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Hedging against air pollution using an option pricing model based on a fine particulate matter index
Some enterprises have been facing long-term operational risks caused by air pollution. By designing an option contract based on a fine particulate...
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Overview of Uncertainty Propagation Methods
This section presents, first, a summarized overview of approaches and concepts, before going into specific methods later in more...
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Fully Bayesian economically optimal design for a spatially varying coefficient linear stochastic plateau model over multiple years
On-farm experimentation to guide fertilizer recommendations is a potential precision agriculture tool. There is, however, no agreement on the optimal...
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Global autocorrelation test based on the Monte Carlo method and impacts of eliminating nonstationary components on the global autocorrelation test
Autocorrelation and non-stationarity are always concerned in analysis of meteorological and hydrological time series. Current commonly used methods,...
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Environmental Distribution and Modelling of Radioactive Lead (210): A Monte Carlo Simulation Application
The abundance of lead element with an atomic number 82 is 1.03 × 10−8 % in the Solar System, 14 mg kg−1 in the Earth’s surface and 3 × 10−5 mg L−1 in...
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Relevance of charge interactions for contaminant transport in heterogeneous formations: a stochastic analysis
The electrostatic properties of clay (or other charged) mineral surfaces play a significant role in the fate, transport, persistence, and remediation...
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Health risk assessment of heavy metal pollutants in Iranian hen eggs: a systematic review and meta-analysis
Eggs are a high-quality, nutrient-dense source of protein that is available at a relatively low price and the contamination of eggs by heavy metals...
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Health risk assessment of heavy metals in cosmetic products sold in Iran: the Monte Carlo simulation
Cosmetics can contain harmful compounds such as heavy metals. Several metals have a cumulative effect on the body, especially fatty tissues, and may...
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Optimal design of groundwater pollution monitoring network based on a back-propagation neural network surrogate model and grey wolf optimizer algorithm under uncertainty
In the optimal design of groundwater pollution monitoring network (GPMN), the uncertainty of the simulation model always affects the reliability of...
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Exploring soil radon (Rn) concentrations and their connection to geological and meteorological factors
The relationship between soil radon and meteorological parameters in a region can provide insight into natural processes occurring between the...
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Analysis of the effect of inputs uncertainty on riverine water temperature predictions with a Markov chain Monte Carlo (MCMC) algorithm
Water temperature is a key characteristic defining chemical, physical, and biologic conditions in riverine systems. Models of riverine water quality...
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Decoding the state of stress and fluid pathways along the Andean Southern Volcanic Zone
Decoding means decrypting a hidden message. Here, the encrypted messages are the state of stress, fluid pathways, and volcano tectonic processes...
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EIA and Uncertainty Management
This chapter looks at the topics of environmental impact assessment (EIA) and handling uncertainty. Key aspects of an EIA are explained including...
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Minimizing the exposure risk from groundwater pollution by optimizing the temporal extraction patterns
Optimization models for minimizing pollutant exposure from groundwater resources require time and resources that many communities might not have...
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Can an ecological scarcity method for Germany support robust decisions? – analysing the effect of uncertain target values on the impact assessment of energy generation technologies
PurposePotentially contradictory indicators in Life Cycle Assessment cause ambiguity and thus uncertainty regarding the interpretation of results....
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Health risk assessment of total petroleum hydrocarbons and heavy metals in groundwater and soils in petrochemical pipelines
Petrochemical pipelines contain many organic compounds that their leakage may bring about both soil and water contamination. This study aimed to...
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An integrated data analysis and machine learning approach to track and monitor SARS-CoV-2 in wastewater treatment plants
Wastewater-based epidemiology (WBE) programs are cost-effective for continuously monitoring infections, including SARS-CoV-2. This work proposes...
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Before the Dam: A Fish-Mercury Contamination Baseline Survey at the **ngu River, Amazon Basin Before the Belo Monte Dam
In the last decades, mega-diverse rivers worldwide (e.g., the Amazon and their tributaries) have experienced several human-driven transformations,...
