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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: closed (31 July 2019) | Viewed by 41387

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Special Issue Editors

Dr. Vlad Isakov

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Guest Editor

Center for Environmental Measurement and Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Interests: air quality; modeling; meteorology; inhalation exposure
Special Issues, Collections and Topics in MDPI journals

Ms. Sue Kimbrough

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Guest Editor

Air and Energy Management Division, National Risk Management Research Laboratory, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Interests: near-source emissions characterization; sensors; mobile measurements; citizen science; PM2.5; black carbon; transportation

Mr. Stephen Krabbe

E-Mail Website
Guest Editor

Environmental Sciences and Technology Division, Region 7, US Environmental Protection Agency, Kansas City, KS, 66101, USA
Interests: near-source emissions characterization; sensors; mobile measurements; citizen science

Special Issue Information

Dear Colleagues,

Globally, the human population is becoming more urbanized. Populations are in closer proximity to sources of air pollution than ever before. This includes air pollution from large multi-modal transportation facilities, industry, and other anthropogenic area sources. Due to this closer proximity, concern over adverse health impacts due to air pollutant exposures has increased. As a result, there is a need to develop innovative techniques that can characterize near-source air pollution, analyse the results, and communicate those results to the public. The goal of this Special Issue on near-source air pollution is to highlight innovative research, measurement techniques, analyses, and model applications with an emphasis on the characterization of near-source emissions, deposition, and transport. Of particular interest are innovative approaches that include lower cost sensors, sensor networks, mobile measurement, and citizen science, and how these approaches may be used to inform research and regulatory entities, as well as the public at-large. This Special Issue represents an effort to capture current developments in the field and provide a forum for cutting edge contributions to the literature. Research papers, analytical reviews, case studies, conceptual frameworks, and policy-relevant articles are encouraged.

Dr. Vlad Isakov
Ms. Sue Kimbrough
Mr. Stephen Krabbe
Guest Editors

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Keywords

near-source
near-road
source characterization
modeling
sensors
mobile measurements
criteria pollutants
PM2.5
black carbon
citizen science

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Published Papers (8 papers)

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Research

15 pages, 2961 KiB

Open AccessFeature PaperArticle

Demonstration of a Low-Cost Multi-Pollutant Network to Quantify Intra-Urban Spatial Variations in Air Pollutant Source Impacts and to Evaluate Environmental Justice

by Rebecca Tanzer, Carl Malings, Aliaksei Hauryliuk, R. Subramanian and Albert A. Presto

Int. J. Environ. Res. Public Health 2019, 16(14), 2523; https://doi.org/10.3390/ijerph16142523 - 15 Jul 2019

Cited by 42 | Viewed by 6043

Abstract

Air quality monitoring has traditionally been conducted using sparsely distributed, expensive reference monitors. To understand variations in PM_2.5 on a finely resolved spatiotemporal scale a dense network of over 40 low-cost monitors was deployed throughout and around Pittsburgh, Pennsylvania, USA. Monitor locations covered a wide range of site types with varying traffic and restaurant density, varying influences from local sources, and varying socioeconomic (environmental justice, EJ) characteristics. Variability between and within site groupings was observed. Concentrations were higher near the source-influenced sites than the Urban or Suburban Residential sites. Gaseous pollutants (NO₂ and SO₂) were used to differentiate between traffic (higher NO₂ concentrations) and industrial (higher SO₂ concentrations) sources of PM_2.5. Statistical analysis proved these differences to be significant (coefficient of divergence > 0.2). The highest mean PM_2.5 concentrations were measured downwind (east) of the two industrial facilities while background level PM_2.5 concentrations were measured at similar distances upwind (west) of the point sources. Socioeconomic factors, including the fraction of non-white population and fraction of population living under the poverty line, were not correlated with increases in PM_2.5 or NO₂ concentration. The analysis conducted here highlights differences in PM_2.5 concentration within site groupings that have similar land use thus demonstrating the utility of a dense sensor network. Our network captures temporospatial pollutant patterns that sparse regulatory networks cannot. Full article

(This article belongs to the Special Issue Near-Source Air Pollution)

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19 pages, 8873 KiB

Open AccessArticle

Rubbertown Next Generation Emissions Measurement Demonstration Project

by Eben Thoma, Ingrid George, Rachelle Duvall, Tai Wu, Donald Whitaker, Karen Oliver, Shaibal Mukerjee, Halley Brantley, Jane Spann, Tiereny Bell, Njeri Carlton-Carew, Parikshit Deshmukh, Jacob Cansler, Tamira Cousett, Wei Tang, Andrea Cooley, Kyle Zimmerman, Billy DeWitt and Bryan Paris

