Effectiveness of urban shelter-in-place—II: Residential districts

Chan, Wanyu R.; Nazaroff, William W.; Price, Phillip N.; Gadgil, Ashok

doi:10.1016/j.atmosenv.2007.04.059

Cited by 21 publications

(22 citation statements)

References 29 publications

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“…In addition, this situation of extreme conditions, especially high wind speeds, should be handled very carefully since as reported by Guyot et al [33], although the pollutant dilutes faster with increasing wind speed, the resulting dose inside the shelter could increase due to the effect of the wind over the ACH, accelerating the toxic gas transfer to the indoor. Thus, a better procedure to estimate the shelter-in-place effectiveness and the evacuation radius should include an appropriate determination of the outdoor concentration for the specific meteorological conditions, especially high wind speeds, and the ACH distribution for the affected area under these meteorological conditions as also proposed by Chan et al [2], instead of assuming a constant ACH for all the dwellings inside the affected area.…”

Section: Resultsmentioning

confidence: 99%

“…Catalonia is a highly industrialized region in the north-east of Spain in which 180 companies are regulated by the Seveso II Directive [1]. In a shelter-in-place situation, air infiltration is one of the variables with the greatest influence on shelter-in-place effectiveness, as discussed by Chan et al [2] and Montoya et al [3], because it conditions the speed of toxic gas inflow and therefore the indoor gas concentration.…”

Section: Introductionmentioning

confidence: 99%

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Air leakage in Catalan dwellings: Developing an airtightness model and leakage airflow predictions

Montoya

Pastor

Carrie³

et al. 2010

Building and Environment

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a b s t r a c tIn this study we estimate the air leakage distribution of single-family dwellings in Catalonia and use a statistical analysis of an airtightness database for single-family dwellings in France to identify the building characteristics that have the greatest influence on airtightness. The most significant variables are found to be the structure type, the floor area, the age of the building, the number of stories and the insulation type. A multiple linear regression technique is then applied to establish a predictive model for deriving an estimated value of airtightness from these characteristics. To estimate the infiltration airflow, a stochastic simulation of the building characteristics was performed per census tract using real data on the distributions of building variables taken from the census information. The model is then applied to determine the power law coefficient and the airtightness distribution. The predicted flow coefficients are combined with the AIM-2 model and given meteorological conditions to determine the infiltration airflow. Two sets of meteorological conditions are considered: average conditions and extreme conditions for each season.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Air leakage in Catalan dwellings: Developing an airtightness model and leakage airflow predictions

Montoya

Pastor

Carrie³

et al. 2010

Building and Environment

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“…Our prior work on evaluating SIP effectiveness during large-scale chemical releases [2][3][4] assumed that the toxic load applies to time-varying concentrations in the following form:…”

Section: Toxic Load and Shelter-in-place Effectivenessmentioning

confidence: 99%

“…Recent studies have modeled the transport and dispersion of chemical compounds both outdoors and indoors under various release scenarios [1][2][3][4]. Model predictions of outdoor and indoor concentrations vary with time, but there is no consensus on how to relate time-varying air concentrations to health effects [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Computing Toxic Load for Shelter-in-Place Analysis Using Joint Urban 2003

Chan¹,

Sohn²

2012

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Toxic load is a metric used to quantify acute effects from inhalation exposures. The toxic load to individuals depends on the fluctuations of chemical concentrations because the exposureresponse relationship is often nonlinear. To study the effects of concentration fluctuations on toxic load, we analyzed concentration data from the Joint Urban 2003 series of city-scale tracer gas studies. We summarized the outdoor concentrations measured by fast-response gas analyzers and computed outdoor toxic load. We then analyzed the amount of tracer gas that entered a 16-story office building and compared indoor and outdoor toxic loads. We show that the time aggregation used to compute toxic load is a source of uncertainty in hazard assessments.However, in comparison to other uncertainties and variability inherent in hazard assessments involving buildings, the choice of time averaging interval plays a minor role, especially when toxic load is used to compute other aggregated metrics such as the effectiveness of sheltering indoors. In the absence of compound-specific information to dictate a time average, we propose following Acute Exposure Guideline Levels (AEGLs) and using timescales on the order of minutes for computing indoor toxic load.

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“…In the first paper (Chan et al, 2007a), we conducted a parametric investigation using an idealized representation of the system. In the second paper (Chan et al, 2007b), SIP effectiveness in a residential community was assessed using realistic transport and transformation models and input parameters. In those studies, we found that SIP effectiveness depends strongly on the degree of nonlinearity in the dose-response relationship.…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of urban shelter-in-place. III: Commercial districts

et al. 2008

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In the event of a toxic chemical release to the atmosphere, shelter-in-place (SIP) is an emergency response option available to protect public health. This paper is the last in a three-part series that examines the effectiveness of SIP at reducing adverse health effects in communities. We model a hypothetical chemical release in an urban area, and consider SIP effectiveness in protecting occupants of commercial buildings. Building air infiltration rates are predicted from empirical data using an existing model. We consider the distribution of building air infiltration rates both with mechanical ventilation systems turned off and with the systems operating. We also consider the effects of chemical sorption to indoor surfaces and nonlinear chemical dose-response relationships. We find that commercial buildings provide effective shelter when ventilation systems are off, but that any delay in turning off ventilation systems can greatly reduce SIP effectiveness. Using a two-zone model, we find that there can be substantial benefit by taking shelter in the inner parts of a building that do not experience direct air exchange with the outdoors. Air infiltration rates vary substantially among buildings and this variation is important in quantifying effectiveness for emergency response. Community-wide health metrics, introduced in the previous papers in this series, can be applied in pre-event planning and to guide real-time emergency response.

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Effectiveness of urban shelter-in-place—II: Residential districts

Cited by 21 publications

References 29 publications

Air leakage in Catalan dwellings: Developing an airtightness model and leakage airflow predictions

Air leakage in Catalan dwellings: Developing an airtightness model and leakage airflow predictions

Computing Toxic Load for Shelter-in-Place Analysis Using Joint Urban 2003

Effectiveness of urban shelter-in-place. III: Commercial districts

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