Healthcare

Treated refinery wastewater flowing through sand, cleans itself further with pollutant-eating bacteria, finds study

pro — Tue, 10 Sep 2024 09:15:30 +0000

Treated refinery wastewater flowing through sand, cleans itself further with pollutant-eating bacteria, finds study pro Tue, 09/10/2024 - 14:45

Refinery wastewater flowing through sand produced biofilms of pollutant-eating bacteria which inturn removed the harmful compounds from the water

? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?Representative image from Rawpexel

Refineries, which transform crude oil into useful products like gasoline and diesel, generate large amounts of wastewater. This water, which has been used for activities like steam generation and heat transfer, often contains harmful organic and inorganic pollutants, including nitrogen-containing compounds. The wastewater then undergoes several steps of treatment to remove most of these contaminants before it can be safely discharged into the environment. Scientists have been exploring alternative additional treatment steps that are both environmentally safe and economically viable.

A recent study by researchers at the Indian Institute of Technology Bombay (IIT Bombay) on biofilters, which are water filters that use microorganisms, like bacteria, to remove pollutants, has led to an interesting observation- partially treated wastewater from refineries already carry bacteria that can remove the organic contaminants from the wastewater. The researchers only had to provide a substratum- in this case, a column of pure quartz sand - onto which the bacteria could cling to get to work.

For their study, the researchers investigated the properties of sand as a biofilter. “Sand was chosen since it is commonly used in deep bed filters used for water and wastewater treatment,” remarks Prof. Suparna Mukherji, from the Department of Environmental Science and Engineering, IIT Bombay, who led this study.

The researchers designed a biofilter made of an acrylic cylinder measuring 45 cm in length and 2 cm in diameter. They filled it with pure quartz sand to a depth of 15 cm. The filtration process begins by allowing secondary treated refinery wastewater, which has undergone the removal of toxic chemicals, to flow through the biofilter at a controlled rate of 1 to 10 mL per minute. The wastewater flowing through the sand leads to the formation of a biofilm, made of several different types of bacteria enmeshed in extracellular polymeric substances secreted by the bacteria, on the grains of sand.

Schematic of sand biofiltration, photo of Sand biofilters made of acrylic, and microscopic images of the sand with and without the biofilm. (Credits: Authors of the study)

“As the water flows through the sand bed, bacteria present in the water/wastewater get adsorbed onto the sand. Subsequently, the attached bacteria replicate and secrete extracellular polymeric substances to form a biofilm on the surface of the sand grains. Bacteria grow using dissolved oxygen, organic carbon, and other nutrients from the water flowing through the sand bed,” explains Prof. Mukherji. This biofilm in turn eats away at the organic contaminants in the water. Degradation of organic compounds containing nitrogen releases inorganic nitrogen in the form of ammonium, which is further converted to nitrate. Although some removal of nitrate may have occurred, build-up of nitrate was observed after biofiltration.

The team analysed the Chemical Oxygen Demand (COD), Total Organic Carbon (TOC), and Assimilable Organic Carbon (AOC), which are measures of the various organic compounds in the water. Analysis of COD and TOC allows researchers to estimate the concentration of organic contaminants in the water. Remarkably, they observed a significant reduction in COD, TOC, and AOC after just two recirculations of the wastewater through the biofilter.

The team also used a technique called GCxGC TOF MS, which stands for Gas chromatography Time of Flight Mass spectrometry, to detect and quantify specific organic compounds in the water. “Recirculating the wastewater up to 12 times resulted in maximum reduction in COD and TOC of 62% and 55%, (by more than half) respectively. GCxGC-TOF-MS revealed that several of the identified target (harmful) compounds could not be detected in the wastewater after 12 recirculations, suggesting 100% removal,” adds Dr. Prashant Sinha, an author of the study, who was pursuing his PhD from IIT Bombay at the time of the study.

The nitrates produced by the bacteria during filtration, through conversion of other forms of nitrogen, caused a build-up of nitrates in the treated water. “The build-up of nitrates observed is not desirable. However, refineries commonly employ reverse osmosis (RO) as the final treatment step. This process can reduce the level of nitrates in the final effluent,” says Prof. Mukherji. Biofiltration can also reduce the deposition and accumulation of unwanted material on the RO membranes by reducing AOC.

