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Special Issue "Technology, Data, and the Assessment of Atmospheric Exposure on Finer Scales"

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A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601).

Deadline for manuscript submissions: closed (30 September 2015) | Viewed by 65211

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Dr. P. Grady Dixon
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Department of Geosciences, Fort Hays State University, Hays, KS 67601, USA

Dr. Scott C. Sheridan
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Department of Geography, Kent State University, Kent, OH 44242, USA

Special Issue Information

Dear Colleagues,

Epidemiological studies of weather influences upon human health have historically relied on coarse aggregations at the scale of municipalities or larger. Health outcomes were then typically associated with point data of atmospheric conditions—whether thermal, pollution, or extreme environments—from which individual-level exposure would be approximated. Technological advances in sensing equipment now allow researchers to more precisely assess environmental exposure at the scale of an individual person. These more-localized response data, geocoded and available on finer scales, have enabled more in-depth responses to be assessed. The improved ability to geospatially integrate and analyze all these data has led to exciting new research, in which the variability of individuals’ exposure and response is coming to light.

Dr. P. Grady Dixon
Dr. Scott C. Sheridan
Guest Editors

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Keywords

weather
scale
sensors
personal exposure
geospatial

Published Papers (10 papers)

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Research

Open AccessArticle

A Conceptual Framework for the Assessment of Cumulative Exposure to Air Pollution at a Fine Spatial Scale

Kihal-Talantikite Wahida

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Int. J. Environ. Res. Public Health 2016, 13(3), 319; https://doi.org/10.3390/ijerph13030319 - 15 Mar 2016

Cited by 5 | Viewed by 6169

Abstract

Many epidemiological studies examining long-term health effects of exposure to air pollutants have characterized exposure by the outdoor air concentrations at sites that may be distant to subjects’ residences at different points in time. The temporal and spatial mobility of subjects and the spatial scale of exposure assessment could thus lead to misclassification in the cumulative exposure estimation. This paper attempts to fill the gap regarding cumulative exposure assessment to air pollution at a fine spatial scale in epidemiological studies investigating long-term health effects. We propose a conceptual framework showing how major difficulties in cumulative long-term exposure assessment could be surmounted. We then illustrate this conceptual model on the case of exposure to NO₂ following two steps: (i) retrospective reconstitution of NO₂ concentrations at a fine spatial scale; and (ii) a novel approach to assigning the time-relevant exposure estimates at the census block level, using all available data on residential mobility throughout a 10- to 20-year period prior to that for which the health events are to be detected. Our conceptual framework is both flexible and convenient for the needs of different epidemiological study designs. Full article

(This article belongs to the Special Issue Technology, Data, and the Assessment of Atmospheric Exposure on Finer Scales)

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Open AccessArticle

Automated Collection of Real-Time Alerts of Citizens as a Useful Tool to Continuously Monitor Malodorous Emissions

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Int. J. Environ. Res. Public Health 2016, 13(3), 263; https://doi.org/10.3390/ijerph13030263 - 26 Feb 2016

Cited by 7 | Viewed by 4805

Abstract

The evaluation of odor emissions and dispersion is a very arduous topic to face; the real-time monitoring of odor emissions, the identification of chemical components and, with proper certainty, the source of annoyance represent a challenge for stakeholders such as local authorities. The complaints of people, often not systematic and variously distributed, in general do not allow us to quantify the perceived annoyance. Experimental research has been performed to detect and evaluate olfactory annoyance, based on field testing of an innovative monitoring methodology grounded in automatic recording of citizen alerts. It has been applied in Taranto, in the south of Italy where a relevant industrial area is located, by using Odortel^® for automated collection of citizen alerts. To evaluate its reliability, the collection system has been integrated with automated samplers, able to sample odorous air in real time, according to the citizen alerts of annoyance and, moreover, with meteorological data (especially the wind direction) and trends in odor marker compounds, recorded by air quality monitoring stations. The results have allowed us, for the first time, to manage annoyance complaints, test their reliability, and obtain information about the distribution and entity of the odor phenomena, such that we were able to identify, with supporting evidence, the source as an oil refinery plant. Full article

(This article belongs to the Special Issue Technology, Data, and the Assessment of Atmospheric Exposure on Finer Scales)

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Open AccessArticle

Mapping to Support Fine Scale Epidemiological Cholera Investigations: A Case Study of Spatial Video in Haiti

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Int. J. Environ. Res. Public Health 2016, 13(2), 187; https://doi.org/10.3390/ijerph13020187 - 03 Feb 2016

