Source apportionment of indoor residential fine particulate matter using land use regression and constrained factor analysis

Source apportionment for indoor air pollution: Current challenges and future directions

Source apportionment (SA) for indoor air pollution is challenging due to the multiplicity and high variability of indoor sources, the complex physical and chemical processes that act as primary sources, sinks and sources of precursors that lead to secondary formation, and the interconnection with the outdoor environment. While the major indoor sources have been recognized, there is still a need for understanding the contribution of indoor versus outdoor-generated pollutants penetrating indoors, and how SA is influenced by the complex processes that occur in indoor environments. This paper reviews our current understanding of SA, through reviewing information on the SA techniques used, the targeted pollutants that have been studied to date, and their source apportionment, along with limitations or knowledge gaps in this research field. The majority (78 %) of SA studies to date focused on PM chemical composition/size distribution, with fewer studies covering organic compounds such as ketones, carbonyls and aldehydes. Regarding the SA method used, the majority of studies have used Positive Matrix Factorization (31 %), Principal Component Analysis (26 %) and Chemical Mass Balance (7 %) receptor models. The indoor PM sources identified to date include building materials and furniture emissions, indoor combustion-related sources, cooking-related sources, resuspension, cleaning and consumer products emissions, secondary-generated pollutants indoors and other products and activity-related emissions. The outdoor environment contribution to the measured pollutant indoors varies considerably (<10 %- 90 %) among the studies. Future challenges for this research area include the need for optimization of indoor air quality monitoring and data selection as well as the incorporation of physical and chemical processes in indoor air into source apportionment methodology.

Personal air pollution exposure and metals in the nasal epithelial lining fluid of COPD patients

Sampling of the nasal epithelial lining fluid is a potential method to assess exposure to air pollution within the respiratory tract among high risk populations. We investigated associations of short- and long-term particulate matter exposure (PM) and pollution-related metals in the nasal fluid of people with chronic obstructive pulmonary disease (COPD). This study included 20 participants with moderate-to-severe COPD from a larger study who measured long-term personal exposure to PM2.5 using portable air monitors and short-term PM2.5 and black carbon (BC) using in-home samplers for the seven days preceding nasal fluid collection. Nasal fluid was sampled from both nares by nasosorption, and inductively coupled plasma mass spectrometry was used to determine the concentration of metals with major airborne sources. Correlations of selected elements (Fe, Ba, Ni, Pb, V, Zn, Cu) were determined within the nasal fluid. Associations between personal long-term PM2.5 and seven day home PM2.5 and BC exposure and nasal fluid metal concentrations were determined by linear regression. Within nasal fluid samples, concentrations of vanadium and nickel (r = 0.8) and lead and zinc (r = 0.7) were correlated. Seven day and long-term PM2.5 exposure were both associated with higher levels of copper, lead, and vanadium in the nasal fluid. BC exposure was associated with higher levels of nickel in the nasal fluid. Levels of certain metals in the nasal fluid may serve as biomarkers of air pollution exposure in the upper respiratory tract.

A study to characterize the lead isotopic fingerprint in PM2.5 emitted from incense stick and cigarette burning

The incense sticks and cigarettes burning are key sources of particulate matter with a diameter of ≤ 2.5 μm (PM_2.5) in indoor and outdoor air. While lead (Pb) isotope ratios provide valuable insights into the origin of particle pollution, their applicability for investigating these source remains unclear. The Pb isotope ratios in the PM_2.5 emitted from these two sources were analyzed, and effects of brands or nicotine contents on the ratios were assessed. In addition, As, Cr, and Pb were analyzed to investigate whether Pb isotope ratios can serve as an indicator for the source investigation of these metals. We found that average ratios of ²⁰⁶Pb/²⁰⁴Pb, ²⁰⁶Pb/²⁰⁷Pb, and ²⁰⁸Pb/²⁰⁷Pb in cigarettes were heavier than those in incense sticks. Scatter plots of Pb isotope ratios indicated an overlap of values for incense sticks or cigarettes linked to different brands, in that ratios for cigarettes with high nicotine content were heavier than for those with low nicotine content. Scatter plots of As, Cr, or Pb concentration against Pb isotope ratios clearly distinguished the effects of cigarette burning versus incense sticks with respect to PM_2.5 of these metals. Results indicate that brand differences did not affect the determination of PM_2.5 in these two sources. We suggest that Pb isotope ratios can be a useful tool in investigating the influence of incense sticks and of cigarettes (with high or low nicotine content) burning to PM_2.5 and associated metals.