Int. J. Environ. Res. Public Health 2019, 16(11), 2041; https://doi.org/10.3390/ijerph16112041 - 8 Jun 2019

Cited by 9 | Viewed by 6489

Abstract

Industrial facilities and other sources can emit air pollutants from fugitive leaks, process malfunctions and area sources that can be difficult to understand and to manage. Next generation emissions measurement (NGEM) approaches executed near facilities are enabling new ways to assess these sources and their impacts to nearby populations. This paper describes complementary uses of emerging NGEM systems in a Louisville, KY industrial district (Rubbertown), focusing on an important area air toxic, 1,3-butadiene. Over a one-year deployment starting in September 2017, two-week average passive samplers (PSs) at 11 sites showed both geospatial and temporal trends. At 0.24 ppbv annual average 1,3-butadiene concentration, a group of PSs located near facility fence lines was elevated compared to a PS group located in the community and upwind from facilities (0.07 ppbv average). Two elevated PS periods capturing emission events were examined using time-resolved NGEM approaches as case studies. In one event a 1.18 ppbv PS reading was found to be relatively localized and was caused by a multiday emission from a yet to be identified, non-facility source. In the other event, the airshed was more broadly impacted with PS concentrations ranging from 0.71 ppbv for the near-facility group to 0.46 ppbv for the community group. This case was likely influenced by a known emission event at an industrial facility. For both case studies, air pollutant and wind data from prototype NGEM systems were combined with source location models to inform the emission events. This research illustrates the power of applying NGEM approaches to improve both the understanding of emissions near sources and knowledge of impacts to near-source communities. Full article

(This article belongs to the Special Issue Near-Source Air Pollution)

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20 pages, 4794 KiB

Open AccessArticle

Conditions Leading to Elevated PM_2.5 at Near-Road Monitoring Sites: Case Studies in Denver and Indianapolis

by Steven G. Brown, Bryan Penfold, Anondo Mukherjee, Karin Landsberg and Douglas S. Eisinger

Int. J. Environ. Res. Public Health 2019, 16(9), 1634; https://doi.org/10.3390/ijerph16091634 - 10 May 2019

Cited by 14 | Viewed by 3601

Abstract

We examined two near-road monitoring sites where the daily PM_2.5 readings were among the highest of any near-road monitoring location in the U.S. during 2014–2016: Denver, Colorado, in February 2014 and Indianapolis, Indiana, in November 2016. At the Denver site, which had the highest measured U.S. near-road 24-hr PM_2.5 concentrations in 2014, concentrations exceeded the daily National Ambient Air Quality Standards (NAAQS) on three days during one week in 2014; the Indianapolis site had the second-highest number of daily exceedances of any near-road site in 2016 and the highest 3-year average PM_2.5 of any near-road site during 2014–2016. Both sites had hourly pollutant, meteorological, and traffic data available, making them ideal for case studies. For both locations, we compared air pollution observations at the near-road site to observations at other sites in the urban area to calculate the near-road PM_2.5 “increment” and evaluated the effects of changes in meteorology and traffic. The Denver near-road site consistently had the highest PM_2.5 values in the Denver area, and was typically highest when winds were near-downwind, rather than directly downwind, to the freeway. Complex Denver site conditions (near-road buildings and roadway alignment) likely contributed to higher PM_2.5 concentrations. The increment at Indianapolis was also highest under near-downwind, rather than directly downwind, conditions. At both sites, while the near-road site often had higher PM_2.5 concentrations than nearby sites, there was no clear correlation between traffic conditions (vehicle speed, fleet mix) and the high PM_2.5 concentrations. Full article

(This article belongs to the Special Issue Near-Source Air Pollution)

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20 pages, 3867 KiB

Open AccessArticle

Quantifying Urban Spatial Variations of Anthropogenic VOC Concentrations and Source Contributions with a Mobile Sampling Platform

by Peishi Gu, Timothy R. Dallmann, Hugh Z. Li, Yi Tan and Albert A. Presto

Int. J. Environ. Res. Public Health 2019, 16(9), 1632; https://doi.org/10.3390/ijerph16091632 - 10 May 2019

Cited by 9 | Viewed by 4754

Abstract

Volatile organic compounds (VOCs) are important atmospheric constituents because they contribute to formation of ozone and secondary aerosols, and because some VOCs are toxic air pollutants. We measured concentrations of a suite of anthropogenic VOCs during summer and winter at 70 locations representing different microenvironments around Pittsburgh, PA. The sampling sites were classified both by land use (e.g., high versus low traffic) and grouped based on geographic similarity and proximity. There was roughly a factor of two variation in both total VOC and single-ring aromatic VOC concentrations across the site groups. Concentrations were roughly 25% higher in winter than summer. Source apportionment with positive matrix factorization reveals that the major VOC sources are gasoline vehicles, solvent evaporation, diesel vehicles, and two factors attributed to industrial emissions. While we expected to observe significant spatial variability in the source impacts across the sampling domain, we instead found that source impacts were relatively homogeneous. Full article

