Special Issue "Models for the Simulation of Chemistry, Climate, and Pollutant Dispersion in Indoor Environments and Atmospheric Near-Source Plumes"

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Environmental Science and Engineering".

Deadline for manuscript submissions: 30 November 2020.

Special Issue Editors

Dr. Matthias Karl
Website
Guest Editor
Helmholtz-Zentrum Geesthacht - Zentrum für Material- und Küstenforschung GmbH, Department for Chemistry Transport Modelling, Geesthacht, Germany
Interests: modelling of chemistry and transport of atmospheric pollutants, urban air quality and development of emission control scenarios, particle emissions from mobile transport sources, transformation of particles in the atmosphere via aerosol dynamics and chemical processes
Prof. Dr. Allan Gross
Website
Guest Editor
Aarhus University, Department of Business Development and Technology, Herning, Denmark
Interests: environmental research (atmospheric chemistry, microplastic, vehicle emission estimations using smart phones), optimization of multi process chemical systems

Special Issue Information

Dear Colleagues,

Indoor Air Pollution (IAP) is responsible for many health and environmental issues that disproportionately and adversely affect humans around the world. IAP comes from a variety of sources and includes a wide range of particles, gases, chemicals, and other substances. Pollutant sources in indoor living environments, among others, include indoor combustion sources (wood stoves, tobacco, and candles), emissions from building materials and furnishings, wall paint, household cleaning products, and electronic devices.

Infiltration of polluted outdoor air is an important contributor to the indoor exposure. Increased traffic emissions cause high outdoor pollution levels in cities. Near-source pollutant plumes can cause serious health impacts close to sources in urban environments, for example, in a street canyon with high traffic volumes, in the neighborhood of port areas, or near industrial production sites.

The evaluation of health risks in indoor environments is limited by the complexity of the chemical interactions between pollutants, the ventilation and dispersion of pollutants, and the environmental factors that determine indoor climate. Outdoor air used for ventilation of buildings contains high levels of pollutants. While ventilation systems effectively can filter pollen and large particles, the filtration of smaller particles remains a challenge. Thus, the smaller particles can enter into buildings through the ventilation systems and contribute the particle concentrations together with indoor primary and secondary particles. Moreover, infiltration of outdoor pollutants can trigger reactions indoors that may lead to products that are more odorous or harmful than the primary pollutants.

Mathematical models can help to assess the significance of processes and to gain a better understanding of indoor sources and pathways of exposure, relations between indoor and outdoor pollutant levels, and the dependencies of pollutant abundances on environmental factors and climate variables. Hence, modelling is a practical tool to understand the impact that chemical compounds have on indoor/outdoor air pollution and climate.

The focus of this Special Issue is on model applications related to chemistry, climate, and dispersion in indoor environments and near-source outdoor environments. The Special Issue covers model studies dealing with one or more aspects causing the modification of the physical and chemical properties of the atmosphere in urbanized areas. The application of models is crucial for the development of mitigation strategies such as source control, ventilation removal, exposure control, and air cleaning technologies.

We welcome scientific research papers and review articles that address chemical processes, particle emission and transformation, as well as climatic conditions in indoor environments or in atmospheric near-source pollution plumes by using computational models. Modelling of the urban heat island effect in relation to the incidence of thermal discomfort on the human cardiovascular and respiratory systems is also welcome.

All submitted papers should link results from their modelling studies to relevant impact on exposures and human health.

Dr. Matthias Karl
Prof. Dr. Allan Gross
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2300 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Indoor Air Pollution (IAP)
  • pollution plume
  • process-oriented modelling
  • Computational Fluid Dynamics (CFD) modeling
  • occupational health
  • indoor exposure
  • hazardous chemicals
  • gas-phase chemistry
  • heterogeneous chemistry
  • particle emission
  • urban heat island

Published Papers (6 papers)

