Spatially resolved environmental fate models: A review

Falakdin, Parisa; Terzaghi, Elisa; Guardo, Antonio Di

doi:10.1016/j.chemosphere.2021.133394

Cited by 13 publications

(4 citation statements)

References 172 publications

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“…For such worst case

and ENM deposition estimations, there is no need to estimate the exact ENM spatial distribution in the regional scale. However, if one aims at realistic prediction of ENM spatial distribution [ 73 ], one needs to consider a number of sources with arbitrary spatial distribution in the regional scale. If such atmospheric emission data from individual sources becomes available, the multiple source situation could be taken into account by placing and modeling multiple local point sources in the bigger regional scale.…”

Section: Discussionmentioning

confidence: 99%

Local Scale Exposure and Fate of Engineered Nanomaterials

Poikkimäki

Quik

Säämänen

et al. 2022

Toxics

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Nanotechnology is a growing megatrend in industrial production and innovations. Many applications utilize engineered nanomaterials (ENMs) that are potentially released into the atmospheric environment, e.g., via direct stack emissions from production facilities. Limited information exists on adverse effects such ENM releases may have on human health and the environment. Previous exposure modeling approaches have focused on large regional compartments, into which the released ENMs are evenly mixed. However, due to the localization of the ENM release and removal processes, potentially higher airborne concentrations and deposition fluxes are obtained around the production facilities. Therefore, we compare the ENM concentrations from a dispersion model to those from the uniformly mixed compartment approach. For realistic release scenarios, we based the modeling on the case study measurement data from two TiO2 nanomaterial handling facilities. In addition, we calculated the distances, at which 50% of the ENMs are deposited, serving as a physically relevant metric to separate the local scale from the regional scale, thus indicating the size of the high exposure and risk region near the facility. As a result, we suggest a local scale compartment to be implemented in the multicompartment nanomaterial exposure models. We also present a computational tool for local exposure assessment that could be included to regulatory guidance and existing risk governance networks.

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“…For such worst case

Section: Discussionmentioning

confidence: 99%

Local Scale Exposure and Fate of Engineered Nanomaterials

Poikkimäki

Quik

Säämänen

et al. 2022

Toxics

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“…Recently models have been developed that bring together the advantages of detailed spatially explicit catchment models and multimedia models into a single modeling framework, as shown in Figure 7 , and reviewed by Falakdin et al. ( 2022 ). This permits not only the prediction of realistic local concentrations but can also provide a starting point for the quantification of far‐field aggregate human exposure (e.g., produce, surface water, fish, meat, milk) and incorporate the role of persistence for evaluating reservoir stocks of CEC in various environmental compartments (Wannaz, Franco, et al., 2018 ).…”

Section: The Challenge Of Numerous and Ubiquitous Cecs: The Role Of M...mentioning

confidence: 99%

Water, Water Everywhere, but Every Drop Unique: Challenges in the Science to Understand the Role of Contaminants of Emerging Concern in the Management of Drinking Water Supplies

Glassmeyer,

Burns,

Focazio

et al. 2023

GeoHealth

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The protection and management of water resources continues to be challenged by multiple and ongoing factors such as shifts in demographic, social, economic, and public health requirements. Physical limitations placed on access to potable supplies include natural and human‐caused factors such as aquifer depletion, aging infrastructure, saltwater intrusion, floods, and drought. These factors, although varying in magnitude, spatial extent, and timing, can exacerbate the potential for contaminants of concern (CECs) to be present in sources of drinking water, infrastructure, premise plumbing and associated tap water. This monograph examines how current and emerging scientific efforts and technologies increase our understanding of the range of CECs and drinking water issues facing current and future populations. It is not intended to be read in one sitting, but is instead a starting point for scientists wanting to learn more about the issues surrounding CECs. This text discusses the topical evolution CECs over time (Section 1), improvements in measuring chemical and microbial CECs, through both analysis of concentration and toxicity (Section 2) and modeling CEC exposure and fate (Section 3), forms of treatment effective at removing chemical and microbial CECs (Section 4), and potential for human health impacts from exposure to CECs (Section 5). The paper concludes with how changes to water quantity, both scarcity and surpluses, could affect water quality (Section 6). Taken together, these sections document the past 25 years of CEC research and the regulatory response to these contaminants, the current work to identify and monitor CECs and mitigate exposure, and the challenges facing the future.

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“…Following the disposal of any pollutant into the environment, it is important to know its fate and transport characteristics, as well as its distribution between all the environmental compartments. The recourse of dispersion, transport and distribution models has become a very useful strategy and many different models have been proposed in the last decades, since the seminal work of MacKay and co-workers [6][7][8]. In the case of pharmaceutical drugs, the discharges are usually done on surface waters and the models designed to follow and predict their fate and dispersion have to take into account, not only the physical phenomena related to the dispersion (mass transport within the solution, sorption on soils, sediments, colloids and biota, evaporation from water or soil to air, etc), but also the chemical phenomena (photo-degradation, biodegradation and hydrolysis) that may transform the original compounds into new ones with different properties [3,9,10].…”

Section: Introductionmentioning

confidence: 99%