Wastewater Treatment in Constructed Wetlands by Phytoremediation Technique

Water is the most required element next to air for terrestrial living being. Though the water is everywhere but no direct use is possible as the fresh water is getting contaminated through various human activities. The conventional treatment methods using activated sludge process, attached growth systems such as trickling filters, rotating biological contactors, aerated lagoons and stabilization ponds are normally practiced in many places with each one having its own merits and demerits depending on space availability, energy requirements etc. An alternative solution called phytoremediation method can save energy requirements to the great extent but space required will be more and it can be used advantageously where space is not a constraint. This method involves using plants to absorb and metabolize pollutants found in wastewater, including nutrients such as nitrogen and phosphorus, heavy metals and other organic and inorganic contaminants. In this study, sewage is passed through a bed of plants, which takes up nutrients and contaminants while releasing oxygen during their photosynthesis process. This promotes the growth of beneficial bacteria that further break down pollutants. In the present work, Spider lily (Hymenocallis littoralis) and Heliconia (Heliconia psittacorum) are two species of tropical plants used in constructed wetlands and that have shown potential in the treatment of sewage. Conducted the performance studies on both plants separately. The efficiency achieved with spider lily plants Heliconia plants are 87.2% and 79.6% in BOD removal respectively. These systems are also relatively low-cost and require minimal maintenance, making them a viable option for wastewater treatment in areas where conventional treatment systems may be too expensive or impractical

Extraction of Heavy Metals from Soil Affected by Landfill Leachate through Constructed Wetlands: A Phytoremediation Approach to Rejuvenating the Contaminated Environment

Water is one of the most essential elements of life. The water shortage is becoming a lurid issue in many regions, with over a billion people without passable water for drinking purposes. The leachate from landfill sites is a major problem and poses a threat to aquatic ecosystems and public health. To overcome this situation, either to remove contaminants or to reduce the amount of contamination, constructed wetlands using phytoremediation can be considered the best solution. This green low-cost technology uses plants to remove heavy metals from soil and water. The objective of this report is to study the removal of specific heavy metals such as Zinc (Zn), Nickel (Ni), Chromium (Cr), Cadmium (Cd), Iron (Fe) and Lead (Pb) from landfill leachate by using two laboratory scaled wetlands. These wetlands were filled with soil and planted with Typha Latifolia. One system was operated without recirculation and the other with effluent recirculation with an interval of one day. The influent and effluent physicochemical parameters were analyzed after 30 days and the concentrations of the heavy metals were observed. The wide variation is seen in the case of Nickel, Lead, Chromium, Cadmium, Zinc and Iron. The percentage of removal with recirculation and without recirculation is 100% for Cadmium and Iron, in the case of Nickel, Lead, Chromium and Zinc the percentage difference between recirculation and without recirculation was found to be 1.6, 2.4, 0, 0. Since the removal efficiency for Cadmium and Iron is predominant this study indicates that this technology gives good removal of heavy metals and has a scope for its effective analysis since it has low working and conservation costs; it is comparatively a step toward a sustainable economy

The National COVID Cohort Collaborative (N3C): Rationale, Design, Infrastructure, and Deployment

ObjectiveCoronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers.Materials and methodsThe Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics.ResultsOrganized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access.ConclusionsThe N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19