The study also delved into the biofilter’s microbial community. It turned out that the predominant bacteria belonged to a group called Proteobacteria. The group is known for their ability to break down complex organic compounds like polynuclear aromatic hydrocarbons (PAHs), which are harmful to living organisms. The Proteobacteria group includes helpful bacteria like Sphingomonadales, Burkholderiales, Rhodobacterales, and Rhodospirillales, all recognized for their role in cleaning up hazardous pollutants.

Sand biofiltration method stands out for its simplicity, meaning it could be an accessible solution for many industrial plants worldwide. It could significantly reduce the environmental footprint of oil refineries. With pure quartz sand being easily available, the overall cost of building and maintaining such a biofilter at large scales remains very low, making the filtration economical. Prof. Mukherji, however, is already planning her next steps, saying, “We would like to explore this process further using other types of media and with different types of water/ wastewater”.

Article written by:? ? ? ? ? ?Dennis C. Joy
Image/ Graphic Credit: ?Lead image: Rawpexel
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?Inline Image: Authors of the study
Link to Gubbi Labs:? ? ? ?--

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Efficient treatment of secondary treated refinery wastewater using sand biofilt…

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Tue, 09/10/2024 - 12:00

Super-emitters on the road- A need for a comprehensive review of vehicular regulations

pro — Wed, 24 Jul 2024 10:13:54 +0000

Super-emitters on the road- A need for a comprehensive review of vehicular regulations pro Wed, 07/24/2024 - 15:43

Researchers from IIT Bombay study heavy polluters on the Mumbai-Pune Expressway and suggest the need for stringent policies to restrict vehicular pollution.

? ? ? ? ? ? ? ? ? ? ? ? ?Few identified super-emitters from the study. Credit: Authors of the study

The year 2023 shocked the globe as the hottest year in recorded history. The last 12 months have experienced the highest monthly temperatures ever recorded, and it looks like it is only going to get worse from here. With every passing year, the realities of climate change are being experienced globally, and the need for comprehensive climate action has never been greater. Air pollution, particularly airborne particles, contributes to climate and is associated with adverse health effects. According to the Global Burden of Disease Study (GBD, 2021), 16.7 lakh deaths have been attributed to air pollution in India.

Emissions from motor vehicles are major contributors to urban air pollution in India. Rapid urbanisation, leading to an increase in the number of vehicles on the road, is a cause for concern. Congestion increases the time spent on the road, leading to large amounts of fuel being burned, thus resulting in more pollution. However, the polluting characteristics of all vehicles are not the same. Some vehicles release disproportionately higher amounts of pollutants. A recent study from the Indian Institute of Technology, Bombay (IIT Bombay) investigates the factors determining the polluting characteristics of such high-emitting vehicles or super-emitters.

“Until now, there has been no study in India that has examined the share of super-emitters in real-world vehicular fleets. The previous studies assumed their share based on literature from other countries or secondary data. The motivation was to reduce uncertainty in the emission estimation from real-world vehicular fleets,” says Ms Sohana Debbarma, a researcher from the study who worked under the guidance of Prof Harish Phuleria and Prof Chandra Venkataraman.

Super-emitters are vehicles that are either old, poorly maintained, over-loaded heavy-duty vehicles or all of them. They release significantly higher amounts of pollutants compared to the other vehicles in the fleet. According to the IIT Bombay study, for light-duty vehicles (vehicles that weigh less than 3,500 kg such as cars, two-wheelers, three-wheelers, and light commercial goods vehicles), the age of the vehicles and the maintenance of the engine potentially determines whether the vehicle is a super-emitter. In the case of heavy-duty vehicles (vehicles that weigh more than 3,500 kg, such as buses and trucks), the overloading condition, along with the age and maintenance of the vehicles, contribute to the disproportionately high pollutant emissions.