Indoor Exposure to Selected Air Pollutants in the Home Environment: A Systematic Review

(1) Background: There is increasing awareness that the quality of the indoor environment affects our health and well-being. Indoor air quality (IAQ) in particular has an impact on multiple health outcomes, including respiratory and cardiovascular illness, allergic symptoms, cancers, and premature mortality. (2) Methods: We carried out a global systematic literature review on indoor exposure to selected air pollutants associated with adverse health effects, and related household characteristics, seasonal influences and occupancy patterns. We screened records from six bibliographic databases: ABI/INFORM, Environment Abstracts, Pollution Abstracts, PubMed, ProQuest Biological and Health Professional, and Scopus. (3) Results: Information on indoor exposure levels and determinants, emission sources, and associated health effects was extracted from 141 studies from 29 countries. The most-studied pollutants were particulate matter (PM_2.5 and PM₁₀); nitrogen dioxide (NO₂); volatile organic compounds (VOCs) including benzene, toluene, xylenes and formaldehyde; and polycyclic aromatic hydrocarbons (PAHs) including naphthalene. Identified indoor PM_2.5 sources include smoking, cooking, heating, use of incense, candles, and insecticides, while cleaning, housework, presence of pets and movement of people were the main sources of coarse particles. Outdoor air is a major PM_2.5 source in rooms with natural ventilation in roadside households. Major sources of NO₂ indoors are unvented gas heaters and cookers. Predictors of indoor NO₂ are ventilation, season, and outdoor NO₂ levels. VOCs are emitted from a wide range of indoor and outdoor sources, including smoking, solvent use, renovations, and household products. Formaldehyde levels are higher in newer houses and in the presence of new furniture, while PAH levels are higher in smoking households. High indoor particulate matter, NO₂ and VOC levels were typically associated with respiratory symptoms, particularly asthma symptoms in children. (4) Conclusions: Household characteristics and occupant activities play a large role in indoor exposure, particularly cigarette smoking for PM_2.5, gas appliances for NO₂, and household products for VOCs and PAHs. Home location near high-traffic-density roads, redecoration, and small house size contribute to high indoor air pollution. In most studies, air exchange rates are negatively associated with indoor air pollution. These findings can inform interventions aiming to improve IAQ in residential properties in a variety of settings.

Chemical and stable isotopic characteristics of PM2.5 emitted from Chinese cooking

This study investigated the characteristics of air pollutants generated from preparing Chinese cuisine and analyzed the isotopic compositions of carbon and nitrogen in particulate matter with a diameter <2.5 μm (PM_2.5) to source apportionment study. The CO and CO₂ concentrations and temperatures were measured using suitable instruments in real time during cooking, including stir-fry, fry, deep-fry, hot-pot, and mixed cooking, and periods with non-cooking. Personal environmental monitoring instruments were used to collect PM_2.5 for carbon and nitrogen elements and isotopes analysis. Our data indicated that the concentrations of CO and CO₂ and the temperature were higher during periods of cooking, especially for the fry and stir-fry methods, than during periods with non-cooking. The concentrations of PM_2.5, total carbon, and total nitrogen were also higher during cooking; the maximum concentrations were measured during fry. The values of δ¹³C were considerably lower during the periods of cooking (mean: -28.15‰) than during non-cooking (-27.18‰). The average values of δ¹⁵N were 8.63‰ and 11.74‰ during deep-fry and hot-pot cooking, respectively. The δ¹³C values can be used to distinguish between cooking and other non-cooking sources and further assess the effect of different cooking activities on PM_2.5. The δ¹⁵N only can be used to investigate the effect of deep-fry on PM_2.5. Moreover, the δ¹³C signature suggested that fry emits higher products of incomplete combustion than do other cooking activities. These findings can assist in pollution source identification of PM_2.5, emission control, and the study of combustion characteristics.

