Determination of ozone in outdoor and indoor environments using nitrite-impregnated passive samplers followed by ion chromatography

An improved ion chromatographic (IC) method has been developed for the separation of nitrate in filter extracts in the presence of high concentrations of nitrite. This analytical method was successfully used for an indirect measurement of ozone (O3) in outdoor and indoor air, following its collection using a nitrite-impregnated passive sampler. The limit of detection and the limit of quantification, using the modified IC method, were 6 microg l(-1) (3sigma) and 20 microg l(-1) (10sigma), respectively. Improved detection limits and low baseline noise were obtained with the use of eluent generator and high-capacity ion exchange column. The optimized method was used for assessing O3 concentration in both indoor and outdoor environments of 28 child care centers (CCCs) located in different parts of Singapore. The O3 concentrations ranged from 0.1 to 11.95 parts per billion (ppb) in indoor and from 3.2 to 21.7 ppb in outdoor environments during the study period. It was found that, among the CCCs investigated in this study, air-conditioned CCCs and those located in close proximity to traffic emissions had significantly lower O3 concentrations indoors.     

Dependence of home outdoor particulate mass and number concentrations on residential and traffic features in urban areas

The associations between residential outdoor and ambient particle mass, fine particle absorbance, particle number (PN) concentrations, and residential and traffic determinants were investigated in four European urban areas (Helsinki, Athens, Amsterdam, and Birmingham). A total of 152 nonsmoking participants with respiratory diseases, not exposed to occupational pollution, were included in the study, which comprised a 7-day intensive exposure monitoring period of both indoor and home outdoor particle mass and number concentrations. The same pollutants were also continuously measured at ambient fixed sites centrally located to the studied areas (fixed ambient sites). Relationships between concentrations measured directly outside the homes (residential outdoor) and at the fixed ambient sites were pollutant-specific, with substantial variations among the urban areas. Differences were more pronounced for coarse particles due to resuspension of road dust and PN, which is strongly related to traffic emissions. Less significant outdoor-to-fixed variation for particle mass was observed for Amsterdam and Birmingham, predominantly due to regional secondary aerosol. On the contrary, a strong spatial variation was observed for Athens and to a lesser extent for Helsinki. This was attributed to the overwhelming and time-varied inputs from traffic and other local sources. The location of the residence and traffic volume and distance to street and traffic light were important determinants of residential outdoor particle concentrations. On average, particle mass levels in suburban areas were less than 30% of those measured for residences located in the city center. Residences located less than 10 m from a street experienced 133% higher PN concentrations than residences located further away. Overall, the findings of this multi-city study, indicated that (1) spatial variation was larger for PN than for fine particulate matter (PM) mass and varied between the cities, (2) vehicular emissions in the residential street and location in the center of the city were significant predictors of spatial variation, and (3) the impact of traffic and location in the city was much larger for PN than for fine particle mass.     

Estimated long-term outdoor air pollution concentrations in a cohort study

Several recent studies associated long-term exposure to air pollution with increased mortality. An ongoing cohort study, the Netherlands Cohort Study on Diet and Cancer (NLCS), was used to study the association between long-term exposure to traffic-related air pollution and mortality. Following on a previous exposure assessment study in the NLCS, we improved the exposure assessment methods.Long-term exposure to nitrogen dioxide (NO₂), nitrogen oxide (NO), black smoke (BS), and sulphur dioxide (SO₂) was estimated. Exposure at each home address (N=21 868) was considered as a function of a regional, an urban and a local component. The regional component was estimated using inverse distance weighed interpolation of measurement data from regional background sites in a national monitoring network. Regression models with urban concentrations as dependent variables, and number of inhabitants in different buffers and land use variables, derived with a Geographic Information System (GIS), as predictor variables were used to estimate the urban component. The local component was assessed using a GIS and a digital road network with linked traffic intensities. Traffic intensity on the nearest road and on the nearest major road, and the sum of traffic intensity in a buffer of 100 m around each home address were assessed. Further, a quantitative estimate of the local component was estimated.The regression models to estimate the urban component explained 67%, 46%, 49% and 35% of the variances of NO₂, NO, BS, and SO₂ concentrations, respectively. Overall regression models which incorporated the regional, urban and local component explained 84%, 44%, 59% and 56% of the variability in concentrations for NO₂, NO, BS and SO₂, respectively.We were able to develop an exposure assessment model using GIS methods and traffic intensities that explained a large part of the variations in outdoor air pollution concentrations.     