(This article belongs to the Special Issue Near-Source Air Pollution)

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16 pages, 4406 KiB

Open AccessArticle

Assessment of Spatial Variability across Multiple Pollutants in Auckland, New Zealand

by Ian Longley, Brett Tunno, Elizabeth Somervell, Sam Edwards, Gustavo Olivares, Sally Gray, Guy Coulson, Leah Cambal, Courtney Roper, Lauren Chubb and Jane E. Clougherty

Int. J. Environ. Res. Public Health 2019, 16(9), 1567; https://doi.org/10.3390/ijerph16091567 - 5 May 2019

Cited by 8 | Viewed by 3563

Abstract

Spatial saturation studies using source-specific chemical tracers are commonly used to examine intra-urban variation in exposures and source impacts, for epidemiology and policy purposes. Most such studies, however, has been performed in North America and Europe, with substantial regional combustion-source contributions. In contrast, Auckland, New Zealand, a large western city, is relatively isolated in the south Pacific, with minimal impact from long-range combustion sources. However, fluctuating wind patterns, complex terrain, and an adjacent major port complicate pollution patterns within the central business district (CBD). We monitored multiple pollutants (fine particulate matter (PM_2.5), black carbon (BC), elemental composition, organic diesel tracers (polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes), and nitrogen dioxide (NO₂)) at 12 sites across the ~5 km² CBD during autumn 2014, to capture spatial variation in traffic, diesel, and proximity to the port. PM_2.5 concentrations varied 2.5-fold and NO₂ concentrations 2.9-fold across the CBD, though constituents varied more dramatically. The highest-concentration constituent was sodium (Na), a distinct non-combustion-related tracer for sea salt (µ = 197.8 ng/m³ (SD = 163.1 ng/m³)). BC, often used as a diesel-emissions tracer, varied more than five-fold across sites. Vanadium (V), higher near the ports, varied more than 40-fold across sites. Concentrations of most combustion-related constituents were higher near heavy traffic, truck, or bus activity, and near the port. Wind speed modified absolute concentrations, and wind direction modified spatial patterns in concentrations (i.e., ports impacts were more notable with winds from the northeast). Full article

(This article belongs to the Special Issue Near-Source Air Pollution)

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17 pages, 6078 KiB

Open AccessArticle

Using Low-Cost Air Quality Sensor Networks to Improve the Spatial and Temporal Resolution of Concentration Maps

by Faraz Enayati Ahangar, Frank R. Freedman and Akula Venkatram

Int. J. Environ. Res. Public Health 2019, 16(7), 1252; https://doi.org/10.3390/ijerph16071252 - 8 Apr 2019

Cited by 28 | Viewed by 4945

Abstract

We present an approach to analyzing fine particulate matter (PM_2.5) data from a network of “low cost air quality monitors” (LCAQM) to obtain a finely resolved concentration map. In the approach, based on a dispersion model, we first identify the probable locations of the sources, and then estimate the magnitudes of the emissions from these sources by fitting model estimates of concentrations to corresponding measurements. The emissions are then used to estimate concentrations on a grid covering the domain of interest. The residuals between model estimates at the monitor locations and the measured concentrations are then interpolated to the grid points using Kriging. We illustrate this approach by applying it to a network of 20 LCAQMs located in the Imperial Valley of Southern California. Estimating the underlying mean concentration field with a dispersion model provides a more realistic estimate of the spatial distribution of PM_2.5 concentrations than that from the Kriging observations directly. Full article

(This article belongs to the Special Issue Near-Source Air Pollution)

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14 pages, 2700 KiB

Open AccessArticle

Characterization of Spatial Air Pollution Patterns Near a Large Railyard Area in Atlanta, Georgia

by Halley L. Brantley, Gayle S.W. Hagler, Scott C. Herndon, Paola Massoli, Michael H. Bergin and Armistead G. Russell

Int. J. Environ. Res. Public Health 2019, 16(4), 535; https://doi.org/10.3390/ijerph16040535 - 13 Feb 2019