Cited by 14 | Viewed by 4997

Abstract

The cartographic challenge in many developing world environments suffering a high disease burden is a lack of granular environmental covariates suitable for modeling disease outcomes. As a result, epidemiological questions, such as how disease diffuses at intra urban scales are extremely difficult to answer. This paper presents a novel geospatial methodology, spatial video, which can be used to collect and map environmental covariates, while also supporting field epidemiology. An example of epidemic cholera in a coastal town of Haiti is used to illustrate the potential of this new method. Water risks from a 2012 spatial video collection are used to guide a 2014 survey, which concurrently included the collection of water samples, two of which resulted in positive lab results “of interest” (bacteriophage specific for clinical cholera strains) to the current cholera situation. By overlaying sample sites on 2012 water risk maps, a further fifteen proposed water sample locations are suggested. These resulted in a third spatial video survey and an additional “of interest” positive water sample. A potential spatial connection between the “of interest” water samples is suggested. The paper concludes with how spatial video can be an integral part of future fine-scale epidemiological investigations for different pathogens. Full article

(This article belongs to the Special Issue Technology, Data, and the Assessment of Atmospheric Exposure on Finer Scales)

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Open AccessArticle

A Bicycle-Based Field Measurement System for the Study of Thermal Exposure in Cuyahoga County, Ohio, USA

Nicholas B. Rajkovich

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Larissa Larsen

Int. J. Environ. Res. Public Health 2016, 13(2), 159; https://doi.org/10.3390/ijerph13020159 - 25 Jan 2016

Cited by 26 | Viewed by 8530

Abstract

Collecting a fine scale of microclimate data can help to determine how physical characteristics (e.g., solar radiation, albedo, sky view factor, vegetation) contribute to human exposure to ground and air temperatures. These data also suggest how urban design strategies can reduce the negative impacts of the urban heat island effect. However, urban microclimate measurement poses substantial challenges. For example, data taken at local airports are not representative of the conditions at the neighborhood or district level because of variation in impervious surfaces, vegetation, and waste heat from vehicles and buildings. In addition, fixed weather stations cannot be deployed quickly to capture data from a heat wave. While remote sensing can provide data on land cover and ground surface temperatures, resolution and cost remain significant limitations. This paper describes the design and validation of a mobile measurement bicycle. This bicycle permits movement from space to space within a city to assess the physical and thermal properties of microclimates. The construction of the vehicle builds on investigations of the indoor thermal environment of buildings using thermal comfort carts. Full article

(This article belongs to the Special Issue Technology, Data, and the Assessment of Atmospheric Exposure on Finer Scales)

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Open AccessArticle

A Two-Stage Method to Estimate the Contribution of Road Traffic to PM_2.5 Concentrations in Beijing, China

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Int. J. Environ. Res. Public Health 2016, 13(1), 124; https://doi.org/10.3390/ijerph13010124 - 13 Jan 2016

Cited by 22 | Viewed by 6946

Abstract

Background: Fine particulate matters with aerodynamic diameters smaller than 2.5 micrometers (PM_2.5) have been a critical environmental problem in China due to the rapid road vehicle growth in recent years. To date, most methods available to estimate traffic contributions to ambient PM_2.5 concentration are often hampered by the need for collecting data on traffic volume, vehicle type and emission profile. Objective: To develop a simplified and indirect method to estimate the contribution of traffic to PM_2.5 concentration in Beijing, China. Methods: Hourly PM_2.5 concentration data, daily meteorological data and geographic information were collected at 35 air quality monitoring (AQM) stations in Beijing between 2013 and 2014. Based on the PM_2.5 concentrations of different AQM station types, a two-stage method comprising a dispersion model and generalized additive mixed model (GAMM) was developed to estimate separately the traffic and non-traffic contributions to daily PM_2.5 concentration. The geographical trend of PM_2.5 concentrations was investigated using generalized linear mixed model. The temporal trend of PM_2.5 and non-linear relationship between PM_2.5 and meteorological conditions were assessed using GAMM. Results: The medians of daily PM_2.5 concentrations during 2013–2014 at 35 AQM stations in Beijing ranged from 40 to 92 μg/m³. There was a significant increasing trend of PM_2.5 concentration from north to south. The contributions of road traffic to daily PM_2.5 concentrations ranged from 17.2% to 37.3% with an average 30%. The greatest contribution was found at AQM stations near busy roads. On average, the contribution of road traffic at urban stations was 14% higher than that at rural stations. Conclusions: Traffic emissions account for a substantial share of daily total PM_2.5 concentrations in Beijing. Our two-stage method is a useful and convenient tool in ecological and epidemiological studies to estimate the traffic contribution to PM_2.5 concentrations when there is limited information on vehicle number and types and emission profile. Full article