An evaluation approach for livable urban environments

This study proposes a method for evaluating livable urban environments using the analytic hierarchy process, a survey of public opinions (n?=?1,075), and gray relational analysis with a pollutant standards index to estimate the weights of weather, air pollution, and environment aspects and each respective factor. This study investigates the positive or negative correlation of these factors and their effects on livable environment. A value of 100 was designated as the perfect living condition. Results show that the weights of weather, air pollution, and environment aspects were 0.288, 0.395, and 0.317, respectively. The weight ranges of three weather factors, five air pollution factors, and ten environmental factors were 0.311-0.358, 0.191-205, and 0.081-0.116, respectively. The monthly livable index of 28 districts in Taichung City and of 20 cities/counties in Taiwan ranged from 81.1 to 92.4 and from 83.1 to 90.8 in different months, respectively, showing that environmental aspect played a key role. These results demonstrate that the proposed method can provide a quantification index of living conditions in each region, thereby establishing the governmental improvement policy firmly. This study also presents a discussion on improvement strategies, especially on the apportionment rate of governmental construction funds for livable urban environments.     

Vehicle wake factor for heterogeneous traffic in urban environments

Vehicles' 'wakes' are generated as a result of vehicular movements. They are one of the dominant factors in dispersing the pollutants in 'calm' meteorological conditions when wind velocity is <1 m/sec (Chock, 1978). They are used as a wind-speed-correction factor in several air quality models considering the effects of traffic movements on the pollutant dispersion. In this study, the vehicle wake factor (VWF) has been estimated using the inverse general finite line source model, GFLSM, (Luhar and Patil, 1989) for heterogeneous traffic conditions at one of the busiest traffic intersections of the Delhi city, near the Income Tax Office (ITO). The results show that in 'unstable' conditions, the VWF varies between 1.63 and 0.3 (for wind direction, θ = 90°) and 2.5 and 0.8 (for wind direction, θ = 180°). During 'neutral' and 'stable' conditions, it is in the range of 0.84–0.4, 1.91–0.85, (for wind direction θ = 270°) and 1.7–0.7, 3.1–0.3 for wind direction θ = 360°, respectively.     

Monitoring of heavy metal concentrations in home outdoor air using moss bags

One monitoring station is insufficient to characterize the high spatial variation of traffic-related heavy metals within cities. We tested moss bags (Hylocomium splendens), deployed in a dense network, for the monitoring of metals in outdoor air and characterized metals’ long-term spatial distribution and its determinants in Girona, Spain. Mosses were exposed outside 23 homes for two months; NO₂ was monitored for comparison. Metals were not highly correlated with NO₂ and showed higher spatial variation than NO₂. Regression models explained 61-85% of Cu, Cr, Mo, Pb, Sb, Sn, and Zn and 72% of NO₂ variability. Metals were strongly associated with the number of bus lines in the nearest street. Heavy metals are an alternative traffic-marker to NO₂ given their toxicological relevance, stronger association with local traffic and higher spatial variability. Monitoring heavy metals with mosses is appealing, particularly for long-term exposure assessment, as mosses can remain on site many months without maintenance.     

Visibility,mass concentration and power use in urban environments

A simple statistical model is used to account for energy and economic costs incurred by additional artificial illumination in urban environments caused by pollutant aerosols. The method of calculation, using the prevailing visibility as a measure of diminished natural illumination, suggests that as much as 1.0 per cent of our electrical energy may be consumed due to this pollution factor.     