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Research

Open AccessArticle
Impact of Air Conditioning Systems on the Outdoor Thermal Environment during Summer in Berlin, Germany
Int. J. Environ. Res. Public Health 2020, 17(13), 4645; https://doi.org/10.3390/ijerph17134645 - 28 Jun 2020
Abstract
This study investigates the effect of anthropogenic heat emissions from air conditioning systems (AC) on air temperature and AC energy consumption in Berlin, Germany. We conduct simulations applying the model system CCLM/DCEP-BEM, a coupled system of the mesoscale climate model COSMO-CLM (CCLM) and [...] Read more.
This study investigates the effect of anthropogenic heat emissions from air conditioning systems (AC) on air temperature and AC energy consumption in Berlin, Germany. We conduct simulations applying the model system CCLM/DCEP-BEM, a coupled system of the mesoscale climate model COSMO-CLM (CCLM) and the urban Double Canyon Effect Parameterization scheme with a building energy model (DCEP-BEM), for a summer period of 2018. The DCEP-BEM model is designed to explicitly compute the anthropogenic heat emissions from urban buildings and the heat flux transfer between buildings and the atmosphere. We investigate two locations where the AC outdoor units are installed: either on the wall of a building (VerAC) or on the rooftop of a building (HorAC). AC waste heat emissions considerably increase the near-surface air temperature. Compared to a reference scenario without AC systems, the VerAC scenario with a target indoor temperature of 22 C results in a temperature increase of up to 0.6 K . The increase is more pronounced during the night and for urban areas. The effect of HorAC on air temperature is overall smaller than in VerAC. With the target indoor temperature of 22 C , an urban site’s daily average AC energy consumption per floor area of a room is 9.1 W   m 2 , which is 35% more than that of a suburban site. This energy-saving results from the urban heat island effect and different building parameters between both sits. The maximum AC energy consumption occurs in the afternoon. When the target indoor temperature rises, the AC energy consumption decreases at a rate of about 16% per 2 K change in indoor temperature. The nighttime near-surface temperature in VerAC scenarios shows a declining trend ( 0.06 K per 2 K change) with increasing target indoor temperature. This feature is not obvious in HorAC scenarios which further confirms that HorAC has a smaller impact on near-surface air temperature. Full article
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Open AccessArticle
Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO2 and PM2.5 Pollution in Urban Areas
Int. J. Environ. Res. Public Health 2020, 17(6), 2099; https://doi.org/10.3390/ijerph17062099 - 22 Mar 2020
Cited by 5
Abstract
To evaluate the effectiveness of alternative policies and measures to reduce air pollution effects on urban citizen’s health, population exposure assessments are needed. Due to road traffic emissions being a major source of emissions and exposure in European cities, it is necessary to [...] Read more.
To evaluate the effectiveness of alternative policies and measures to reduce air pollution effects on urban citizen’s health, population exposure assessments are needed. Due to road traffic emissions being a major source of emissions and exposure in European cities, it is necessary to account for differentiated transport environments in population dynamics for exposure studies. In this study, we applied a modelling system to evaluate population exposure in the urban area of Hamburg in 2016. The modeling system consists of an urban-scale chemistry transport model to account for ambient air pollutant concentrations and a dynamic time-microenvironment-activity (TMA) approach, which accounts for population dynamics in different environments as well as for infiltration of outdoor to indoor air pollution. We integrated different modes of transport in the TMA approach to improve population exposure assessments in transport environments. The newly developed approach reports 12% more total exposure to NO2 and 19% more to PM2.5 compared with exposure estimates based on residential addresses. During the time people spend in different transport environments, the in-car environment contributes with 40% and 33% to the annual sum of exposure to NO2 and PM2.5, in the walking environment with 26% and 30%, in the cycling environment with 15% and 17% and other environments (buses, subway, suburban, and regional trains) with less than 10% respectively. The relative contribution of road traffic emissions to population exposure is highest in the in-car environment (57% for NO2 and 15% for PM2.5). Results for population-weighted exposure revealed exposure to PM2.5 concentrations above the WHO AQG limit value in the cycling environment. Uncertainties for the exposure contributions arising from emissions and infiltration from outdoor to indoor pollutant concentrations range from −12% to +7% for NO2 and PM2.5. The developed “dynamic transport approach” is integrated in a computationally efficient exposure model, which is generally applicable in European urban areas. The presented methodology is promoted for use in urban mobility planning, e.g., to investigate on policy-driven changes in modal split and their combined effect on emissions, population activity and population exposure. Full article
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Open AccessArticle
Modelling of Urban Air Pollutant Concentrations with Artificial Neural Networks Using Novel Input Variables
Int. J. Environ. Res. Public Health 2020, 17(6), 2025; https://doi.org/10.3390/ijerph17062025 - 19 Mar 2020
Cited by 1
Abstract
Since operating urban air quality stations is not only time consuming but also costly, and because air pollutants can cause serious health problems, this paper presents the hourly prediction of ten air pollutant concentrations (CO2, NH3, NO, NO2 [...] Read more.
Since operating urban air quality stations is not only time consuming but also costly, and because air pollutants can cause serious health problems, this paper presents the hourly prediction of ten air pollutant concentrations (CO2, NH3, NO, NO2, NOx, O3, PM1, PM2.5, PM10 and PN10) in a street canyon in Münster using an artificial neural network (ANN) approach. Special attention was paid to comparing three predictor options representing the traffic volume: we included acoustic sound measurements (sound), the total number of vehicles (traffic), and the hour of the day and the day of the week (time) as input variables and then compared their prediction powers. The models were trained, validated and tested to evaluate their performance. Results showed that the predictions of the gaseous air pollutants NO, NO2, NOx, and O3 reveal very good agreement with observations, whereas predictions for particle concentrations and NH3 were less successful, indicating that these models can be improved. All three input variable options (sound, traffic and time) proved to be suitable and showed distinct strengths for modelling various air pollutant concentrations. Full article