Predictors of urban household variability of indoor PM2.5 in low socio-economic communities

In epidemiological studies, levels of PM2.5 need to be estimated over time and space. Because of logistical constraints, very few studies have been conducted to assess the variability within and across homes and the predictors of this variability. This study evaluated within- and between-home variability of indoor PM2.5 and identified predictors for PM2.5 in homes of mothers participating in the urban Mother and Child in the Environment birth cohort study in Durban, South Africa. Thirty homes were selected from 300 homes that were previously sampled for PM2.5. Two measurements of PM2.5 levels were conducted in each home within a 1 week interval in both warm and cold seasons (four samplings per home) using Airmetrics MiniVol samplers. A linear mixed-effect model was used to evaluate within- and between-home variability and to identify fixed effects (predictors) that result in reduced variability. The PM2.5 levels in the 30 homes ranged from 2 to 303 μg m-3. The within-home variability accounted for 94% of the total variability in the log-transformed PM2.5 levels for the 30 homes. The fixed effects extracted from the repeated samplings in the present study were used to improve a previously developed multivariable linear regression model for 300 homes, and thereby increased the R2 from 0.50 to 0.54. Inclusion of fixed-effects in multivariable linear regression models resulted in a reasonably robust model that can be used to predict PM2.5 levels in unmeasured homes of the cohort.

Indoor air sampling for fine particulate matter and black carbon in industrial communities in Pittsburgh

Impacts of industrial emissions on outdoor air pollution in nearby communities are well-documented. Fewer studies, however, have explored impacts on indoor air quality in these communities. Because persons in northern climates spend a majority of their time indoors, understanding indoor exposures, and the role of outdoor air pollution in shaping such exposures, is a priority issue. Braddock and Clairton, Pennsylvania, industrial communities near Pittsburgh, are home to an active steel mill and coke works, respectively, and the population experiences elevated rates of childhood asthma. Twenty-one homes were selected for 1-week indoor sampling for fine particulate matter (PM2.5) and black carbon (BC) during summer 2011 and winter 2012. Multivariate linear regression models were used to examine contributions from both outdoor concentrations and indoor sources. In the models, an outdoor infiltration component explained 10 to 39% of variability in indoor air pollution for PM2.5, and 33 to 42% for BC. For both PM2.5 models and the summer BC model, smoking was a stronger predictor than outdoor pollution, as greater pollutant concentration increases were identified. For winter BC, the model was explained by outdoor pollution and an open windows modifier. In both seasons, indoor concentrations for both PM2.5 and BC were consistently higher than residence-specific outdoor concentration estimates. Mean indoor PM2.5 was higher, on average, during summer (25.8±22.7 μg/m3) than winter (18.9±13.2 μg/m3). Contrary to the study's hypothesis, outdoor concentrations accounted for only little to moderate variability (10 to 42%) in indoor concentrations; a much greater proportion of PM2.5 was explained by cigarette smoking. Outdoor infiltration was a stronger predictor for BC compared to PM2.5, especially in winter. Our results suggest that, even in industrial communities of high outdoor pollution concentrations, indoor activities--particularly cigarette smoking--may play a larger role in shaping indoor exposures.

Modeling spatial effects of PM(2.5) on term low birth weight in Los Angeles County

Air pollution epidemiological studies suggest that elevated exposure to fine particulate matter (PM2.5) is associated with higher prevalence of term low birth weight (TLBW). Previous studies have generally assumed the exposure-response of PM2.5 on TLBW to be the same throughout a large geographical area. Health effects related to PM2.5 exposures, however, may not be uniformly distributed spatially, creating a need for studies that explicitly investigate the spatial distribution of the exposure-response relationship between individual-level exposure to PM2.5 and TLBW. Here, we examine the overall and spatially varying exposure-response relationship between PM2.5 and TLBW throughout urban Los Angeles (LA) County, California. We estimated PM2.5 from a combination of land use regression (LUR), aerosol optical depth from remote sensing, and atmospheric modeling techniques. Exposures were assigned to LA County individual pregnancies identified from electronic birth certificates between the years 1995-2006 (N=1,359,284) provided by the California Department of Public Health. We used a single pollutant multivariate logistic regression model, with multilevel spatially structured and unstructured random effects set in a Bayesian framework to estimate global and spatially varying pollutant effects on TLBW at the census tract level. Overall, increased PM2.5 level was associated with higher prevalence of TLBW county-wide. The spatial random effects model, however, demonstrated that the exposure-response for PM2.5 and TLBW was not uniform across urban LA County. Rather, the magnitude and certainty of the exposure-response estimates for PM2.5 on log odds of TLBW were greatest in the urban core of Central and Southern LA County census tracts. These results suggest that the effects may be spatially patterned, and that simply estimating global pollutant effects obscures disparities suggested by spatial patterns of effects. Studies that incorporate spatial multilevel modeling with random coefficients allow us to identify areas where air pollutant effects on adverse birth outcomes may be most severe and policies to further reduce air pollution might be most effective.

