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

Source contributions to urban fine particulate matter (PM(2.5) ) have been modelled using land use regression (LUR) and factor analysis (FA). However, people spend more time indoors, where these methods are less explored. We collected 3-4- day samples of nitrogen dioxide and PM(2.5) inside and outside of 43 homes in summer and winter, 2003-2005, in and around Boston, Massachusetts. Particle filters were analysed for black carbon and trace element concentrations using reflectometry, X-ray fluorescence (XRF), and high-resolution inductively coupled mass spectrometry (ICP-MS). We regressed indoor against outdoor concentrations modified by ventilation, isolating the indoor-attributable fraction, and then applied constrained FA to identify source factors in indoor concentrations and residuals. Finally, we developed LUR predictive models using GIS-based outdoor source indicators and questionnaire data on indoor sources. FA using concentrations and residuals reasonably separated outdoor (long-range transport/meteorology, fuel oil/diesel, road dust) from indoor sources (combustion, smoking, cleaning). Multivariate LUR regression models for factors from concentrations and indoor residuals showed limited predictive power, but corroborated some indoor and outdoor factor interpretations. Our approach to validating source interpretations using LUR methods provides direction for studies characterizing indoor and outdoor source contributions to indoor cocentrations. PRACTICAL IMPLICATIONS: By merging indoor-outdoor modeling, factor analysis, and LUR-style predictive regression modeling, we have added to previous source apportionment studies by attempting to corroborate factor interpretations. Our methods and results support the possibility that indoor exposures may be modeled for epidemiologic studies, provided adequate sample size and variability to identify indoor and outdoor source contributions. Using these techniques, epidemiologic studies can more clearly examine exposures to indoor sources and indoor penetration of source-specific components, reduce exposure misclassification, and improve the characterization of the relationship between particle constituents and health effects.     

Source apportionment of human personal exposure to volatile organic compounds in homes, offices and outdoors by chemical mass balance and genetic algorithm receptor models

A number of past studies have shown the prevalence of a considerable amount of volatile organic compounds (VOCs) in workplace, home and outdoor microenvironments. The quantification of an individual's personal exposure to VOCs in each of these microenvironments is an essential task to recognize the health risks. In this paper, such a study of source apportionment of the human exposure to VOCs in homes, offices, and outdoors has been presented. Air samples, analysed for 25 organic compounds and sampled during one week in homes, offices, outdoors and close to persons, at seven locations in the city of Leipzig, have been utilized to recognize the concentration pattern of VOCs using the chemical mass balance (CMB) receptor model. In result, the largest contribution of VOCs to the personal exposure is from homes in the range of 42 to 73%, followed by outdoors, 18 to 34%, and the offices, 2 to 38% with the corresponding concentration ranges of 35 to 80 microg m(- 3), 10 to 45 microg m(- 3) and 1 to 30 microg m(- 3) respectively. The species such as benzene, dodecane, decane, methyl-cyclopentane, triethyltoluene and trichloroethylene dominate outdoors; methyl-cyclohexane, triethyltoluene, nonane, octane, tetraethyltoluene, undecane are highest in the offices; while, from the terpenoid group like 3-carane, limonene, a-pinene, b-pinene and the aromatics toluene and styrene most influence the homes. A genetic algorithm (GA) model has also been applied to carry out the source apportionment. Its results are comparable with that of CMB.     

Levels of heavy metals in outdoor and indoor dusts in Muscat,Oman

The concentrations of lead, copper, nickel, zinc and chromium in outdoor and indoor dusts collected from different sites in Muscat, Oman, were determined by flame atomic absorption. Results showed a wide range of concentrations, the means in the outdoor dust being, 65?±?50, 124?±?316, 47?±?45, 930?±?666 and 64?±?26 mg kg^??1 for lead, zinc, copper, nickel and chromium, respectively. The 2001 Omani phasing out of leaded fuel resulted in low levels of lead in outdoor dust compared to those reported in the literature. Outstanding was the high nickel concentration in outdoor dust when compared to that in the literature, the reason being natural soil pollution due to the local geology of the northern parts of Oman. The concentrations of chromium, copper and zinc are lower than or comparable to these in other cities around the world. The results also showed that the industrial activities in Muscat do not contribute significantly to metal pollution in street dusts.

