Indoor Samples Research Articles

Indoor source apportionment in urban communities near industrial sites

Because fine particulate matter (PM2.5) differs in chemical composition, source apportionment is frequently used for identification of relative contributions of multiple sources to outdoor concentrations. Indoor air pollution and source apportionment is often overlooked, though people in northern climates may spend up to 90% of their time inside. We selected 21 homes for a 1-week indoor sampling session during summer (July to September 2011), repeated in winter (January to March 2012). Elemental analysis was performed using inductively-coupled plasma mass spectrometry (ICP-MS), and factor analysis was used to determine constituent grouping. Multivariate modeling was run on factor scores to corroborate interpretations of source factors based on a literature review. For each season, a 5-factor solution explained 86–88% of variability in constituent concentrations. Indoor sources (i.e. cooking, smoking) explained greater variability than did outdoor sources in these industrial communities. A smoking factor was identified in each season, predicted by number of cigarettes smoked. Cooking factors were also identified in each season, explained by frequency of stove cooking and stovetop frying. Significant contributions from outdoor sources including coal and motor vehicles were also identified. Higher coal and secondary-related elemental concentrations were detected during summer than winter. Our findings suggest that source contributions to indoor concentrations can be identified and should be examined in relation to health effects.

Distribution patterns, infiltration and health risk assessment of PM2.5-bound PAHs in indoor and outdoor air in cold zone

In this study we investigated the distribution patterns, infiltration and health risk assessment of PM2.5-bound PAHs in indoor and outdoor air done in Harbin city, northeastern China. Simultaneous indoor and outdoor sampling was done to collect 264 PM2.5 samples from four sites during winter, summer, and spring. Infiltration of PAHs into indoors was estimated using Retene, Benzo [ghi]perylene and Chrysene as reference compounds, where the latter compound was suggested to be a good estimator and subsequently used for further calculation of infiltration factors (IFs). Modeling with positive matrix factorization (PMF5) and estimation of diagnostic isomeric ratios were applied for identifying sources, where coal combustion, crop residues burning and traffic being the major contributors, particularly during winter. Linear discriminant analysis (LDA) has been utilized to show the distribution patterns of individual PAH congeners. LDA showed that, the greatest seasonal variability was attributed to high molecular weight compounds (HMW PAHs). Potential health risk of PAHs exposure was assessed through relative potency factor approach (RPF). The levels of the sum of 16 US EPA priority PAHs during colder months were very high, with average values of 377 ± 228 ng m−3 and 102 ± 75.8 ng m−3, for the outdoors and indoors, respectively. The outdoor levels reported to be 19 times higher than the outdoor concentrations during warmer months (summer + spring), while the indoor concentrations were suggested to be 9 times and 10 times higher than that for indoor summer (average 11.73 ± 4 ng m−3) and indoor spring (9.5 ± 3.3 ng m−3). During nighttime, outdoor PAHs revealed wider range of values compared to datytime which was likely due to outdoor temperature, a weather parameter with the strongest negative influence on ∑16PAHs compared to low impact of relative humidity and wind speed.

A rapid method for the analysis of methyl dihydrojasmonate and galaxolide in indoor and outdoor air particulate matter

A method for the analysis of methyl dihydrojasmonate (MHDJ) in air particulate matter (PM1 and PM2.5) is described for the first time. This fragrance is determined together galaxolide (HHCB). Airborne particles were collected by filtration of air volumes between 100 and 1000m3. Recovery efficiencies of filter extraction with Soxhlet and pressurized liquids were evaluated. The method included reaction with BSTFA:TMCS for generation of trimethylsilyloxy derivatives which prevented deleterious effects in the gas capillary column by interaction of hydroxyl groups from air constituents other than these fragrances. This step avoided the use of additional clean up methods such as liquid column chromatography affording direct quantification by GC-EI-MS. The proposed method had enough sensitivity for quantification of these fragrances in indoor and outdoor environmental samples using small aliquots of the PM extracts, e.g. 2.5%, and therefore saving sample material for eventual determination of other compounds. The detection limits were 0.03ng and 0.01ng for MHDJ and HHCB, respectively.Both MHDJ and HHCB were predominantly found in the smallest PM fraction analyzed (<0.5μm). The outdoor concentrations were highest in busy urban streets. However, indoor levels in school classrooms and subway stations were one order of magnitude higher than those observed outdoor. This difference was consistent with the use of these compounds as additives in cleaning and personal care products and the small dispersion of these fragrances in indoor environments. Information on the occurrence of this and other fragrances is needed to increase the understanding on the influence of anthropogenic activities in the formation of organic aerosols and source apportionment.

