My research focuses on understanding the fundamental chemistry of natural and engineered systems using a combination of laboratory, field, and computer-based modeling studies for a sustainable future. Specifically, I am interested in understanding the effects of natural and anthropogenic activities on the fate of pollutants, and the mechanistic insights into the chemical, physical and biological fate of synthetic contaminants in the environment. Currently, I am interested in three main research topics: (i) natural organic matter bulk, molecular, photochemical, and photophysical characterization, (ii) application of instrumentation and chemistry principles to identify and understand the fate of synthetic contaminants in natural environmental compartments and engineered systems, and (iii) using cheminformatics and artificial intelligence and/or machine learning to develop reaction pathways and kinetic models, perform network generation and property estimation of synthetic contaminants in natural and engineered systems. This knowledge can help us predict the fate of contaminants in the environment, and design mitigation strategies and treatment processes to prevent potential risks and inform decision-making. Each of these projects has been discussed in detail below.

Man-made contaminants, natural organic matter, and other organic constituents co-exist in environmental compartments. Recent research has indicated that the annual production and release of synthetic organic compounds (SOCs), including synthetic polymeric materials, pesticides, personal care products, pharmaceuticals, and other industrial chemicals, has outpaced the global capacity of assessment and monitoring. In aquatic environments, the transformation and fate of contaminants are majorly controlled by the constituents and the chemistry of the water body. Dissolved organic matter (DOM) is a major constituent in aquatic systems that influences aquatic chemistry and plays a major role in the degradation of contaminants. The first part of my research employs molecular characterization and other analytical chemistry techniques to characterize and screen environmental samples.  Specific objectives under this research will involve but not be limited to; (i) screening for the occurrence of man-made contaminants in environmental samples, (ii) understanding the role of natural, anthropogenic activities, and disasters in the transformation and fate of environmental contaminants and natural organic matter, (iii) fate and transformation of man-made contaminants, and organic matter in engineered systems, (iv) understanding the process of formation and transformation of DOM in terrestrial and aquatic systems with contribution from natural abiotic and biotic transformation processes, (v) understanding the role of DOM from different sources and transformation processes in the transformation of man-made organic pollutants, and (vii) microheterogeneous distribution of reactive intermediates in DOM, etc. The research output from this aim plus data curated from online databases and literature will be used in research goal 2 to develop models and solutions based on real-world samples and experiments. Laboratory and field-controlled experiments will always help us generate high-fidelity data for testing computational hypotheses and validating predictions for our computer-based models. 

Tremendous amounts of data about environmental chemical reactions have been collected and have informed us about the fate of several contaminants. However, it remains a challenge to use this information to accurately produce robust and computer-based models that can inform us about the reaction kinetics, reaction mechanisms, and physicochemical and molecular properties of contaminants under different environmental conditions. With the recent advances in computational and analytical chemistry, it is possible to understand challenging chemical problems, such as analyzing complex reaction networks, generation of rate constants, and property estimation. This research will focus on advancing the development of computer-based models that can inform the transformation and fate of contaminants. The long-term goal of this research is but not limited to; (i) accelerating the application of AI-driven approaches to understanding the transformation and fate of contaminants, and (ii) increasing and promoting the use of computer-based models in the scientific community to understand the fate of environmental contaminants. Some of the specific objectives under this research will include (i) develop and apply tools that can improve data curation, cleaning, transformation  and feature selection through molecular/ feature representations using methods like generative de novo models,  molecular fingerprints and descriptors, group contribution and graph representations etc., (ii) using molecular representations to evaluate existing and develop new automated computer-based models to perform reaction kinetics and mechanisms modeling, (iii) using experimentally collected data, online databases and literature to develop, test, and disseminate machine learning/ quantitative structure–property/activity/toxicity relationship (QSPR/QSAR/QSTR) models that can be used to estimate the molecular, physical, chemical, and thermodynamic  properties of contaminants and their transformational products  in the environment and engineered systems, (iv) reaction classification, reaction condition recommendation and optimization for both engineered and natural systems,  and (v) improving the supervised and exploratory use of machine learning in environmental chemistry through  improving robustness, interpretability, and performance optimization.

Dissolved organic matter (DOM) is a critical component of aquatic systems that serves  many purposes. Among them is the production of reactive intermediates when irradiated. Examples of RIs produced when DOM is irradiated include the excited triplet states of dissolved organic matter (3DOM*), singlet oxygen (1O2), hydroxyl radicals (·OH), carbonate radicals, and halide radicals all of which contribute to the degradation of environmental contaminants and disinfection of pathogens. It is therefore critical to understand how the cycling, transformation, and composition of DOM may affect the production of reactive intermediates in aquatic systems. The DOM’s ability to produce RIs was studied using probe compounds that have been well-studied and established as methods for the quantification of RIs. These probe compounds included terephthalic acid (TPA) for •OH, furfuryl alcohol (FFA) for 1O2, 2,4,6-trimethylphenol (TMP) as an electron transfer probe for 3DOM* (), and trans,trans-2,4-hexadien-1-ol (t,t-HDO or sorbic alcohol) as an energy transfer probe for 3DOM*. Overall, this dissertation contributes to the growing knowledge about the photochemical reactivity of DOM in aquatic systems. It advances our understanding of the roles of several natural and anthropogenically influenced activities toward the photochemical reactivity of DOM. 

See the publications page for results from this study.

In 2017 while planning a trip to Uganda to visit my family, I had an idea that I could use the opportunity to contribute to the scientific knowledge base in Africa. There is a big research gap between Africa and the developed world, yet Africa faces tremendous environmental challenges. Uganda has antiquated wastewater treatment and disposal facilities which have resulted in the contamination of the environment. I decided to carry out a study aimed at understanding the current occurrence and distribution of organic micropollutants (OMPs) in drinking water sources, wastewater treatment plants as well as waterways of Kampala. I wrote a proposal and obtained funding to carry out sampling in Uganda. I initiated and led this collaborative study between Syracuse University and Makerere University in Uganda. Our results prioritized and confirmed 157 OMPs in Kampala samples for target quantification. Many OMPs detected in Kampala samples occurred within concentration ranges similar to those documented in previous studies reporting OMP occurrence in sub-Saharan Africa (SSA), but some have never or rarely been quantified in environmental water samples from SSA. This work has been published as a peer-reviewed journal article and it is the first larger study to evaluate the spatial and temporal distribution of organic micropollutants in a major city in sub-Saharan Africa. 

See the publications page for results from this study.

This research aimed at assessing the use of fluorescence spectroscopy as a real time surveillance tool in advanced water reuse operations. I evaluated how temperature changes affects the in-situ fluorescence sensors deployed in water, wastewater, and water reuse operations, and suggested correction protocols to compensate sensor performance for temperature fluctuation.  I also I evaluated and compared the potential of both in situ and 3D benchtop fluorescence equipment to monitor contaminants in water, wastewater, and water reuse operation. Another section of this study focused on evaluating the suitability of fluorescence spectroscopy as a tool to monitor membrane fouling during ultrafiltration as well as understanding changes in dissolved organic matter (DOM) bulk properties during the process. Overall, this work demonstrated the potential application of fluorescence spectroscopy to monitor contaminants in advanced water treatment and reuse facilities and developing in situ, quick, and robust contaminant sensors. Fluorescence sensors could serve as an early warning system for source water protection in water operations.

See the publicatiosn page for results from this study.