On the other hand, the mean concentrations of lead, zinc, copper, nickel and chromium in indoor dust were 108?±?65, 753?±?1162, 108?±?91, 130?±?125 and 34?±?14 mg kg^??1, respectively. In general, zinc and nickel levels are higher than those reported in the literature while lead, copper and chromium levels are lower or comparable.

When outdoor and indoor dusts were correlated, the ratios between indoor–outdoor mean concentrations revealed that lead, zinc, and copper were generated internally, while nickel and chromium were from external sources.     

Physico-chemical characterization of indoor/outdoor particulate matter in two residential houses in Oslo, Norway: measurements overview and physical properties--URBAN-AEROSOL Project

Indoor/outdoor measurements have been performed in the Oslo metropolitan area during summer and winter periods (2002-2003) at two different residential houses. The objective of the measurement study was to characterize, physically and chemically, the particulate matter (PM) and gaseous pollutants associated with actual human exposure in the selected places, and their indoor/outdoor relationship. In this paper, we focus on the PM measurements and examine the relationship between the indoor and outdoor PM concentrations taking into account the ventilation rate, indoor sources and meteorological conditions. The indoor/outdoor measurements indicate the important contribution of the outdoor air to the indoor air quality and the influence of specific indoor sources such as smoking and cooking to the concentration of PM inside houses. However, no specific correlation was found between the indoor/outdoor concentration ratio and the meteorological parameters. This study provides information on the physical characteristics and the relationship of indoor to outdoor concentration of particulate matter in residential houses. Moreover, the parameters that influence this relationship are discussed. The results presented here are specific to the sampled houses and conditions used and provide data on the actual human exposure characteristics which occur in the spatial and temporal scales of the present study.     

Concentrations of Volatile Organic Compounds in Indoor Air – A Review

A review is presented of investigations of volatile organic compound (VOC) concentrations in indoor air of buildings of different classifications (dwellings, offices, schools, hospitals) and categories (established, new and complaint buildings). Measured concentrations obtained from the published literature and from research in progress overseas were pooled so that VOC concentration profiles could be derived for each building classification/category. Mean concentrations of individual compounds in established buildings were found to be generally below 50 μg/m³, with most below 5 μg/m³. Concentrations in new buildings were much greater, often by an order of magnitude or more, and appeared to arise from construction materials and building contents. The nature of these sources and approaches to reduce indoor air concentrations by limiting source VOC emissions is discussed. Total VOC (TVOC) concentrations were substantially higher than concentrations of any individual VOCs in all situations, reflecting the large number of compounds present, but interpretation of such measurements was limited by the lack of a common definition for TVOC relevant to occupant exposure.     

Size distribution and source apportionment of polycyclic aromatic hydrocarbons (PAHs) in aerosol particle samples from the atmospheric environment of Delhi, India

Ambient aerosol particles were collected using a five-stage impactor at six different sites in Delhi. The impactor segregates the TSPM into five different sizes (viz. > 10.9, 10.9-5.4, 5.4-1.6, 1.6-0.7, and < 0.7 μm). Samples collected were chemically analyzed for all the five size ranges, for the estimation of 16 different PAHs. The particle size distribution of PAHs was observed to be unimodal in nature with the highest peak towards the smallest size aerosol particle (< 0.7 μm). The five size ranges were categorized into two broad categories viz. coarse (> 10.9 + 10.9 to 5.4 + 5.4 to 1.6 μm) and fine (1.6 to 0.7 + < 0.7 μm). It was observed that the dominant PAHs found were pyrene, benzo(a)pyrene, benzo(ghi)perylene and benzo(b)fluoranthene for both the coarse and fine fractions. Source apportionment of polycyclic aromatic hydrocarbons (PAHs) has been carried out using principal component analysis method (PCA) in both coarse and fine size modes. The major sources identified in this study, responsible for the elevated concentration of PAHs in Delhi, are vehicular emission and coal combustion. Some contribution from biomass burning was also observed.     