Roadway tunnels offer ideal conditions for this study because of the confined space within the tunnel, which effectively traps the emissions from the vehicles, barring the influence of other ambient sources. It also has the added advantage of being able to collect data from a large vehicle fleet in a real-world scenario, as opposed to measuring emissions from a limited number of individual vehicles in a controlled environment in testing laboratories.

To conduct the study, the researchers set up their pollutant-measuring equipment at the entry and exit of the Kamshet-I tunnel located on the Mumbai-Pune Expressway. Along with exhaust emissions (resulting from incomplete combustion of fossil fuels), non-exhaust emissions (resulting from brake wear, tyre wear, road surface wear, and resuspension of road dust) were also collected. The traffic data was collected using high-definition video cameras and the vehicle registration numbers data (collected manually). The study collected data over two weeks.

The researchers identified super-emitters through manual inspection based on the video surveillance records of the traffic passing through the tunnel. Vehicles that emitted a visible plume of smoke or appeared to be overloaded were identified as super-emitters. It was also validated using the information on the age of the vehicles and type of emission technology: Bharat Stages (BS) - II, III, and IV (the study was conducted in 2019 when there were no BS VI vehicles) and the type of fuel (petrol, diesel, and CNG).

Monitoring equipment at the study location. Credit: Authors of the study

The researchers observed that the pollutant levels at the exit of the tunnel were significantly higher than those at the entry, and the tunnel exit captured the true signature of the vehicular emissions. While the traffic flow was the major determinant of pollutants at the exit, other surrounding factors influenced the pollutant levels at the entry, such as biomass burning from the neighbouring village. However, determining the difference in pollutant levels between the entry and the exit helped to effectively capture the impact of the traffic flow on the measured pollutant levels.

The IIT Bombay researchers estimated that super-emitters constituted an average of 21%(±3%) of the total vehicle fleet in the Kamshet-I tunnel, where 10%(±2%) of the fleet had a visible plume of smoke and 11%(±2%) were overloaded freight vehicles. The team developed a mathematical model to predict the share of super-emitters in any given real-world traffic in India by factoring in the shares of heavy-duty vehicles and light-duty vehicles, their respective ages, and fuel composition.

Old vehicles with engines that don’t comply with modern emission technologies and poor maintenance of relatively new vehicles could lead them to become potential super-emitters. Overloaded vehicles, especially heavy-duty vehicles, require additional fuel to power the vehicle,?leading to the release of higher pollutant emissions. Additionally, overloaded vehicles also cause higher non-exhaust emissions due to the higher road surface friction while moving. The Vehicle scrappage policy in India focuses on the scrapping of private and commercial petrol vehicles more than 15 years old and diesel vehicles more than 10 years old. However, the researchers did not find strict enforcement of these policies. Moreover, some of the relatively newer vehicles, likely due to poor maintenance, can lead to disproportionate pollution from a significant portion of vehicles in India.

The IIT Bombay study has highlighted the importance of enforcing strict regulations along with strengthening vehicle inspection and maintenance programs on India’s vehicle fleet with respect to super-emitters and their disproportionate release of pollutants. With over one-fifth of the vehicles in India being estimated to be potential super-emitters, it is high time the authorities take action. According to the Voluntary Vehicle Fleet Modernization Program (VVMP) published by the Ministry of Road Transport and Highways, the replacement of vehicles at the end of their lives will reduce vehicular pollution by 15-20%. However, this alone will not be sufficient because even a relatively new heavy-duty vehicle can be a super-emitter if loaded beyond its capacity or poorly maintained.

Recently, Nitin Gadkari, the Union Minister for Road Transport and Highways, has expressed an intention to completely phase out petrol and diesel vehicles and adopt alternatives, such as electric vehicles (EVs). The Union Government has created multiple incentives for both industries and consumers to promote the adoption of EVs in India.

“While the exhaust emissions can be controlled with the introduction of EVs, the non-exhaust emissions will still be of concern. There are still no emission standards for non-exhaust emissions in India,” concluded Ms Debbarma.