Prenatal Particulate Matter/Tobacco Smoke Increases Infants' Respiratory Infections: COCOA Study

Purpose

To investigate whether prenatal exposure to indoor fine particulate matter (PM_2.5) and environmental tobacco smoke (ETS) affects susceptibility to respiratory tract infections (RTIs) in infancy, to compare their effects between prenatal and postnatal exposure, and to determine whether genetic factors modify these environmental effects.

Methods

The study population consisted of 307 birth cohort infants. A diagnosis of RTIs was based on parental report of a physician's diagnosis. Indoor PM_2.5 and ETS levels were measured during pregnancy and infancy. TaqMan was used for genotyping of nuclear factor erythroid 2-related factor (Nrf2) (rs6726395), glutathione-S-transferase-pi (GSTP) 1 (rs1695), and glutathione-S-transferase-mu (GSTM) 1. Microarrays were used for genome-wide methylation analysis.

Results

Prenatal exposure to indoor PM_2.5 increased the susceptibility of lower RTIs (LRTIs) in infancy (adjusted odds ratio [aOR]=2.11). In terms of combined exposure to both indoor PM_2.5 and ETS, prenatal exposure to both pollutants increased susceptibility to LRTIs (aOR=6.56); however, this association was not found for postnatal exposure. The Nrf2 GG (aOR=23.69), GSTM1 null (aOR=8.18), and GSTP1 AG or GG (aOR=7.37) genotypes increased the combined LRTIs-promoting effects of prenatal exposure to the 2 indoor pollutants. Such effects of prenatal indoor PM_2.5 and ETS exposure were not found for upper RTIs.

Conclusions

Prenatal exposure to both indoor PM_2.5 and ETS may increase susceptibility to LRTIs. This effect can be modified by polymorphisms in reactive oxygen species-related genes.

A cross sectional analysis of behaviors related to operating gas stoves and pneumonia in U.S. children under the age of 5

Background

Poorly ventilated combustion stoves and pollutants emitted from combustion stoves increase the risk of acute lower respiratory illnesses (ALRI) in children living in developing countries but few studies have examined these issues in developed countries. Our objective is to investigate behaviors related to gas stove use, namely using them for heat and without ventilation, on the odds of pneumonia and cough in U.S. children.

Methods

The National Health and Nutrition Examination Survey (1988–1994) was used to identify children < 5 years who lived in homes with a gas stove and whose parents provided information on their behaviors when operating their gas stoves and data on pneumonia (N = 3,289) and cough (N = 3,127). Multivariate logistic regression models were used to examine the association between each respiratory outcome and using a gas stove for heat or without ventilation, as well as, the joint effect of both behaviors.

Results

The adjusted odds of parental-reported pneumonia (adjusted odds ratio [aOR] = 2.08, 95% confidence interval [CI]: 1.08, 4.03) and cough (aOR = 1.66, 95% CI: 1.14, 2.43) were higher among children who lived in homes where gas stoves were used for heat compared to those who lived in homes where gas stoves were only used for cooking. The odds of pneumonia (aOR = 1.76, 95% CI: 1.04, 2.98), but not cough (aOR = 1.23, 95% CI: 0.87, 1.75), was higher among those children whose parents did not report using ventilation when operating gas stoves compared to those who did use ventilation. When considering the joint association of both stove operating conditions, only children whose parents reported using gas stoves for heat without ventilation had significantly higher odds of pneumonia (aOR = 3.06, 95% CI: 1.32, 7.09) and coughing (aOR = 2.07, 95% CI: 1.29, 3.30) after adjusting for other risk factors.

Conclusions

Using gas stoves for heat without ventilation was associated with higher odds of pneumonia and cough among U.S. children less than five years old who live in homes with a gas stove. More research is needed to determine if emissions from gas stoves ventilation infrastructure, or modifiable behaviors contribute to respiratory infections in children.

Saturation sampling for spatial variation in multiple air pollutants across an inversion-prone metropolitan area of complex terrain

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. Street-level integrated samples of fine particulate matter (PM2.5), black carbon (BC), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) were collected during morning rush and probable inversion hours (6-11 AM), during summer and winter. We hypothesized that pollution concentrations would be: 1) higher under inversion conditions, 2) exacerbated in lower-elevation areas, and 3) vary by season.

RESULTS

During July - August 2011 and January - March 2012, we observed wide spatial and seasonal variability in pollution concentrations, exceeding the range measured at regulatory monitors. We identified elevated concentrations of multiple pollutants at lower-elevation sites, and a positive association between inversion frequency and NO2 concentration. We examined temporal adjustment methods for deriving seasonal concentration estimates, and found that the appropriate reference temporal trend differs between pollutants.