Sources and concentrations of indoor nitrogen dioxide in Hamburg (west Germany) and Erfurt (east Germany)

Here we report indoor and outdoor concentrations of NO2 for Erfurt and Hamburg and assess the contribution of the most important indoor sources (e.g. the presence of gas cooking ranges, smoking) and outdoor sources (traffic exhaust emissions). We examined the relative contribution of the different sources of NO2 to the total indoor NO2 levels in Erfurt and Hamburg. NO2 indoor concentrations in Hamburg were slightly higher than those in Erfurt (i.e. living room: 15 microg m(-3) for Erfurt and 17 microg m(-3) for Hamburg). A linear regression model including the variables, place of residence, season and outdoor NO2 levels, location of the home within the city, housing and occupant characteristics accounted for 38% of the NO2 variance. The most important predictors of indoor NO2 concentrations were gas in cooking followed by other characteristics, such as ventilation or outdoor NO2 level. Residences in which gas was used for cooking, or in which occupants smoked, had substantially higher indoor NO2 concentrations (41 or 18% increase, respectively). An increase in the outdoor NO2 concentration from the 25th to the 75th-percentile (17 microg m(-3)) was associated with a 33% increase in the living room NO2 concentration. Multiple regression analysis for both cities separately illustrated that use of gas for cooking was the major indoor source of NO2. This variable caused a similar increase in the indoor NO2 levels in each city (43% in Erfurt and 47% in Hamburg). However, outdoor sources of NO2 (motor vehicle traffic) contributed more to indoor NO2 levels in Hamburg than in Erfurt.     

Receptor modeling of PM2.5, PM10 and TSP in different seasons and long-range transport analysis at a coastal site of Tianjin, China

Atmospheric particulate matter (PM_2.5, PM₁₀ and TSP) were sampled synchronously during three monitoring campaigns from June 2007 to February 2008 at a coastal site in TEDA of Tianjin, China. Chemical compositions including 19 elements, 6 water-solubility ions, organic and elemental carbon were determined. principle components analysis (PCA) and chemical mass balance modeling (CMB) were applied to determine the PM sources and their contributions with the assistance of NSS SO₄²⁻, the mass ratios of NO₃⁻ to SO₄²⁻ and OC to EC. Air mass backward trajectory model was compared with source apportionment results to evaluate the origin of PM. Results showed that NSS SO₄²⁻ values for PM_2.5 were 2147.38, 1701.26 and 239.80 ng/m³ in summer, autumn and winter, reflecting the influence of sources from local emissions. Most of it was below zero in summer for PM₁₀ indicating the influence of sea salt. The ratios of NO₃⁻ to SO₄²⁻ was 0.19 for PM_2.5, 0.18 for PM₁₀ and 0.19 for TSP in winter indicating high amounts of coal consumed for heating purpose. Higher OC/EC values (mostly larger than 2.5) demonstrated that secondary organic aerosol was abundant at this site. The major sources were construction activities, road dust, vehicle emissions, marine aerosol, metal manufacturing, secondary sulfate aerosols, soil dust, biomass burning, some pharmaceutics industries and fuel-oil combustion according to PCA. Coal combustion, marine aerosol, vehicular emission and soil dust explained 5-31%, 1-13%, 13-44% and 3-46% for PM_2.5, PM₁₀ and TSP, respectively. Backward trajectory analysis showed air parcels originating from sea accounted for 39% in summer, while in autumn and winter the air parcels were mainly related to continental origin.     

Toxicity and elemental composition of particulate matter from outdoor and indoor air of elementary schools in Munich, Germany