Short-term dynamics of indoor and outdoor endotoxin exposure: Case of Santiago, Chile, 2012

Indoor and outdoor endotoxin in PM2.5 was measured for the very first time in Santiago, Chile, in spring 2012. Average endotoxin concentrations were 0.099 and 0.094 [EU/m3] for indoor (N=44) and outdoor (N=41) samples, respectively; the indoor–outdoor correlation (log-transformed concentrations) was low: R=−0.06, 95% CI: (−0.35 to 0.24), likely owing to outdoor spatial variability.A linear regression model explained 68% of variability in outdoor endotoxins, using as predictors elemental carbon (a proxy of traffic emissions), chlorine (a tracer of marine air masses reaching the city) and relative humidity (a modulator of surface emissions of dust, vegetation and garbage debris). In this study, for the first time a potential source contribution function (PSCF) was applied to outdoor endotoxin measurements. Wind trajectory analysis identified upwind agricultural sources as contributors to the short-term, outdoor endotoxin variability. Our results confirm an association between combustion particles from traffic and outdoor endotoxin concentrations.For indoor endotoxins, a predictive model was developed but it only explained 44% of endotoxin variability; the significant predictors were tracers of indoor PM2.5 dust (Si, Ca), number of external windows and number of hours with internal doors open. Results suggest that short-term indoor endotoxin variability may be driven by household dust/garbage production and handling. This would explain the modest predictive performance of published models that use answers to household surveys as predictors. One feasible alternative is to increase the sampling period so that household features would arise as significant predictors of long-term airborne endotoxin levels.

Distribution of legacy and emerging semivolatile organic compounds in five indoor matrices in a residential environment

Seven types of indoor samples, covering five indoor matrices, were collected in a residential room, and analyzed for five classes of semivolatile organic compounds (SVOCs). The goal was to improve the understanding of the relationship between indoor air, surface films and dust, based on differences in sources, physicochemical properties, and indoor environmental characteristics. Comparisons of the five matrices (gas- and particle-phase air, floor dust, surface dust/films and window films) demonstrated that within our test room a semi-quantitative measurement of the SVOC distributions and concentrations could be obtained by air, and composite dust or furniture surface wipes. Dust concentrations varied within the room, and spot samples were not necessarily representative of the average room conditions.Polyurethane foam passive air samplers (PUF-PAS) successfully quantified the total air concentrations of the studied SVOC compound groups, as indoor air concentrations were dominated by gas-phase compounds, however air concentrations of individual particle-bound compounds had higher uncertainty. Measured concentrations of dust/surfaces could be used to estimate air concentrations of legacy SVOCs, demonstrating equilibrium in the room. However, air concentrations of current-use compounds (flame retardants, polycyclic aromatic hydrocarbons (PAHs)) could not be estimated from dust/surface concentrations, demonstrating the influence of ongoing primary emissions and non-equilibrium status in the room.

Estimation of sources and factors affecting indoor VOC levels using basic numerical methods