Time-resolved measurements of aerosol elemental concentrations in indoor working environments

We have measured the elemental concentrations in aerosols with a 2-h time resolution in two different types of working environment: a chemistry laboratory dealing with the processing of advanced nanoparticulate materials and a medium-sized machine workshop. Non-stop 10-day and 12-day samplings were performed at each location in order to determine the concentration trends during the non-working/working and weekday/weekend periods. Supplementary measurements of PM10 aerosols with a 2-day sample collection time were performed with a standard Gent PM10 sampler to compare the elemental concentrations with the time-averaged concentrations detected by the 2D step-sampler. The concentrations were determined a posteriori by analyzing the x-ray spectra of aerosol samples emitted after 3-MeV proton bombardment. The PM10 samples collected in the chemistry laboratory were additionally inspected by scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) to determine the chemical compositions of the individual particles. In the workshop, a total PM10 mass sampling was performed simultaneously with a minute resolution to compare the signal with typical outdoor PM10 concentration levels. A factor analysis of the time-resolved dataset points to six and eight factors in the chemistry laboratory and the machine workshop, respectively. These factors describe most of the data variance, and their composition in terms of different elements can be related to specific indoor activities and conditions. We were able to demonstrate that the elemental concentration sampling with hourly resolution is an excellent tool for studying the indoor air pollution. While sampling the total PM10 mass concentration with a minute resolution may lack the potential to identify the emission sources in a “noisy” environment, the time averaging on a day time scale is too coarse to cope with the working dynamics, even if elemental sensitivity is an option.     

Airborne PBDEs in specialized occupational settings, houses and outdoor urban areas in Greece

Airborne polybrominated diphenyl ethers (PBDEs) were measured in workplaces, homes and urban outdoor air in Greece. The geometric mean concentrations of total PBDEs (sum of 19 congeners) in offices (205pgm(-3)), internet cafes/computer rooms (127pgm(-3)) and computers/electronics shops (85pgm(-3)) were significantly higher than those in furniture stores (12pgm(-3)), homes (8pgm(-3)) and outdoor air (18pgm(-3)). The daily inhalation intake of PBDEs estimated for the employees of the four occupational settings ranged from 0.2 to 1.4ngday(-1) and it was significantly lower than the expected dietary intake ( approximately 77ngday(-1)). Although inhalation generally represented a small fraction of the overall daily exposure to PBDEs ( approximately 1%), the results from a heavily contaminated office (10 848pgm(-3) of total PBDEs) indicated that the intake from this route (65ngday(-1)) may, in some extreme cases, be as important as diet.     

Airborne concentrations of SARS-CoV-2 in indoor community environments in Italy

Environmental Science and Pollution Research - COVID-19 pandemic raised a debate regarding the role of airborne transmission. Information regarding virus-laden aerosol concentrations is still...     

Carbonaceous aerosol characteristics in outdoor and indoor environments of Nanchang, China, during summer 2009

A study of carbonaceous aerosol was initiated in Nanchang, a city in eastern China, for the first time. Daily and diurnal (daytime and nighttime) PM2.5 (particulate matter with aerodynamic diameter < or =2.5 microm) samples were collected at an outdoor site and in three different indoor environments (common office, special printing and copying office, and student dormitory) in a campus of Nanchang University during summer 2009 (5-20 June). Daily PM10 (particulate matter with aerodynamic diameter < or =10 microm) samples were collected only at the outdoor site, whereas PM2.5 samples were collected at both indoor and outdoor sites. Loaded PM2.5 and PM10 samples were analyzed for organic and elemental carbon (OC, EC) by thermal/optical reflectance following the Interagency Monitoring of Protected Visual Environments-Advanced (IMPROVE-A) protocol. Ambient mass concentrations of PM10 and PM2.5 in Nanchang were compared with the air quality standards in China and the United States, and revealed high air pollution levels in Nanchang. PM2.5 accounted for about 70% of PM10, but the ratio of OC and EC in PM2.5 to that in PM10 was higher than 80%, which indicated that OC and EC were mainly distributed in the fine particles. The variations of carbonaceous aerosol between daytime and nighttime indicated that OC was released and formed more rapidly in daytime than in nighttime. OC/EC ratios were used to quantify secondary organic carbon (SOC). The differences in SOC and SOC/OC between daytime and nighttime were useful in interpreting the secondary formation mechanism. The results of (1) OC and EC contributions to PM2.5 at indoor sites and the outdoor site; (2) indoor-outdoor correlation of OC and EC; (3) OC-EC correlation; and (4) relative contributions of indoor and outdoor sources to indoor carbonaceous aerosol indicated that OC indoor sources existed in indoor sites, with the highest OC emissions in I2 (the special printing and copying office), and that indoor EC originated from outdoor sources. The distributions of eight carbon fractions in emissions from the printer and copier showed obviously high OC1 (>20%) and OC2 (approximately 30%), and obviously low EC1-OP (a pyrolyzed carbon fraction) (<10%), when compared with other sources.     