Outdoor particulate matter (PM(10)) is associated with detrimental health effects. However, individual PM(10) exposure occurs mostly indoors. We therefore compared the toxic effects of classroom, outdoor, and residential PM(10). Indoor and outdoor PM(10) was collected from six schools in Munich during teaching hours and in six homes. Particles were analyzed by scanning electron microscopy and X-ray spectroscopy (EDX). Toxicity was evaluated in human primary keratinocytes, lung epithelial cells and after metabolic activation by several human cytochromes P450. We found that PM(10) concentrations during teaching hours were 5.6-times higher than outdoors (117 ± 48 μg/m(3) vs. 21 ± 15 μg/m(3), P < 0.001). Compared to outdoors, indoor PM contained more silicate (36% of particle number), organic (29%, probably originating from human skin), and Ca-carbonate particles (12%, probably originating from paper). Outdoor PM contained more Ca-sulfate particles (38%). Indoor PM at 6 μg/cm(2) (10 μg/ml) caused toxicity in keratinocytes and in cells expressing CYP2B6 and CYP3A4. Toxicity by CYP2B6 was abolished with the reactive oxygen species scavenger N-acetylcysteine. We concluded that outdoor PM(10) and indoor PM(10) from homes were devoid of toxicity. Indoor PM(10) was elevated, chemically different and toxicologically more active than outdoor PM(10). Whether the effects translate into a significant health risk needs to be determined. Until then, we suggest better ventilation as a sensible option. PRACTICAL IMPLICATIONS: Indoor air PM(10) on an equal weight base is toxicologically more active than outdoor PM(10). In addition, indoor PM(10) concentrations are about six times higher than outdoor air. Thus, ventilation of classrooms with outdoor air will improve air quality and is likely to provide a health benefit. It is also easier than cleaning PM(10) from indoor air, which has proven to be tedious.     

Characterizations,relationship, and potential sources of outdoor and indoor particulate matter bound polycyclic aromatic hydrocarbons (PAHs) in a community of Tianjin,Northern China

Polycyclic aromatic hydrocarbons (PAHs) are among the most toxic air pollutants in China. However, because there are unsubstantial data on indoor and outdoor particulate PAHs, efforts in assessing inhalation exposure and cancer risk to PAHs are limited in China. This study measured 12 individual PAHs in indoor and outdoor environments at 36 homes during the non‐heating period and heating period in 2009. Indoor PAH concentrations were comparable with outdoor environments in the non‐heating period, but were lower in the heating period. The average indoor/outdoor ratios in both sampling periods were lower than 1, while the ratios in the non‐heating period were higher than those in the heating period. Correlation analysis and coefficient of divergence also verified the difference between indoor and outdoor PAHs, which could be caused by high ventilation in the non‐heating period. To support this conclusion, linear and robust regressions were used to estimate the infiltration factor to compare outdoor PAHs to indoor PAHs. The calculated infiltration factors obtained by the two models were similar in the non‐heating period but varied greatly in the heating period, which may have been caused by the influence of ventilation. Potential sources were distinguished using a diagnostic ratio and a mixture of coal combustion and traffic emission, which are major sources of PAHs.     

Volatile organic compounds, polycyclic aromatic hydrocarbons and elements in the air of ten urban homes

Ten homes were monitored at regular intervals from June 1994 through April 1995 as part of a Public Health Assessment in Southeast Chicago for exposure to volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), and elements. Simultaneous 24-h indoor and outdoor samples were collected. VOCs were and analyzed using USEPA Method TO-14 with Selected Ion Monitoring Mass Spectrometry (GC/MS). PAHs were analyzed using USEPA Method TO-13 with GC/MS. Elements were collected on quartz fiber filters and analyzed by Inductively Coupled Argon Plasma (ICP) spectroscopy or Graphite Furnace Atomic Absorption (GFAA). Continuous measurements of CO2 and temperature were recorded for each indoor sample. Twenty-four h total CO2 emissions were determined from occupancy and estimated gas stove usage and were moderately correlated (R2 = 0.19) with 24 h average indoor CO2 concentrations. Modeled 24-h air exchange rates ranged from 0.04 to 3.76 air changes h-1 (ACH), with mean of 0.52 ACH. Median particle penetration was 0.89. Emission rates were calculated for each pollutant sampled. Using a detailed housing survey and field sampling questionnaires, it was possible to evaluate associations between housing characteristics and source activities, and pollutant source rates. The data indicate that several predictor variables, including mothball storage, air freshner use, and cooking activities, are reasonable predictors for emission rates for specific pollutants in the homes studied.     