Volatile Organic Compounds (VOCs) are a concern due to their adverse health effects and extensive usage. Levels of indoor VOCs were measured in six homes located in three different towns in Canakkale, Turkey. Monthly indoor VOC samples were collected by passive sampling throughout a year. The highest levels of total volatile organic compounds (TVOC), benzene, toluene, and xylenes occurred in industrial, rural, and urban sites in a descending order. VOC levels were categorized as average values annually, during the heating period, and non-heating period. Several building/environmental factors together with occupants’ habits were scored to obtain a basic indoor air pollution index (IAPi) for the homes. Bivariate regression analysis was applied to find the associations between the pollutant levels and home scores. IAPi scores were found to be correlated with average indoor VOC levels. In particular, very strong associations were found for occupants’ habits. Furthermore, observed indoor VOC levels were categorized by using self-organizing map (SOM) and two simple scoring approaches, rounded average and maximum value methods, to classify the indoor environments based on their VOC compositions (IAPvoc). Three classes were used for both IAPi and IAPvoc approaches, namely “good”, “moderate”, and “bad”. There is an urgent need for indexing studies to determine the potential sources and/or factors affecting observed VOCs. This study gives a basic but good start for further studies.

Determination of the personal, indoor and outdoor exposure levels of inorganic gaseous pollutants in different microenvironments in an industrial city.

We measured SO2, NO2 and O3 concentrations during the summer and winter in Kocaeli, Turkey. The sampling was carried out indoors and outdoors at homes, schools and offices. Personal samplers were also used to determine personal exposures to these pollutants. High NO2 and SO2 concentrations were observed in outdoor samples collected close to locations characterized by heavy urban traffic. Concentrations of O3, on the other hand, were higher in rural areas around the city due to ozone distillation. For both sampling periods, the concentrations of outdoor SO2 and O3 were higher than for indoor and personal samples; however, the NO2 concentrations were higher in indoor and personal samples, indicating that outdoor sources significantly contribute to indoor SO2 and O3 levels and that indoor NO2 concentrations are primarily modulated by sources within buildings. Seasonal variations in pollutant concentrations showed statistically significant differences. Indoor and outdoor concentrations of NO2 and SO2 measured in the winter were higher than the levels measured in the summer; O3 concentrations, on the other hand, exhibited the opposite trend. Active-to-passive concentration ratios for NO2, SO2 and O3 were 0.99, 1.08 and 1.16, respectively; the corresponding outdoor ratios were 0.95, 0.99 and 1.00.

Real-time indoor and outdoor measurements of black carbon at primary schools

Epidemiological and toxicological studies have demonstrated the association between Black Carbon in indoor and outdoor air and the occurrence of health risks. Data on air quality in schools is of special interest, as children are more vulnerable to health hazards. In this context, indoor and outdoor measurements of real-time Equivalent Black Carbon (EBC) were collected at 39 primary schools located in Barcelona (Spain), with classrooms naturally ventilated under warm weather conditions. A main contribution of road traffic emissions to indoor and outdoor EBC levels was evidenced through different approaches. Simultaneous measurements of EBC levels at schools under different traffic conditions revealed concentrations by 30–35% higher at schools exposed to higher vehicles intensities. Moreover, a significant correlation was obtained between average outdoor EBC levels at different districts of the city and the percentage of surface area in each district used for the road network (R2 = 0.61). Higher indoor than outdoor levels were recorded at some instances when the indoor sampling location was relatively closer to road traffic, even under low outdoor temperatures. Indeed, the average indoor/outdoor EBC ratios for each school correlate moderately between campaigns in spite of significant differences in temperature between sampling periods. These two facts highlight the strong dependency of the EBC levels on the distance to traffic. The peaks of exposure inside the classrooms seemed to be determined by outdoor concentrations, as shown by the parallelism between indoor and outdoor mean EBC daily cycles and the similar contribution of traffic rush hours to indoor and outdoor daily mean levels. The airtightness of the classroom was suggested as the responsible for the indoor/outdoor ratios of EBC higher than 1 recorded at nights.

Chemical characterization of indoor and outdoor fine particulate matter in an occupied apartment in Rome, Italy.

