally, the appearance of antibiotic-resistant bacteria (ARBs) and antibiotic resistance genes (ARGs) threatens the effectiveness of the pharmaceuticals developed to treat certain diseases. To address this problem, there have been efforts to develop efficient and cost-effective (waste)water treatment methods or to upgrade the existing facilities to regenerate clean water resources. According to the reports available in the literature, the effectiveness of these methods is highly dependent on the applied technology and the type and concentration of the PhACs. The efficiency of these systems can also determine the environmental and ecotoxicological effects expected from the release of these compounds. This chapter aims to summarize and discuss the available literature on the occurrence, environmental concentrations, fate, and possible effects of typical PhACs when introduced into receiving environments. The existing research gaps have also been discussed, and recommendations have been provided for further studies. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Efficacy Evaluation of Silty-Sandy Soil and Chrysopogon zizanioides to Attenuate Doxycycline from Wastewater in a Constructed Wetland System

In recent years, the emergence of COVID-19 has created disastrous health effects worldwide. Doxycycline, a member of the tetracycline group, has been prescribed as a treatment companion for attending this catastrophe. Due to extensive use and high solubility, a significant amount of un-metabolized doxycycline has been found to reach water bodies within a short time, and consumption of this water may lead to the development of fatal resistance in organisms and create health problems. Therefore, it has become necessary to develop suitable technologies from a geoenvironmental point of view to remove these unwanted antibiotics from wastewater. In this context, locally obtainable silty-sandy soil was explored as a low-cost material in a constructed wetland with Chrysopogon zizanioides (vetiver sp.) for phytoremediation to mitigate doxycycline spiked wastewater. The obtained soil hydraulic conductivity was 1.63×10-7 m/s. Batch adsorption tests conducted on silty-sandy soil, vetiver leaf, and vetiver root provided maximum removal efficiencies of 90%, 72%, and 80% percent, respectively, at optimal sorbent doses of 10 g/L, 17 g/L, and 16 g/L, and contaminant concentrations of 25 mg/L, 20 mg/L, and 23 mg/L, with a 30-min time of contact. The Freundlich isotherm was the best fit, indicative of sufficient sorption capacity of all the adsorbents for doxycycline. The best match in the kinetic research was pseudo-second-order kinetics. A one dimensional vertical column test with the used soil on doxycycline revealed a 90% breakthrough in 24 h for a soil depth of 30 mm. Studies on a laboratory-scale wetland and numerically modeled yielded removal of around 92% by the selected soil and about 98% combined with Chrysopogon zizanioides for 25 mg/L of initial doxycycline concentration, which is considered quite satisfactory. Simulated results matched the laboratory tests very well. The study is expected to provide insight into remedies for similar practical problems. © 2023 American Society of Civil Engineers.

The Effect of Harmful Algal Blooms on COVID-19 Patient Outcomes in Florida

Harmful Algal Blooms (HABs) in coastal and inland waterbodies release toxins which are known to have negative effects on local ecology and public health. Toxins released by Karenia Brevis and other phytoplankton are known to cause fatigue, muscle aches, neurological and respiratory illness in humans after exposure, which match those of COVID-19. A relationship between HABs and COVID virality could help explain the seasonality and unique symptoms in COVID-infections. COVID infection, hospitalization, and ICU usage data in the state of Florida were compared with instances of K. brevis blooms on a state and county basis. Results of correlation analysis indicate that blooms potentially correlated with increased hospitalizations compared to infections on a state-level. County level analysis was inconclusive. Due to broadness and complexity of subject, further investigation is necessary to fully understand how HABs and coastal ecology affect public health and virality of infectious disease. © 2022 IEEE.

Smart Aero-Spider: An adaptive and selective smart switching aerator system

The recovery from the COVID-19 pandemic hit shows the emergence of increase in quality of life across various parts of the world. With this lifestyle change, people are looking towards high quality food. Fish being a major source of protein, the industry producing fish from aquaculture is booming. The proposed smart aerator system provides an integrated array of underwater systems for selective aeration of the water body. The smart system ensures targeted aeration to guarantee optimal levels of dissolved oxygen at all times. This is beneficial for perfect survival, growth, and reproduction of fishes. The strategically placed spider aerators are turned on when readings from the dissolved oxygen level at the location is below the optimum range of values. The air blower system consists of an intelligent switching system to activate the right aerator based on the requirement. The sensor data is relayed to the cloud with a wireless communication module. This data can be used for useful insights and all-round monitoring of the water body. The respective aerators have IR sensor to detect movement alongside on-board LEDs to indicate functioning status. Overall, this ensures maximum accelerated growth of healthy fishes. Thus, the solution aims at efficiently boosting the ability of the aquaculture industry to meet the ever-growing demand of consumers. © 2022 Institute of Physics Publishing. All rights reserved.

Land cover change in Badung Regency 2016-2020 : An approach using machine learning method: Random Forest Extreme Gradient Boost (XGB)

Badung Regency is one area that mostly suffered from Covid-19 pandemic. Their gross regional domestic product has decreased 21.5% from 2019 to 2020 because of sluggishness of the tourism sector. It also affects the physical development of Badung Regency as a fast-changing area. To map the change of its land cover, satellite imagery-based classification was conducted. Both optical and radar imagery has its own deficiencies due to cloud cover in optical imagery and difficulties in interpretation in radar imagery. Therefore, combining optical and radar imagery and classifying the land cover through machine learning (ML) algorithm is necessary. In this study, we compare two methods of ML which are Random Forest and Extreme Gradient Boost. Sentinel 1 and 2 imageries utilized as the input to derive land cover change from 2016 to 2020. The data is classified into five classes: dense vegetation, sparse vegetation, bare land, water body, and urban, using supervised classification. As for training and validation, the field survey data was conducted. With similar input and set of training data, Extreme Gradient Boost (XGB) methods yield higher average accuracy than Random Forest (RF). The XGB has around 93% of accuracy, while RF has around 76% accuracy. From the result of land cover change using XGB method, bare land and water bodies are decreasing 22.9% and 4.1% consecutively. While urban areas and sparse vegetation, slightly develop around 5.6% and 1.26%. Dense vegetation has almost not changed with increasing 0.34% of its area. © 2021 IEEE.