Article written by:	Balaram Vishnu Subramani
Image/ Graphic Credit:	Authors of the study
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Impact of real-world traffic and super-emitters on vehicular emissions under in…

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Wed, 07/24/2024 - 12:00

A much needed analytical study for a more sustainable waste disposal in the healthcare sector in India

pro — Tue, 25 Jun 2024 05:25:47 +0000

A much needed analytical study for a more sustainable waste disposal in the healthcare sector in India pro Tue, 06/25/2024 - 10:55

New study at IIT Bombay identifies factors essential for successful adoption of a circular economy model for healthcare waste management in India.

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In 2020, India produced 774 tons of biomedical waste per day. Additionally, large amounts of used, unused and infected medications, instruments, safety gear, and packaging materials are disposed of by individuals and healthcare centres. Safe disposal of healthcare waste is a concern as the special methods and technologies needed for it are not easily available. Public awareness and professional training regarding healthcare waste disposal is inadequate and funds for proper planning and implementation of effective waste management systems are not enough.

A ‘reduce-reuse-recycle’ approach, termed as circular economy model, helps avoid and mitigate pollution and environment damage which a ‘take-make-dispose’ approach is likely to cause. Though the effectiveness of the circular economy model is well-proven for efficient waste management and minimisation in the non-healthcare sector, it is not explored enough in the healthcare sector. Implementing it for healthcare waste management has its own challenges.

Dr. Anuj Dixit and Prof. Pankaj Dutta from the Shailesh J. Mehta School of Management, Indian Institute of Technology Bombay (IIT Bombay) carried out a study to identify the key factors for effective implementation of the circular economy model for healthcare waste management. Their research was published in the journal Clean Technologies and Environmental Policy.

The IIT Bombay researchers studied prior research related to the practices, factors and barriers in adopting circular economy models at different global locations in industries such as healthcare, medical devices, stainless-steel surgical instruments, plastic healthcare products and biomedical waste. Most of these were qualitative studies. “Various existing qualitative studies recommended the need for quantitative research within the healthcare sector to gain more insights into adopting circular economy in the domain,” explained Dr. Anuj Dixit while highlighting the need for analytical studies.

The researchers collected data about how the participants of the survey rate the importance of various factors such as awareness and training about waste management, budget, use of technology, waste segregation/collection, responsibilities of various stakeholders among others. This data was gathered through an objective questionnaire survey from medical practitioners and other professionals from 54 healthcare organisations in India. The organisations included hospitals, nursing homes, healthcare waste recycling units, pathological laboratories, and pharmaceutical companies in the private and public sectors operational for a minimum ten years with a minimum annual revenue of ?100 million, indicating growing organisations. “Our major challenge was to select appropriate health organisations according to their type and nature of healthcare waste,” Prof. Pankaj Dutta reported.

The researchers used a combination of well-established statistical techniques called ANOVA, F- DEMATEL and ISM, which gave qualitative as well as quantitative insights. Combination of these methods help prioritise contributing factors in a system, provide actionable insights and help decision-making in the face of uncertainty. The researchers believe that the conclusions drawn from this study offer a deeper, more structured, and analytically rigorous understanding of complex systems compared to simple surveys.

They identified 17 relevant and adequate factors called ‘critical success factors’ (CSFs) under five broad areas of impact—research and development, education and social behaviour, economic facets, responsibility, and tracking mechanism—called ‘implication dimensions’, critical to success of a circular economy model in healthcare waste management. The CSFs denote the actual activities to which the efforts can be allocated, and they include factors related to estimation, design, training, awareness, budget, responsibility and transparency to name a few.

Based on their analysis, the researchers further categorised the CSFs as causal and effect factors to offer better direction in planning for the implementation. Twelve CSFs were identified in the causal group, while the remaining five were in the effect group. The identified factors were also ranked depending on their impact intensity which can help in prioritising effort allocation during policy making.

Factors such as ‘government's responsibility’ and ‘stakeholders' participation’ were found to have the highest driving potential, whereas ‘segregation and collection’, though considered critical, were found to depend on other causal CSFs. ‘Information visibility and transparency’, ‘manufacturer/corporate responsibility’, ‘training and empowerment’ and ‘budget allocation’ were the factors found to impact healthcare waste management most.