The daily concentration and chemical composition of PM2.5 was determined in indoor and outdoor 24-h samples simultaneously collected for a total of 5weeks during a winter and a summer period in an apartment sited in Rome, Italy. The use of a specifically developed very quiet sampler (<35dB) allowed the execution of the study while the family living in the apartment led its normal life. The indoor concentration of PM2.5 showed a small seasonal variation, while outdoor values were much higher during the winter study. Outdoor sources were found to contribute significantly to indoor PM concentration especially during the summer, when the apartment was naturally ventilated by opening the windows. During the winter the infiltration of outdoor PM components was lower and mostly regulated by the particle dimensions. Organics displayed In/Out ratios higher than unity during both periods; their indoor production increased significantly during the weekends, where the family stayed mostly at home. PM components were grouped into macrosources (soil, sea, secondary inorganics, traffic, organics). During the summer the main contributions to outdoor PM2.5 came from soil (30%), secondary inorganics (29%) and organics (22%). Organics dominated both indoor PM2.5 during the summer (60%) and outdoor and indoor PM2.5 during the winter (51% and 66%, respectively).

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±22.7μg/m3) than winter (18.9±13.2μg/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.

Relationships among indoor, outdoor, and personal airborne Japanese cedar pollen counts.

Japanese cedar pollinosis (JCP) is an important illness caused by the inhalation of airborne allergenic cedar pollens, which are dispersed in the early spring throughout the Japanese islands. However, associations between pollen exposures and the prevalence or severity of allergic symptoms are largely unknown, due to a lack of understanding regarding personal pollen exposures in relation to indoor and outdoor concentrations. This study aims to examine the relationships among indoor, outdoor, and personal airborne Japanese cedar pollen counts. We conducted a 4-year monitoring campaign to quantify indoor, outdoor, and personal airborne cedar pollen counts, where the personal passive settling sampler that has been previously validated against a volumetric sampler was used to count airborne pollen grains. A total of 256 sets of indoor, outdoor, and personal samples (768 samples) were collected from 9 subjects. Medians of the seasonally-integrated indoor-to-outdoor, personal-to-outdoor, and personal-to-indoor ratios of airborne pollen counts measured for 9 subjects were 0.08, 0.10, and 1.19, respectively. A greater correlation was observed between the personal and indoor counts (r = 0.89) than between the personal and outdoor counts (r = 0.71), suggesting a potential inaccuracy in the use of outdoor counts as a basis for estimating personal exposures. The personal pollen counts differed substantially among the human subjects (49% geometric coefficient of variation), in part due to the variability in the indoor counts that have been found as major determinants of the personal pollen counts. The findings of this study highlight the need for pollen monitoring in proximity to human subjects to better understand the relationships between pollen exposures and the prevalence or severity of pollen allergy.

Analytical method for the determination of mycotoxins in indoor/outdoor airborne particulate matter by HPLC-MS-MS

An effective analytical method for the screening of mycotoxins, in indoor/outdoor airborne particulate matter, was developed and method performance data are presented. Mycotoxins are natural compounds produced, in particular conditions, as secondary metabolites by filamentous fungi and moulds, and, after their production, they can be transported far from their source. To simulate real samples, an urban dust (reference material 1649a) free from mycotoxins was used as matrix and spiked by the most common mycotoxins, chosen on the basis of studies carried out previously in other real matrices: deoxynivalenol, aflatoxin B1, ochratoxin A, T-2 toxin, zearalenone and sterigmatocystin. The analytical method was optimised and structured in four successive steps: (1) accelerated solvent extraction of the (spiked) analytes from matrix, (2) solid-phase purification (SPE) of the previous extract, (3) pre-concentration of the eluates from SPE and (4) analysis of the concentrated eluates by high performance liquid chromatography tandem mass spectrometry in multiple reaction monitoring mode. After a proper sampling campaign, the method was applied to real indoor and outdoor particulate matter samples, where the clean-up step showed to be very effective and fundamental to avoid misleading analytical results.

Chemical characterization of outdoor and subway fine (PM(2.5-1.0)) and coarse (PM(10-2.5)) particulate matter in Seoul (Korea) by computer-controlled scanning electron microscopy (CCSEM).