Cited by 21 | Viewed by 5216

Abstract

Railyards are important transportation hubs, and they are often situated near populated areas with high co-located density of manufacturing, freight movement and commercial enterprises. Emissions occurring within railyards can affect nearby air quality. To better understand the air pollution levels in proximity to a major railyard, an intensive mobile air monitoring study was conducted in May 2012 around a major railyard area in Atlanta, GA, constituted of two separate facilities situated side-by-side. A total of 19 multi-hour mobile monitoring sessions took place over different times of day, days of the week, and under a variety of wind conditions. High time resolution measurements included black carbon (BC), particle number concentration (PN), particle optical extinction (EXT), oxides of nitrogen (NO, NO₂, NOy), carbon monoxide (CO), and speciated air toxics. Urban background was estimated to contribute substantially (>70%) to EXT and CO, whereas BC, oxides of nitrogen (NOx) and toluene had comparably low background contributions (<30%). Mobile monitoring data were aggregated into 50 meter spatial medians by wind categories, with categories including low speed wind conditions (<0.5 m s⁻¹) and, for wind speeds above that threshold, by wind direction relative to the railyard. Spatial medians of different pollutants measured had a wide range of correlation—gas-phase air toxics (benzene, toluene, acetaldehyde) had moderate correlation with each other (r = 0.46–0.59) and between toluene and CO (r = 0.53), but lower correlation for other pairings. PN had highest correlation with oxides of nitrogen (r = 0.55–0.66), followed by BC (r = 0.4), and lower correlation with other pollutants. Multivariate regression analysis on the full set of 50 m medians found BC and NO as having the strongest relationship to railyard emissions, in comparison to their respective background levels. This was indicated by an increase associated with transiting through the yard and inverse relationship with distance from the railyard; NO and BC decreased by a factor of approximately 0.5 and 0.7 over 1 km distance of the railyard boundary, respectively. Low speed, variable wind conditions were related to higher concentrations of all measured parameters. Full article

(This article belongs to the Special Issue Near-Source Air Pollution)

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15 pages, 1809 KiB

Open AccessArticle

Disability Adjusted Life Years (DALYs) in Terms of Years of Life Lost (YLL) Due to Premature Adult Mortalities and Postneonatal Infant Mortalities Attributed to PM_2.5 and PM₁₀ Exposures in Kuwait

by Ali Al-Hemoud, Janvier Gasana, Abdullah N. Al-Dabbous, Ahmad Al-Shatti and Ahmad Al-Khayat

Int. J. Environ. Res. Public Health 2018, 15(11), 2609; https://doi.org/10.3390/ijerph15112609 - 21 Nov 2018

Cited by 38 | Viewed by 5841

Abstract

Ambient air pollution in terms of fine and coarse particulate matter (PM_2.5 and PM₁₀) has been shown to increase adult and infant mortalities. Most studies have estimated the risk of mortalities through attributable proportions and number of excess cases with no reference to the time lost due to premature mortalities. Disability adjusted life years (DALYs) are necessary to measure the health impact of Ambient particulate matter (PM) over time. In this study, we used life-tables for three years (2014–2016) to estimate the years of life lost (YLL), a main component of DALYs, for adult mortalities (age 30+ years) and postneonatal infant mortalities (age 28+ days–1 year) associated with PM_2.5 exposure and PM₁₀ exposure, respectively. The annual average of PM_2.5 and PM₁₀ concentrations were recorded as 87.9 μg/m³ and 167.5 μg/m³, which are 8 times greater than the World Health Organization (WHO) air quality guidelines of 10 μg/m³ and 20 μg/m³, respectively. Results indicated a total of 252.18 (95% CI: 170.69–322.92) YLL for all ages with an increase of 27,474.61 (95% CI: 18,483.02–35,370.58) YLL over 10 years. The expected life remaining (ELR) calculations showed that 30- and 65-year-old persons would gain 2.34 years and 1.93 years, respectively if the current PM_2.5 exposure levels were reduced to the WHO interim targets (IT-1 = 35 μg/m³). Newborns and 1-year old children may live 79.81 and 78.94 years, respectively with an increase in average life expectancy of 2.65 years if the WHO PM₁₀ interim targets were met (IT-1 = 70 μg/m³). Sensitivity analyses for YLL were carried out for the years 2015, 2025, and 2045 and showed that the years of life would increase significantly for age groups between 30 and 85. Life expectancy, especially for the elderly (≥60 years), would increase at higher rates if PM_2.5 levels were reduced further. This study can be helpful for the assessment of poor air quality represented by PM_2.5 and PM₁₀ exposures in causing premature adult mortalities and postneonatal infant mortalities in developing countries with high ambient air pollution. Information in this article adds insights to the sustainable development goals (SDG 3.9.1 and 11.6.2) related to the reduction of mortality rates attributed to ambient air levels of coarse and fine particulate matter. Full article

(This article belongs to the Special Issue Near-Source Air Pollution)

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