Reduction in personal exposures to particulate matter and carbon monoxide as a result of the installation of a Patsari improved cook stove in Michoacan Mexico

The impact of an improved wood burning stove (Patsari) in reducing personal exposures and indoor concentrations of particulate matter (PM(2.5)) and carbon monoxide (CO) was evaluated in 60 homes in a rural community of Michoacan, Mexico. Average PM(2.5) 24-h personal exposure was 0.29 mg/m(3) and mean 48-h kitchen concentration was 1.269 mg/m(3) for participating women using the traditional open fire (fogon). If these concentrations are typical of rural conditions in Mexico, a large fraction of the population is chronically exposed to levels of pollution far higher than ambient concentrations found by the Mexican government to be harmful to human health. Installation of an improved Patsari stove in these homes resulted in 74% reduction in median 48-h PM(2.5) concentrations in kitchens and 35% reduction in median 24-h PM(2.5) personal exposures. Corresponding reductions in CO were 77% and 78% for median 48-h kitchen concentrations and median 24-h personal exposures, respectively. The relationship between reductions in median kitchen concentrations and reductions in median personal exposures not only changed for different pollutants, but also differed between traditional and improved stove type, and by stove adoption category. If these reductions are typical, significant bias in the relationship between reductions in particle concentrations and reductions in health impacts may result, if reductions in kitchen concentrations are used as a proxy for personal exposure reductions when evaluating stove interventions. In addition, personal exposure reductions for CO may not reflect similar reductions for PM(2.5). This implies that PM(2.5) personal exposure measurements should be collected or indoor measurements should be combined with better time-activity estimates, which would more accurately reflect the contributions of indoor concentrations to personal exposures. PRACTICAL IMPLICATIONS: Installation of improved cookstoves may result in significant reductions in indoor concentrations of carbon monoxide and fine particulate matter (PM(2.5)), with concurrent but lower reductions in personal exposures. Significant errors may result if reductions in kitchen concentrations are used as a proxy for personal exposure reductions when evaluating stove interventions in epidemiological investigations. Similarly, time microenvironment activity models in these rural homes do not provide robust estimates of individual exposures due to the large spatial heterogeneity in pollutant concentrations and the lack of resolution of time activity diaries to capture movement through these microenvironments.     

Daily concentrations of trace metals in aerosols in Beijing, China, determined by using inductively coupled plasma mass spectrometry equipped with laser ablation analysis, and source identification of aerosols

This paper describes the daily concentrations of trace metals and ionic constituents in the aerosol of Beijing, China from March 2001 to August 2003. Daily PM10 concentrations were also measured from September 2001 to August 2003. The daily average PM10 concentration at Beijing, China from September 2001 to August 2003 was 171+/-117 microg m(-3) (n = 673), which is 5-fold higher than at Yokohama, Japan. Trace metal concentrations were analyzed by using inductively coupled plasma mass spectrometry equipped with a laser ablation sample introduction (LA/ICP-MS), which is a rapid and simultaneous method for multi-element analysis. The daily average metal concentrations in TSP in Beijing from March 2001 to August 2003 were: Al: 3.5+/-2.4 (n = 727), Ti: 0.47+/-0.35 (n = 720), V: 0.013+/-0.010 (n = 716), Cr: 0.019+/-0.015 (n = 618), Mn: 0.24+/-0.16 (n = 730), Fe: 5.5+/-3.9 (n = 728), Co: 0.0046+/-0.0055 (n = 629), Ni: 0.022+/-0.024 (n = 680), Cu: 0.11+/-0.11 (n = 660), Zn: 0.77+/-0.60 (n = 726), As: 0.048+/-0.047 (n = 731), Se: 0.010+/-0.010 (n = 550), Cd: 0.0068+/-0.0082 (n = 709), Sb: 0.033+/-0.036 (n = 687), and Pb: 0.43+/-0.50 (n = 728) (unit, microg m(-3)). All the metal concentrations in TSP in Beijing, China were 1.7-21.8 times higher than those in TSP in the center of Tokyo, Japan. Notably, As concentrations in TSP in Beijing were 20-fold higher than those in Tokyo. Source identification of aerosols in Beijing was carried out by using the chemical mass balance (CMB) receptor model, with the daily concentration of metals in the aerosol. The major primary sources of the aerosol of Beijing were considered to be soil dust and coal combustion. Vehicle exhaust contribution tended to increase.