Outdoor and indoor (subway) samples were collected by passive sampling in urban Seoul (Korea) and analyzed with computer-controlled scanning electron microscopy coupled with energy dispersive x-ray spectroscopy (CCSEM-EDX). Soil/road dust particles accounted for 42%–60% (by weight) of fine particulate matter larger than 1 µm (PM2.5–1.0) in outdoor samples and 18% of PM2.5–1.0 in subway samples. Iron-containing particles accounted for only 3%–6% in outdoor samples but 69% in subway samples. Qualitatively similar results were found for coarse particulate matter (PM10–2.5) with soil/road dust particles dominating outdoor samples (66%–83%) and iron-containing particles contributing most to subway PM10–2.5 (44%). As expected, soil/road dust particles comprised a greater mass fraction of PM10–2.5 than PM2.5–1.0. Also as expected, the mass fraction of iron-containing particles was substantially less in PM10–2.5 than in PM2.5–1.0. Results of this study are consistent with known emission sources in the area and with previous studies, which showed high concentrations of iron-containing particles in the subway compared to outdoor sites. Thus, passive sampling with CCSEM-EDX offers an inexpensive means to assess PM2.5–1.0 and PM10-2.5 simultaneously and by composition at multiple locations.

PROSPECTIVE HEALTH RISK OF EXPOSURE TO FINE PARTICULATE MATTER AND ITS ELEMENTAL COMPOSITION IN SHOE INDUSTRIES IN AGRA

The present study shows the current scenario of the prospective health risk of exposure to fine particulate matter and its composition at industry level. The indoor and outdoor sampling of fine particulate matter was conducted in residential site (Industry-1) and road site (Industry-2) shoe industry in Agra city. The average concentration of PM sizes accounted in indoor during sampling duration were 30.11µg/m 3 ±10.29µg/m 3 for PM1.0, 47.79 µg/m 3 ±45.49µg/m 3 for PM2.5 and 90.15µg/m 3 ±33.61 µg/m 3 for PM10 at industry-1, and 7.66 µg/m 3 ±1.86 µg/m 3 for PM1.0, 22.24 µg/m 3 ±3.69 µg/m 3 for PM2.5 and 60.89 µg/m 3 ±49.06 µg/m 3 for PM10 at industry-2. The concentration of the three components of PM (PM1.0, PM2.5, PM10) was found to be highest in industry-1 in comparison to industry-2. The full-day variation of fine particulate matter concentration and indoor meteorological parameters were also monitored. The average mass concentrations of various fraction of PM (PM1.0, PM2.5, PM10) were collected at indoor and outdoor environment in two leather (shoe) small scale industries by APM 550. After acid digestion, quantification of 16 major metals Cu, Ba, Cd, Cr, Fe, Mn, Ni, Pb, Al, K, Ca, Na, Mg, As, Co and Zn was done using ICP-AES (Inductive Couple Plasma-Atomic Emission Spectroscopy) and AAS (Atomic Absorption spectroscopy).

Airborne bacteria levels in indoor urban environments: The influence of season and prevalence of sick building syndrome (SBS)

This study investigated levels of airborne bacteria in 90 indoor sampling sites with no known complaints such as kindergartens, schools, homes and dorms over three seasons. Airborne bacteria samples were collected before and during the heating season in Çanakkale, Turkey. Also, a detailed occupant questionnaire was completed by one of the occupants ( n = 90) in each sampling site. Total bacteria counts (TBCs) were found to be higher in the sampling sites where coal was used as a heating source and in kindergartens where the occupancy rate was highest ( p &lt; 0.05). Meteorological parameters were associated with outdoor TBC levels ( p &lt; 0.001). Associations were found ( p = 0.05) for indoor TBC and other building factors (last floor covering/wall painting/renovation times, heating/cooking fuels and the age of the building). Indoor TBC levels together with the building-related factors (environmental tobacco smoke exposure, occupancy rate, distance to traffic, heating fuel, amount of carpet covering, and last wall painting time) and personal factors (gender and daily time spent indoors) were found to be associated with at least one group of the sick building syndrome (SBS) symptoms ( p &lt; 0.05). In particular, general SBS symptoms (headache, fatigue and dizziness) were observed more often in female participants ( p &lt; 0.05). In conclusion, there is a need to conduct more studies in larger populations to find the links between air pollutants and SBS symptoms.