CONCLUSIONS

Our time-stratified spatial saturation approach found some evidence for modification of inversion-concentration relationships by topography, and provided useful insights for refining and interpreting GIS-based pollution source indicators for Land Use Regression modeling.

Fine particulate matter in the indoor air of barbeque restaurants: elemental compositions, sources and health risks

Cooking is a significant source of indoor particulate matter that can cause adverse health effects. In this study, a 5-stage cascade impactor was used to collect particulate matter from 14 restaurants that cooked with charcoal in Kocaeli, the second largest city in Turkey. A total of 24 elements were quantified using ICP-MS. All of the element contents except for Mn were higher for fine particles (PM2.5) than coarse particles (PM>2.5), and the major trace elements identified in the PM2.5 included V, Se, Zn, Cr, As, Cu, Ni, and Pb. Principle component analysis (PCA) and enrichment factor (EF) calculations were used to determine the sources of PM2.5. Four factors that explained over 77% of the total variance were identified by the PCA. These factors included charcoal combustion, indoor activities, crustal components, and road dust. The Se, As, Cd, and V contents in the PM2.5 were highly enriched (EF>100). The health risks posed by the individual metals were calculated to assess the potential health risks associated with inhaling the fine particles released during charcoal cooking. The total hazard quotient (total HQ) for a PM2.5 of 4.09 was four times greater than the acceptable limit (i.e., 1.0). In addition, the excess lifetime cancer risk (total ELCR) for PM2.5 was 1.57×10(-4), which is higher than the acceptable limit of 1.0×10(-6). Among all of the carcinogenic elements present in the PM2.5, the cancer risks resulting from Cr(VI) and As exposure were the highest (i.e., 1.16×10(-4) and 3.89×10(-5), respectively). Overall, these results indicate that the lifetime cancer risk associated with As and Cr(VI) exposure is significant at selected restaurants, which is of concern for restaurant workers.

Indoor residence times of semivolatile organic compounds: model estimation and field evaluation

Indoor residence times of semivolatile organic compounds (SVOCs) are a major and mostly unavailable input for residential exposure assessment. We calculated residence times for a suite of SVOCs using a fugacity model applied to residential environments. Residence times depend on both the mass distribution of the compound between the "mobile phase" (air and dust particles settled on the carpet) and the "non-mobile phase" (carpet fibers and pad) and the removal rates resulting from air exchange and cleaning. We estimated dust removal rates from cleaning processes using an indoor-particle mass-balance model. Chemical properties determine both the mass distribution and relative importance of the two removal pathways, resulting in different residence times among compounds. We conducted a field study after chlorpyrifos was phased out for indoor use in the United States in 2001 to determine the decreases in chlorpyrifos air concentrations over a one-year period. A measured average decrease of 18% in chlorpyrifos air concentrations indicates the residence time of chlorpyrifos is expected to be 6.9 years and compares well with model predictions. The estimates from this study provide the opportunity to make more reliable estimates of SVOCs exposure in the indoor residential environment.

Statistical approaches for identifying air pollutant mixtures associated with aircraft departures at Los Angeles International Airport

Aircraft departures emit multiple pollutants common to other near-airport sources, making it challenging to determine relative source contributions. While there may not be unique tracers of aircraft emissions, examination of multipollutant concentration patterns in combination with flight activity can facilitate source attribution. In this study, we examine concentrations of continuously monitored air pollutants measured in 2008 near a departure runway at Los Angeles International Airport (LAX), considering single-pollutant associations with landing and takeoff (LTO) of the aircraft (LTO activity, weighted by LTO cycle fuel burn), as well as multipollutant predictors of binary LTO activity. In the single-pollutant analyses, one-minute average concentrations of carbon monoxide, carbon dioxide, nitrogen oxides, and sulfur dioxide are positively associated with fuel burn-weighted departures on the runway proximate to the monitor, whereas ozone is negatively associated with fuel burn-weighted departures. In analyses in which the flight departure is predicted by pollutant concentrations, carbon dioxide and nitrogen oxides are the best individual predictors, but including all five pollutants greatly increases the power of prediction compared to single-pollutant models. Our results demonstrate that air pollution impacts from aircraft departures can be isolated using time-resolved monitoring data, and that combinations of simultaneously measured pollutants can best identify contributions from flight activity.