Publications by authors named "Michanowicz D"

Article Synopsis
  • Gas and propane stoves release nitrogen dioxide (NO) indoors, with unknown exposure levels across different U.S. demographic groups.
  • The average long-term NO exposure from these stoves is 4.0 parts per billion, potentially leading to about 50,000 pediatric asthma cases due to this exposure.
  • Smaller homes and certain racial/ethnic households experience disproportionately higher NO exposure compared to larger homes and the national average.
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Article Synopsis
  • - The review highlights the use of organosulfur compounds as odorants in natural gas to help detect leaks, but points out that there are currently no established regulatory exposure limits for these compounds.
  • - Analysis of 22 studies revealed that prolonged exposure to natural gas odorants is linked to various health symptoms like headaches, respiratory issues, and skin irritation, indicating potential health risks.
  • - The findings suggest the need for more detailed research on the health impacts of these odorants at lower exposure levels and recommend better practices for their use in natural gas.
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Exposure pathways to the carcinogen benzene are well-established from tobacco smoke, oil and gas development, refining, gasoline pumping, and gasoline and diesel combustion. Combustion has also been linked to the formation of nitrogen dioxide, carbon monoxide, and formaldehyde indoors from gas stoves. To our knowledge, however, no research has quantified the formation of benzene indoors from gas combustion by stoves.

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People living near oil and gas development are exposed to multiple environmental stressors that pose health risks. Some studies suggest these risks are higher for racially and socioeconomically marginalized people, which may be partly attributable to disparities in exposures. We examined whether racially and socioeconomically marginalized people in California are disproportionately exposed to oil and gas wells and associated hazards.

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The presence of hazardous air pollutants (HAPs) entrained in end-use natural gas (NG) is an understudied source of human health risks. We performed trace gas analyses on 185 unburned NG samples collected from 159 unique residential NG stoves across seven geographic regions in California. Our analyses commonly detected 12 HAPs with significant variability across region and gas utility.

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Hurricanes have caused major healthcare system disruptions. No systematic assessment of hurricane risk to United States hospital-based healthcare delivery has been performed. Here, we show that 25 of 78 metropolitan statistical areas (MSAs) on the United States Atlantic and Gulf Coasts have half or more of their hospitals at risk of flooding from relatively weak hurricanes.

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The presence of volatile organic compounds (VOCs) in unprocessed natural gas (NG) is well documented; however, the degree to which VOCs are present in NG at the point of end use is largely uncharacterized. We collected 234 whole NG samples across 69 unique residential locations across the Greater Boston metropolitan area, Massachusetts. NG samples were measured for methane (CH), ethane (CH), and nonmethane VOC (NMVOC) content (including tentatively identified compounds) using commercially available USEPA analytical methods.

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Scientific instrumentation driven by academic, military, and industrial applications tends to be high cost, designed for expert use, and "black boxed". Community-led citizen science (CLCS) is creating different research instruments with different measurement goals and processes. This paper identifies four design attributes for CLCS tools: affordability, accessibility, builds community efficacy and provides actionable data through validating a community method for monitoring the neurotoxic and corrosive gas Hydrogen Sulfide (HS).

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Fine particulate matter (PM) air pollution varies spatially and temporally in concentration and composition and has been shown to cause or exacerbate adverse effects on human and ecological health. Biomonitoring using airborne tree leaf deposition as a proxy for particulate matter (PM) pollution has been explored using a variety of study designs, tree species, sampling strategies, and analytical methods. In the USA, relatively few have applied these methods using co-located fine particulate measurements for comparison and relying on one tree species with extensive spatial coverage, to capture spatial variation in ambient air pollution across an urban area.

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Background: Spatially accurate population data are critical for determining health impacts from many known risk factors. However, the utility of the increasing spatial resolution of disease mapping and environmental exposures is limited by the lack of receptor population data at similar sub-census block spatial scales.

Methods: Here we apply an innovative method (Population Allocation by Occupied Domicile Estimation - ABODE) to disaggregate U.

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Land use regression (LUR) modeling has become a common method for predicting pollutant concentrations and assigning exposure estimates in epidemiological studies. However, few LUR models have been developed for metal constituents of fine particulate matter (PM) or have incorporated source-specific dispersion covariates in locations with major point sources. We developed hybrid AERMOD LUR models for PM, black carbon (BC), and steel-related PM constituents lead, manganese, iron, and zinc, using fine-scale air pollution data from 37 sites across the Pittsburgh area.

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Air pollution exposure characterization has been shaped by many constraints. These include technologies that lead to insufficient coverage across space and/or time in order to characterize individual or community-level exposures with sufficient accuracy and precision. However, there is now capacity for continuous monitoring of many air pollutants using comparatively inexpensive, real-time sensors.

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Health effects of fine particulate matter (PM) may vary by composition, and the characterization of constituents may help to identify key PM sources, such as diesel, distributed across an urban area. The composition of diesel particulate matter (DPM) is complicated, and elemental and organic carbon are often used as surrogates. Examining multiple elemental and organic constituents across urban sites, however, may better capture variation in diesel-related impacts, and help to more clearly separate diesel from other sources.

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Despite advances in monitoring and modelling of intra-urban variation in multiple pollutants, few studies have attempted to separate spatial patterns by time of day, or incorporated organic tracers into spatial monitoring studies. Due to varying emissions sources from diesel and gasoline vehicular traffic, as well as within-day temporal variation in source mix and intensity (e.g.

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Sustainability challenges for nature and people are complex and interconnected, such that effective solutions require approaches and a common theory of change that bridge disparate disciplines and sectors. Causal chains offer promising approaches to achieving an integrated understanding of how actions affect ecosystems, the goods and services they provide, and ultimately, human well-being. Although causal chains and their variants are common tools across disciplines, their use remains highly inconsistent, limiting their ability to support and create a shared evidence base for joint actions.

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Article Synopsis
  • Capturing diesel pollution in urban areas is complex due to varying sources and a lack of effective pollution tracers.
  • The study analyzed air quality in downtown Pittsburgh by using a GIS approach to select 36 sampling sites, collecting fine particulate matter data across different seasons and times, while associating pollution levels with traffic density and bus routes.
  • Results revealed significant spatial variations in pollutants, with higher concentrations of fine particulate matter and black carbon found closer to the downtown core, indicating strong relationships between pollution levels and urban traffic patterns.
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Fine particulate matter (PM2.5) air pollution, varying in concentration and composition, has been shown to cause or exacerbate adverse effects on both human and ecological health. The concept of biomonitoring using deciduous tree leaves as a proxy for intraurban PM air pollution in different areas has previously been explored using a variety of study designs (e.

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Health effects of fine particulate matter (PM2.5) vary by chemical composition, and composition can help to identify key PM2.5 sources across urban areas.

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The causes of autism spectrum disorder (ASD) are not well known. Recent investigations have suggested that air pollution, including PM2.5, may play a role in the onset of this condition.

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A growing literature explores intra-urban variation in pollution concentrations. Few studies, however, have examined spatial variation during "peak" hours of the day (e.g.

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Background: Characterizing intra-urban variation in air quality is important for epidemiological investigation of health outcomes and disparities. To date, however, few studies have been designed to capture spatial variation during select hours of the day, or to examine the roles of meteorology and complex terrain in shaping intra-urban exposure gradients.

Methods: We designed a spatial saturation monitoring study to target local air pollution sources, and to understand the role of topography and temperature inversions on fine-scale pollution variation by systematically allocating sampling locations across gradients in key local emissions sources (vehicle traffic, industrial facilities) and topography (elevation) in the Pittsburgh area.

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