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Open AccessArticle
Modeling of the Concentrations of Ultrafine Particles in the Plumes of Ships in the Vicinity of Major Harbors
Int. J. Environ. Res. Public Health 2020, 17(3), 777; https://doi.org/10.3390/ijerph17030777 - 26 Jan 2020
Cited by 1
Abstract
Marine traffic in harbors can be responsible for significant atmospheric concentrations of ultrafine particles (UFPs), which have widely recognized negative effects on human health. It is therefore essential to model and measure the time evolution of the number size distributions and chemical composition [...] Read more.
Marine traffic in harbors can be responsible for significant atmospheric concentrations of ultrafine particles (UFPs), which have widely recognized negative effects on human health. It is therefore essential to model and measure the time evolution of the number size distributions and chemical composition of UFPs in ship exhaust to assess the resulting exposure in the vicinity of shipping routes. In this study, a sequential modelling chain was developed and applied, in combination with the data measured and collected in major harbor areas in the cities of Helsinki and Turku in Finland, during winter and summer in 2010–2011. The models described ship emissions, atmospheric dispersion, and aerosol dynamics, complemented with a time–microenvironment–activity model to estimate the short-term UFP exposure. We estimated the dilution ratio during the initial fast expansion of the exhaust plume to be approximately equal to eight. This dispersion regime resulted in a fully formed nucleation mode (denoted as Nuc2). Different selected modelling assumptions about the chemical composition of Nuc2 did not have an effect on the formation of nucleation mode particles. Aerosol model simulations of the dispersing ship plume also revealed a partially formed nucleation mode (Nuc1; peaking at 1.5 nm), consisting of freshly nucleated sulfate particles and condensed organics that were produced within the first few seconds. However, subsequent growth of the new particles was limited, due to efficient scavenging by the larger particles originating from the ship exhaust. The transport of UFPs downwind of the ship track increased the hourly mean UFP concentrations in the neighboring residential areas by a factor of two or more up to a distance of 3600 m, compared with the corresponding UFP concentrations in the urban background. The substantially increased UFP concentrations due to ship traffic significantly affected the daily mean exposures in residential areas located in the vicinity of the harbors. Full article
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Open AccessArticle
Dispersion Characteristics of Hazardous Gas and Exposure Risk Assessment in a Multiroom Building Environment
Int. J. Environ. Res. Public Health 2020, 17(1), 199; https://doi.org/10.3390/ijerph17010199 - 27 Dec 2019
Cited by 2
Abstract
The leakage of hazardous chemicals during storage and transport processes is a kind of commonly occurring accident that can pose a serious threat to people’s lives and property. This paper aims to investigate the airflow and dispersion characteristics of hazardous gas around a [...] Read more.
The leakage of hazardous chemicals during storage and transport processes is a kind of commonly occurring accident that can pose a serious threat to people’s lives and property. This paper aims to investigate the airflow and dispersion characteristics of hazardous gas around a multiroom building, and evaluate the corresponding exposure risks. The effects on indoor air quality (IAQ) when polluted air enters a room under different indoor and external conditions were examined by using a computational fluid dynamics technique. First, the numerical model established herein was verified by the available wind-tunnel experimental data, and acceptable agreement was found between the predicted and measured velocities. Subsequently, the effects of different natural ventilation paths, wall porosities and outdoor pollutant source characteristics on the airflow and contaminant distribution were evaluated. The study not only reveals the airflow pattern and concentration distribution in indoor spaces under different natural ventilation conditions but also quantitatively analyzes the relationship between the probability of death and the corresponding source strength under the circumstance of pollutant leakage near a building. The results can be useful for the prevention and control of hazardous chemical gas leakages and provide some guidance on evacuation after an accidental or routine leakage. Full article
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Open AccessArticle
Modeling of High Nanoparticle Exposure in an Indoor Industrial Scenario with a One-Box Model
Int. J. Environ. Res. Public Health 2019, 16(10), 1695; https://doi.org/10.3390/ijerph16101695 - 14 May 2019
Cited by 2
Abstract
Mass balance models have proved to be effective tools for exposure prediction in occupational settings. However, they are still not extensively tested in real-world scenarios, or for particle number concentrations. An industrial scenario characterized by high emissions of unintentionally-generated nanoparticles (NP) was selected [...] Read more.
Mass balance models have proved to be effective tools for exposure prediction in occupational settings. However, they are still not extensively tested in real-world scenarios, or for particle number concentrations. An industrial scenario characterized by high emissions of unintentionally-generated nanoparticles (NP) was selected to assess the performance of a one-box model. Worker exposure to NPs due to thermal spraying was monitored, and two methods were used to calculate emission rates: the convolution theorem, and the cyclic steady state equation. Monitored concentrations ranged between 4.2 × 104–2.5 × 105 cm−3. Estimated emission rates were comparable with both methods: 1.4 × 1011–1.2 × 1013 min−1 (convolution) and 1.3 × 1012–1.4 × 1013 min−1 (cyclic steady state). Modeled concentrations were 1.4-6 × 104 cm−3 (convolution) and 1.7–7.1 × 104 cm−3 (cyclic steady state). Results indicated a clear underestimation of measured particle concentrations, with ratios modeled/measured between 0.2–0.7. While both model parametrizations provided similar results on average, using convolution emission rates improved performance on a case-by-case basis. Thus, using cyclic steady state emission rates would be advisable for preliminary risk assessment, while for more precise results, the convolution theorem would be a better option. Results show that one-box models may be useful tools for preliminary risk assessment in occupational settings when room air is well mixed. Full article
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