Does the elemental composition of indoor and outdoor PM2.5 accurately represent the elemental composition of personal PM2.5?

The complex mixture of chemical and elemental constituents that comprise particulate matter (PM) is hypothesized to be, in part, responsible for its toxicity. Epidemiologic studies have identified specific components and sources of PM2.5 associated with adverse health outcomes, but the majority of these studies use the mass concentration of elements in outdoor PM2.5 at central monitoring sites as a surrogate for personal exposure. Personal exposure to PM2.5 and its elemental composition, however, may vary from stationary outdoor measurements. Here, we use concurrent indoor, outdoor, and personal sampling of PM2.5 and its elemental constituents along with personal and home characteristics, collected as a part of the Relationships of Indoor, Outdoor, and Personal Air (RIOPA) study to characterize the differences in PM2.5 among indoor, outdoor, and personal air samples. We found that personal exposure to PM2.5 and most elements were significantly correlated with, though frequently exceeded, both indoor and outdoor measurements. Principal component scores were used to determine that the mixture of elemental components in PM2.5 varies significantly across indoor, outdoor, and personal sample types. Using model-based clustering, we identified 7 clusters of RIOPA participants whose personal PM2.5 samples had similar patterns of elemental composition. Using this approach, two subsets of RIOPA participants were identified whose personal exposure to PM2.5 and elemental concentrations were significantly increased compared to both their indoor and outdoor levels. Collectively, our results suggest that the elemental composition of PM2.5 obtained at central monitoring stations do not accurately represent the overall elemental composition of personal PM2.5 exposure.

Characterization of heavy metals and brominated flame retardants in the indoor and outdoor dust of e-waste workshops: implication for on-site human exposure.

Forty-four indoor and outdoor dust samples were collected from e-waste workshops and were analyzed to characterize the heavy metals and brominated flame retardants (BFRs) as well as on-site human exposure. The results showed that the most abundant Polybrominated diphenyl ethers (PBDE) congener from three sites was deca-BDE, and it was penta-BDE for the other site. A significant and positive association was found between BDE-209 and decabromodiphenyl ethane (DBDPE). The high percentage of nona-BDE indicated the debromination of deca-BDE during e-waste recycling. The ratio comparison of BDE-47 to (BDE-100 + BDE-99) indicated that the outdoor dust went through more physiochemical processes. The enrichment factors for Cu and Pb were high in both the indoor and outdoor samples. Cd significantly exceeded the Chinese soil guideline grade III. The PCA results combined with the enrichment factor (EF) values suggested common sources and behaviours of Cu, Pb and Sb in the indoor dust. Co, Cr, Ni, Zn and Mn in the outdoor samples were more likely affected by crust. Strong correlations were found only for Pb and Sb with polybrominated diphenyl ethers (PBDEs). The hazard index for on-site human exposure to Pb was at a chronic risk. Despite the low deleterious risk of BFRs, concern should be given to DBDPE; the chronic toxicity of which is not known.

Characterization of indoor air quality and resident health in an Arizona senior housing apartment building

A survey of key indoor air quality (IAQ) parameters and resident health was carried out in 72 apartments within a single low-income senior housing building in Phoenix, Arizona. Air sampling was carried out simultaneously with a questionnaire on personal habits and general health of residents. Mean PM10 concentrations are 66±16, 58±13, and 24±3 μg/m3 and mean PM2.5 concentrations are 62±16, 53±13, and 20±2 μg/m3 for the living room, kitchen, and outdoor balcony, respectively. Median PM10 concentrations are 17, 18 and 17 μg/m3 and median PM2.5 concentrations are 13, 14, and 13 μg/m3, respectively. The initial results indicate that increased indoor particle concentrations coincide with residents who report smoking cigarettes. Indoor formaldehyde concentrations revealed median levels of 36.9, 38.8, and 4.3 ppb in the living room, kitchen, and balcony, respectively. Results show that 36% of living room samples and 44% of kitchen samples exceeded the Health Canada REL for chronic exposure to formaldehyde (40 ppb). Associations between occupants’ behavior, self-reported health conditions, and IAQ are evaluated.Implications:This study provides a characterization of indoor air quality (IAQ) of subsidized apartments for seniors in Phoenix, Arizona. It is important for policy makers to understand the environments in which low-income seniors live, as they are vulnerable to the health impacts from poor IAQ. Formaldehyde concentrations were found to exceed the Health Canada 8-hr reference exposure level (REL) for up to 44% of indoor samples. Particulate matter exposure was governed by resident behavior (i.e., smoking). Associations between occupants’ behavior, IAQ, and self-reported health conditions are evaluated. This work can provide a foundation for subsequent remediation of IAQ conditions.

