Modeling and predicting fecal coliform bacteria levels in oyster harvest waters along Louisiana Gulf coast

Wang, Jiao; Deng, Zhiqiang

doi:10.1016/j.ecolind.2019.01.013

Cited by 22 publications

(7 citation statements)

References 37 publications

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“…In this study, the FC concentration in the Beiyun River responded more actively to a combination of environmental factors, indicating that multiple environmental factors should be used to explain FC levels in water bodies. This result is consistent with previous studies (Thoe et al, 2014;Leight et al, 2016;Badgley et al, 2019;Wang and Deng, 2019). However, the temporal dynamics of FC in P3 failed due to other complex anthropogenic influences in the urban areas, particularly from the point source input.…”

Section: Environmental Factors Affecting Fc Concentration In Differensupporting

confidence: 93%

“…The National Health and Medical Research Council of Australia and the European Environment Agency (EEA) both use FC as one of the microbiological indicators of drinking water quality. The FC index is particularly important especially in areas where marine products are abundant (Wang and Deng, 2019). Previous studies have reported two significant observations of the worldwide FC situation.…”

Section: Introductionmentioning

confidence: 99%

“…Regression models can be applied to explore how one environmental factor affects FC levels while the remaining factors are fixed; however, it usually has poor fitness. This result may be due to the complicated and nonlinear relationship between environmental factors and FC (Fan et al, 2015;Tong et al, 2016;Wang and Deng, 2019). Several additional studies have investigated the link between land-use types and FC concentration, including urban development levels, agriculture-dominated watersheds and comparisons of different watershed types (Sliva, 2001;Walters et al, 2011;Chow et al, 2013;Mcmichael et al, 2013;Badgley et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal variability and key influencing factors of river fecal coliform within a typical complex watershed

et al. 2020

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a b s t r a c tFecal coliform bacteria are a key indicator of human health risks; however, the spatiotemporal variability and key influencing factors of river fecal coliform have yet to be explored in a rural-suburban-urban watershed with multiple land uses. In this study, the fecal coliform concentrations in 21 river sections were monitored for 20 months, and 441 samples were analyzed. Multivariable regressions were used to evaluate the spatiotemporal dynamics of fecal coliform. The results showed that spatial differences were mainly dominated by urbanization level, and environmental factors could explain the temporal dynamics of fecal coliform in different urban patterns except in areas with high urbanization levels. Reducing suspended solids is a direct way to manage fecal coliform in the Beiyun River when the natural factors are difficulty to change, such as temperature and solar radiation. The export of fecal coliform from urban areas showed a quick and sensitive response to rainfall events and increased dozens of times in the short term. Landscape patterns, such as the fragmentation of impervious surfaces and the overall landscape, were identified as key factors influencing urban non-point source bacteria. The results obtained from this study will provide insight into the management of river fecal pollution.

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Section: Environmental Factors Affecting Fc Concentration In Differensupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal variability and key influencing factors of river fecal coliform within a typical complex watershed

et al. 2020

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“…An accurate battery model is conducive to better battery management which allows full use to be made of the battery's performance. In accordance with the model mechanism, battery models can be divided into: electrochemical models, equivalent circuit models, neural network models and so on [34]. The model established according to the chemical reaction mechanism of the battery is called the electrochemical model, and this can accurately simulate the main characteristics of the battery.…”

Section: Energy Loss Modelmentioning

confidence: 99%

Adaptive Cruise Control Strategy for Electric Vehicles Considering Battery Degradation Characteristics

et al. 2023

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This paper proposes an economic adaptive cruise controller (EACC) that considers battery aging characteristics based on adaptive model predictive control (AMPC). By establishing a battery capacity decay model based on experimental data, the capacity loss during vehicle operation is determined, and the parameters in the equivalent circuit model are updated according to the actual capacity of the battery. The controller uses indicators that characterize driving safety, tracking performance, comfort, and economy. The economic indicator is the decrease in the value of the battery capacity. Fuzzy weight allocation is designed based on the host vehicle’s speed and the workshop’s relative distance to adjust the weight between different indicators under different working conditions. Additionally, the proposed controller is compared with other traditional controllers under different working conditions, cycle times, and battery state of health (SOH). The simulation results indicate that, under various battery SOH conditions, the performance of the controller which considers battery capacity degradation characteristics is better than that of traditional controllers. Moreover, the fixed-weight controller performs better when following a vehicle at medium and low speeds. Finally, the proposed strategy was validated through hardware-in-the-loop testing, demonstrating its ability to meet the real-time requirements of the system.

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“…The amount of coliform in the environment is influenced by many factors, including rainfall and turbidity. Adequate food availability can help coliforms reproduce and grow to form colonies in a dark, warm, and humid environment (Wang and Deng, 2019). Coliform bacteria can be divided into two groups: fecal coliform and non-fecal coliform.…”

Section: Introductionmentioning

confidence: 99%

Microbiological Analysis of Drinking Water Sourcing from the Spring of Joben Pesanggrahan, Montong Gading, East Lombok

Jupri¹,

Vofi²,

Faturrahman³

et al. 2023

AAVS

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Water is an essential component for humans, mainly used as drinking water. There are still many people in Indonesia who use springs as a source of drinking water, one of which is in Joben, Pesanggrahan Village, Montong Gading District, East Lombok Regency. Drinking water from springs can be polluted by contaminants such as bacteria, viruses and others during storage and distribution. This study aims to analyze the quality and microbiological feasibility of drinking water sourced from Joben Springs, Montong Gading, East Lombok. The research was carried out in May-June 2021. The research method used was purposive sampling with sampling carried out at three points: the spring, the main reservoir, and the residents' reservoir. The Coliform test was carried out using the Most Probable Number (MPN) method and Escherichia coli (E. coli) identification using Kirby Bauer. The results of this study indicate that the coliform MPN test from the spring sample obtained the highest value in the paddy field, spring, and house sample of 4,050/100 ml and was classified as class E clean water. Moreover, it was very poor water; the lowest was in mountain storage water of 390/100 ml, which was classified as water clean class C bad category. Water from the Joben spring is not suitable for direct consumption by the community, so it needs to be boiled first to kill bacteria and minimize health problems. All samples, there were no coliform bacteria of the E. coli group. The bacteria in all samples were bacteria from other coliform groups. Therefore, further analysis is needed to determine the content of other bacteria in the water at the Joben spring, Pesanggrahan Montong Gading, East Lombok.

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Modeling and predicting fecal coliform bacteria levels in oyster harvest waters along Louisiana Gulf coast

Cited by 22 publications

References 37 publications

Spatiotemporal variability and key influencing factors of river fecal coliform within a typical complex watershed

Spatiotemporal variability and key influencing factors of river fecal coliform within a typical complex watershed

Adaptive Cruise Control Strategy for Electric Vehicles Considering Battery Degradation Characteristics

Microbiological Analysis of Drinking Water Sourcing from the Spring of Joben Pesanggrahan, Montong Gading, East Lombok

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