Considering case-specific implication dimensions based on the goals of the policies, the efforts can be focused on the required factors. The research findings can help policymakers and Government bodies to create practical and feasible plans to enhance the success of the ongoing efforts for sustainable healthcare waste management.

The researchers believe that although the results obtained are specific to India, they can be useful for other developing economies as well. Including more experts and policy makers in the survey can broaden and strengthen the results.

“It is also important that when the circular economy model reaches a satisfactory level of success, the critical success factors must be re-evaluated,” concludes Prof. Pankaj Dutta.

Article written by:	Gubbi Labs
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Tue, 06/25/2024 - 12:00

Blood Proteins to detect Brain Tumours

pro — Fri, 22 Mar 2024 09:43:00 +0000

Blood Proteins to detect Brain Tumours pro Fri, 03/22/2024 - 15:13

Glioblastoma Multiforme (GBM) is the most aggressive of all grades of a type of brain tumour known as glioma, with less than one year of life expectancy. Detection of brain tumors at the early stages of the disease is a challenge and may improve treatment outcomes.?A recent research finds that it is possible to detect GBM by analysis of proteins in the blood serum.

Glioma brain tumors are caused due to an uncontrolled increase in certain cells known as ‘glial cells’. Gliomas form 80% of all brain and central nervous system tumours and 30% of malignant brain tumours. GBM (Glioblastoma Multiforme) is the fourth and final stage of Glioma. It is particularly aggressive and with presently available treatments, it is difficult to eradicate the uncontrolled growth of tumour cells, hence leading to early death.

While early detection may hold some hope, available diagnostic methods fall short. Imaging methods such as MRI are also unsatisfactory in early detection of gliomas. Tissue diagnosis is usually recommended at very advanced stage and may not always be feasible. Hence diagnosis through proteins in blood is being seriously explored for brain tumour detection.

Using proteins to detect diseases is part of Proteomics, a discipline for large scale study of proteins. Proteomics has a role not only in disease detection but also may have role in disease treatment since many diseases are caused due to malfunctioning proteins. However, the challenge is to identify few proteins out of thousands of proteins that are differently expressed in diseased subjects Advanced analytical techniques such as mass spectrometry and protein microarrays are used to study thousands of proteins in a given experiment.

The study led by Dr. Sanjeeva Srivastava of the Biosciences Department of IIT Bombay, jointly with Tata Memorial Centre, National Centre for Cell Science, and Strand Life Sciences,?conducted an experiment comparing blood samples of healthy subjects, with blood samples of GBM patients. The researchers found almost 55 differently expressed proteins in GBM patients. Of these 4 proteins are more important because of their contribution to tumour growth. The researchers also found increased cholesterol level, triglyceride levels and low density lipo proteins in blood samples of GBM patients.

This research represents an advance in method of detection of GBM. Early detection may even result in better treatment and hence better outcome. Of course, it must be remembered that GBM is the fourth stage of Glioma, and this research is part of bigger research to identify proteins at various stages of Glioma so as to lead to detection at even earlier stage and hence better treatment. In a collaborative research with Johns Hopkins Medical and IIT Bombay, Dr. Srivastava’s group is using protein chips containing 17,000 human proteins (~ 40,000 features) for the identification of protein autoantibody markers from blood serum for the early detection of brain tumors.

However it could take some time for this advance to reach consumer stage. Dr. Sanjeeva Srivastava, lead researcher of the study from IIT Bombay informs, “There are various stages for such research to reach clinical stage, where it contributes to human welfare. The first step is discovery stage, where one discovers the proteins which are differently expressed in a certain disease. After this there is the validation stage where the discovery is validated. It is only after validation that diagnostic advances can reach the clinical stage.”

IIT Bombay will be hosting 6th Annual Meeting of Proteomics Society of India and International Conference and workshops from 6th to 11th December 2014.

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Proteomics, 2012 (DOI)

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Tue, 01/31/2023 - 12:00