(This article belongs to the Special Issue Technology, Data, and the Assessment of Atmospheric Exposure on Finer Scales)

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Open AccessArticle

Heat and Humidity in the City: Neighborhood Heat Index Variability in a Mid-Sized City in the Southeastern United States

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Int. J. Environ. Res. Public Health 2016, 13(1), 117; https://doi.org/10.3390/ijerph13010117 - 11 Jan 2016

Cited by 48 | Viewed by 7837

Abstract

Daily weather conditions for an entire city are usually represented by a single weather station, often located at a nearby airport. This resolution of atmospheric data fails to recognize the microscale climatic variability associated with land use decisions across and within urban neighborhoods. This study uses heat index, a measure of the combined effects of temperature and humidity, to assess the variability of heat exposure from ten weather stations across four urban neighborhoods and two control locations (downtown and in a nearby nature center) in Knoxville, Tennessee, USA. Results suggest that trees may negate a portion of excess urban heat, but are also associated with greater humidity. As a result, the heat index of locations with more trees is significantly higher than downtown and areas with fewer trees. Trees may also reduce heat stress by shading individuals from incoming radiation, though this is not considered in this study. Greater amounts of impervious surfaces correspond with reduced evapotranspiration and greater runoff, in terms of overall mass balance, leading to a higher temperature, but lower relative humidity. Heat index and relative humidity were found to significantly vary between locations with different tree cover and neighborhood characteristics for the full study time period as well as for the top 10% of heat index days. This work demonstrates the need for high-resolution climate data and the use of additional measures beyond temperature to understand urban neighborhood exposure to extreme heat, and expresses the importance of considering vulnerability differences among residents when analyzing neighborhood-scale impacts. Full article

(This article belongs to the Special Issue Technology, Data, and the Assessment of Atmospheric Exposure on Finer Scales)

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Open AccessArticle

Occupational Heat Stress Profiles in Selected Workplaces in India

Vidhya Venugopal

Jeremiah S. Chinnadurai

Rebekah A. I. Lucas

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Tord Kjellstrom

Int. J. Environ. Res. Public Health 2016, 13(1), 89; https://doi.org/10.3390/ijerph13010089 - 29 Dec 2015

Cited by 76 | Viewed by 7718

Abstract

Health and productivity impacts from occupational heat stress have significant ramifications for the large workforce of India. This study profiled occupational heat stress impacts on the health and productivity of workers in select organized and unorganized Indian work sectors. During hotter and cooler seasons, Wet Bulb Globe Temperatures (WBGT) were used to quantify the risk of heat stress, according to International workplace guidelines. Questionnaires assessed workers’ perceived health and productivity impacts from heat stress. A total of 442 workers from 18 Indian workplaces participated (22% and 78% from the organized and unorganized sector, respectively). Overall 82% and 42% of workers were exposed to higher than recommended WBGT during hotter and cooler periods, respectively. Workers with heavy workloads reported more heat-related health issues (chi square = 23.67, p ≤ 0.001) and reduced productivity (chi square = 15.82, p ≤ 0.001), especially the outdoor workers. Heat-rashes, dehydration, heat-syncope and urinogenital symptoms were self-reported health issues. Cited reasons for productivity losses were: extended-work hours due to fatigue/exhaustion, sickness/hospitalization and wages lost. Reducing workplace heat stress will benefit industries and workers via improving worker health and productivity. Adaptation and mitigation measures to tackle heat stress are imperative to protect the present and future workforce as climate change progresses. Full article

(This article belongs to the Special Issue Technology, Data, and the Assessment of Atmospheric Exposure on Finer Scales)

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Open AccessArticle

A Spatial Framework to Map Heat Health Risks at Multiple Scales

Hung Chak Ho

Anders Knudby

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Wei Huang

Int. J. Environ. Res. Public Health 2015, 12(12), 16110-16123; https://doi.org/10.3390/ijerph121215046 - 18 Dec 2015