A study of pre-analytical errors in a hospital based clinical biochemistry laboratory and formulation of measures for correction

A prospective observational study was done in the Central Clinical Laboratory of Gauhati Medical College & Hospital for a period of 2 months from 1 st March to 30 th April 2014. The objective of the study was to evaluate the pre-analytical phase of laboratory testing in a Clinical Biochemistry Laboratory to detect the different errors which occurred in the preanalytical phase and calculate their percentage and to determine in which step the error occurred so that corrective measures can be formulated to avoid such errors. All the samples and their accompanying laboratory request forms were screened for pre-analytical errors and the daily errors and their types recorded in Problem Notification Logbook. The data collected was analyzed and the entire process of sample collection and transport was evaluated to formulate corrective measures to prevent these errors from occurring. The total number of samples received in 2 months was 23,680. Out of this OPD samples were 11,414 and Indoor samples were 12,266.Of the 12,266 laboratory request forms which were screened 12,106, forms were incomplete i.e. only 160 forms carried all the required information. Out of the total 23,680 sample tubes screened preanalytical errors were observed in 6.61% of Indoor samples and 3.69% of OPD samples. Hemolysed sample was the most commonly observed preanalytical error both in OPD and Indoor samples. Hemolysis was observed in 4.25% of Indoor samples and in 3.55% of OPD samples. Insufficient sample volume was observed in 1.74% of Indoor and .026% of OPD samples. Preanalytical error was observed in 5.20% of samples during the study period. Of this 3.91% of samples received were hemolysed and were rejected .Corrective measures have to be taken to reduce the percentage of rejected samples.

Indoor and Outdoor Biomonitoring Using Lichens at Urban and Rural Primary Schools

Monitoring particulate matter (PM) and its chemical constituents in classrooms is a subject of special concern within the scientific community in order to control and minimize child exposure. Regulatory sampling methods have presented several limitations in their application to larger number of classrooms due to operational and financial constraints. Consequently, passive sampling methodologies using filters were developed for indoor sampling. However, such methodologies could not provide parallel information for outdoors, which is important to identify pollution sources and assess outdoor contribution to the indoors. Therefore, biomonitoring with transplanted lichens, a technique usually applied for outdoor studies, was used both indoor and outdoor of classrooms. Three main objectives were proposed, to (i) characterize simultaneously indoor and outdoor of classrooms regarding inorganic air pollutants, (ii) investigate spatial patterns of lichen conductivity, and (iii) assess pollution sources that contribute to a poor indoor air quality in schools. Lichens Flavoparmelia caperata were transplanted to indoor and outdoor of classrooms for 59 d. After exposure, electric conductivity of lichens leachate was measured to evaluate lichen vitality and cell damage. Outdoors lichen conductivity was higher near the main highways, and indoors there was great variability in levels, which indicates different emissions sources and different ventilation patterns. Chemical content of lichens was assessed by instrumental neutron activation analysis (INAA), and As, Br, Ca, Ce, Co, Cr, Cs, Eu, Fe, Hf, K, La, Na, Rb, Sb, Sc, Sm, Sr, Ta, Th, Yb, and Zn were determined. Element accumulation, crustal enrichment factors, and spatial variability of elements were analyzed and contaminants from anthropogenic sources, such as traffic (As, Sb, and Zn) and indoor chalk (Ca) found. Classrooms with potential indoor air quality problems were identified by presenting higher accumulations of inorganic pollutants in exposed biomonitors.