Deciphering the water quality impacts of COVID-19 human mobility shifts in estuaries surrounding New York City

Sherman, Jonathan; Tzortziou, M.; Turner, Kyle J.; Greenfield, Dianne I.; Menendez, Alana

doi:10.1016/j.scitotenv.2023.164953

Cited by 3 publications

(1 citation statement)

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“…The estuary is also characterized by long water residence time (2–3 months) that allows sufficient DOM processing within the system (Tamborski et al., 2020; Vlahos & Whitney, 2017). Over the past six years (period of this study), LIS was hit by 20 storms, experienced dramatic changes in human mobility and air quality during the COVID‐19 lockdowns (Sherman, Tzortziou, Turner, Greenfield, & Menendez, 2023; Tzortziou et al., 2022), and continued to be impaired with seasonally recurring hypoxia and harmful algal blooms despite strict regulations in nutrient loads and air quality (Connecticut Department of Energy and Environmental Protection, 2021).…”

Section: Methodsmentioning

confidence: 99%

Impacts of Hydrology and Extreme Events on Dissolved Organic Carbon Dynamics in a Heavily Urbanized Estuary and Its Major Tributaries: A View From Space

Cao,

Tzortziou

2024

JGR Biogeosciences

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Dissolved organic matter and its colored component, Colored Dissolved Organic Matter (CDOM), play a major role in global carbon budgets, and their fluxes provide an essential link between terrestrial and aquatic biogeochemical cycles. Satellite observations can uniquely capture the hydro‐biogeochemical connectivity of terrestrial and aquatic landscapes, across scales. Yet, accurate satellite retrievals of CDOM and dissolved organic carbon (DOC) dynamics remain challenging in urbanized estuaries and coasts. Here, we present an advanced unified algorithm for space‐based retrieval of coastal CDOM and DOC dynamics and its application in Long Island Sound—one of the world's most heavily urbanized estuaries that is becoming increasingly vulnerable to climate change stressors. A rich bio‐optical data set, encompassing a wide range of environmental conditions, was integrated into the algorithm training to retrieve DOC concentrations and CDOM spectral shape (i.e., spectral slope S275–295)—a proxy for DOC quality. The new algorithms were applied to full‐resolution satellite imagery from the Sentinel‐3 Ocean and Land Color Instrument (OLCI) after thoroughly evaluating the performance of six ocean color atmospheric correction approaches (ACOLITE, BAC, C2RCC, MUMM, l2gen, and Polymer). Evaluation of the algorithms yielded mean absolute percent differences of 28%, 12%, and 10% for aCDOM(300), S275–295, and DOC, respectively. Application of the algorithms to multi‐year satellite OLCI imagery captured, for the first time, the coupled impact of seasonal transitions, wind regimes, freshwater inputs, anthropogenic disturbances, and hydrological extremes (both intense precipitation and droughts) on DOC fluxes and CDOM quality at the ecosystem scale. Results have important implications for improved predictions of coastal biogeochemical fluxes in complex urban−estuary systems.

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Section: Methodsmentioning

confidence: 99%

Impacts of Hydrology and Extreme Events on Dissolved Organic Carbon Dynamics in a Heavily Urbanized Estuary and Its Major Tributaries: A View From Space

Cao,

Tzortziou

2024

JGR Biogeosciences

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Driving factors of colored dissolved organic matter dynamics across a complex urbanized estuary

Menendez,

Tzortziou

2024

Science of The Total Environment

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Predicting High-Risk Individuals in Disease Outbreaks Using Fuzzy Logic-Based Contact Tracing Model.

Aklah,

Al-Safi,

Abdali

2023

Preprint

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Contact tracing plays a crucial role in identifying exposed individuals at high risk of infection during disease outbreaks. In this paper, we propose a fuzzy logic-based contact tracing model for predicting high-risk exposed individuals in disease outbreaks. The model utilizes various input parameters, including distance, overlap time, visiting time lag, incubation time, and facility size, to assess the risk of infection. Through the application of fuzzy logic, the model enables the modeling of complex relationships and uncertainties associated with these input parameters. We evaluated the model using simulated data, demonstrating its effectiveness in identifying individuals at different levels of risk. The evaluation includes partial input evaluation, and comprehensive inputs assessment to assess the impact of each parameter on the risk of infection. The results highlight the importance of considering multiple factors in contact tracing and provide insights into the key parameters that significantly influence the risk assessment. The proposed model has the potential to assist public health authorities in making informed decisions and implementing targeted interventions to mitigate the spread of diseases in outbreak situations. Moreover, it helps to alleviate unnecessary fear among individuals who are less likely to have been infected.

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Deciphering the water quality impacts of COVID-19 human mobility shifts in estuaries surrounding New York City

Cited by 3 publications

References 40 publications

Impacts of Hydrology and Extreme Events on Dissolved Organic Carbon Dynamics in a Heavily Urbanized Estuary and Its Major Tributaries: A View From Space

Impacts of Hydrology and Extreme Events on Dissolved Organic Carbon Dynamics in a Heavily Urbanized Estuary and Its Major Tributaries: A View From Space

Driving factors of colored dissolved organic matter dynamics across a complex urbanized estuary

Predicting High-Risk Individuals in Disease Outbreaks Using Fuzzy Logic-Based Contact Tracing Model.

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