Cited by 51 | Viewed by 7359

Abstract

In the last few decades extreme heat events have led to substantial excess mortality, most dramatically in Central Europe in 2003, in Russia in 2010, and even in typically cool locations such as Vancouver, Canada, in 2009. Heat-related morbidity and mortality is expected to increase over the coming centuries as the result of climate-driven global increases in the severity and frequency of extreme heat events. Spatial information on heat exposure and population vulnerability may be combined to map the areas of highest risk and focus mitigation efforts there. However, a mismatch in spatial resolution between heat exposure and vulnerability data can cause spatial scale issues such as the Modifiable Areal Unit Problem (MAUP). We used a raster-based model to integrate heat exposure and vulnerability data in a multi-criteria decision analysis, and compared it to the traditional vector-based model. We then used the Getis-Ord G_i index to generate spatially smoothed heat risk hotspot maps from fine to coarse spatial scales. The raster-based model allowed production of maps at spatial resolution, more description of local-scale heat risk variability, and identification of heat-risk areas not identified with the vector-based approach. Spatial smoothing with the Getis-Ord G_i index produced heat risk hotspots from local to regional spatial scale. The approach is a framework for reducing spatial scale issues in future heat risk mapping, and for identifying heat risk hotspots at spatial scales ranging from the block-level to the municipality level. Full article

(This article belongs to the Special Issue Technology, Data, and the Assessment of Atmospheric Exposure on Finer Scales)

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Open AccessArticle

Role of Acclimatization in Weather-Related Human Mortality During the Transition Seasons of Autumn and Spring in a Thermally Extreme Mid-Latitude Continental Climate

Christopher R. De Freitas

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Elena A. Grigorieva

Int. J. Environ. Res. Public Health 2015, 12(12), 14974-14987; https://doi.org/10.3390/ijerph121214962 - 26 Nov 2015

Cited by 17 | Viewed by 4597

Abstract

Human mortality is closely related to natural climate-determined levels of thermal environmental stress and the resulting thermophysiological strain. Most climate-mortality research has focused on seasonal extremes during winter and summer when mortality is the highest, while relatively little attention has been paid to mortality during the transitional seasons of autumn and spring. The body acclimatizes to heat in the summer and cold in winter and readjusts through acclimatization during the transitions between the two during which time the body experiences the thermophysiological strain of readjustment. To better understand the influences of weather on mortality through the acclimatization process, the aim here is to examine the periods that link very cold and very warms seasons. The study uses the Acclimatization Thermal Strain Index (ATSI), which is a comparative measure of short-term thermophysiological impact on the body. ATSI centers on heat exchange with the body’s core via the respiratory system, which cannot be protected. The analysis is based on data for a major city in the climatic region of the Russian Far East characterized by very hot summers and extremely cold winters. The results show that although mortality peaks in winter (January) and is at its lowest in summer (August), there is not a smooth rise through autumn nor a smooth decline through spring. A secondary peak occurs in autumn (October) with a smaller jump in May. This suggests the acclimatization from warm-to-cold produces more thermophysiological strain than the transition from cold-to-warm. The study shows that ATSI is a useful metric for quantifying the extent to which biophysical adaptation plays a role in increased strain on the body during re-acclimatization and for this reason is a more appropriate climatic indictor than air temperature alone. The work gives useful bioclimatic information on risks involved in transitional seasons in regions characterized by climatic extremes. This could be handy in planning and managing health services to the public and measures that might be used to help mitigate impacts. Full article

(This article belongs to the Special Issue Technology, Data, and the Assessment of Atmospheric Exposure on Finer Scales)

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Open AccessArticle

Spatial and Temporal Distribution of PM_2.5 Pollution in Xi’an City, China

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Int. J. Environ. Res. Public Health 2015, 12(6), 6608-6625; https://doi.org/10.3390/ijerph120606608 - 10 Jun 2015

Cited by 45 | Viewed by 5792

Abstract

The monitoring data of the 13 stations in Xi’an city for the whole years of 2013 and 2014 was counted and analyzed. Obtaining the spatial and temporal distribution characteristics of PM_2.5 was the goal. Cluster analysis and the wavelet transform were utilized to discuss the regional distribution characteristics of PM_2.5 concentration (ρ(PM_2.5)) and the main features of its yearly changes and sudden changes. Additionally, some relevant factors were taken into account to interpret the changes. The results show that ρ(PM_2.5) in Xi’an during 2013 was generally higher than in 2014, it is high in winter and low in summer, and the high PM_2.5 concentration centers are around the People’s Stadium and Caotan monitoring sites; For the regional PM_2.5 distribution, the 13 sites can be divided into three categories, in which Textile city is Cluster 1, and High-tech Western is Cluster 2, and Cluster 3 includes the remaining 11 monitoring sites; the coefficient of goodness of the cluster analysis is 0.6761, which indicates that the result is acceptable. As for the yearly change, apart from June and July, the average ρ(PM_2.5) concentration has been above the normal concentration criteria of Chinese National Standard (50 g/m³); cloudy weather and low winds are the major meteorological factors leading to the sudden changes of ρ(PM_2.5). Full article

(This article belongs to the Special Issue Technology, Data, and the Assessment of Atmospheric Exposure on Finer Scales)

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