Air pollution dispersion within urban street canyons

A semi-empirical mathematical model, Urban Street Model (USM), is proposed to efficiently estimate the dispersion of vehicular air pollution in cities. This model describes urban building arrangements by combining building density, building heights and the permeability of building arrangements relative to wind flow. To estimate the level of air pollution in the city of Krasnoyarsk (in Eastern Siberia), the spatial distribution of pollutant concentrations off roadways is calculated using Markov's processes in USM. The USM-predicted numerical results were compared with field measurements and with results obtained from other frequently used models, CALINE-4 and OSPM. USM consistently yielded the best results. OSPM usually overestimated pollutant concentration values. CALINE-4 consistently underestimated these values. For OSPM, the maximum differences were 160% and for CALINE-4 about 400%. Permeability and building density are necessary parameters for accurately modeling urban air pollution and influencing regulatory requirements for building planning.     

Spatial and seasonal variation of outdoor BC and PM2.5 in densely populated urban slums

Environmental Science and Pollution Research - A large proportion of residents in urban centers of low- and middle-income countries live in low-socioeconomic neighborhoods called...     

Experimental investigation of outdoor and indoor mean concentrations and concentration fluctuations of pollutants

Tracer gas was released upwind of a two-compartment complex shaped building under unstable atmospheric conditions. The mean wind direction was normal to or at 45° to the long face of the building. The general patterns of concentration distribution on the building external walls and inside the building were analysed and the influence of natural and mechanical ventilation on indoor concentration distributions was discussed. Mean concentration levels, as well as the concentration fluctuation intensity, were higher on the windward walls of the building, although concentration levels varied along each wall. Concentration fluctuations measured inside the building were lower than those measured outside. Inside the two compartments of the building, the time series of concentrations had a similar general behaviour; however, gas concentrations took approximately 1.5 times longer to reach the mean maximum concentration value at the downwind compartment 02 while they also decreased more rapidly in the upwind compartment 01 after the source was turned off. The highest indoor concentration and concentration fluctuation values were observed at the detectors located close to the windward walls, especially when the building windows were open. Experiments with and without natural ventilation suggested that infiltration and exfiltration of contaminants is much faster when the building windows are open, resulting to higher indoor concentration levels. Furthermore, mechanical ventilation tends to homogenize concentrations and suppress concentration fluctuations, leading to lower maximum concentration values.     

Detecting and characterising small changes in urban nitrogen dioxide concentrations

Detecting and quantifying abnormal changes in the concentration of urban air pollutants can be difficult due to the influence of meteorology and atmospheric chemistry. This study presents methods to detect and characterise small changes in the concentration of nitrogen dioxide (NO₂) that deviate from expected behaviour. Generalized additive models (GAMs) are used to describe daily mean NO₂ concentrations at roadside monitoring sites to determine how concentrations deviate from measured concentrations. Structural change methods are applied to time series describing this difference to identify change-points, where concentrations of NO₂ deviate significantly from expected behaviour. Methods are also used which quantify the timing and uncertainty associated in the timing of these change-points. For most time series data considered in London, concentrations of NO₂ underwent relatively abrupt changes rather than smoothly varying increases; changes which remain largely undetected in raw time series data. Most change-points occurred in late 2002 or early 2003, and the factors, which may have contributed to them, are discussed. These methods can also identify technical problems with monitoring equipment and are applicable to other instances where detecting sudden atmospheric composition change is important.     

Controls on hourly variations in urban background air pollutant concentrations

Average 21st century concentrations of urban air pollutants linked to cardiorespiratory disease are not declining, and commonly exceed legal limits. Even below such limits, health effects are being observed and may be related to transient daytime peaks in pollutant concentrations. With this in mind, we analyse >52,000 hourly urban background readings of PM₁₀ and pollutant gases throughout 2007 at a European town with legal annual average concentrations of common pollutants, but with a documented air pollution-related cardiorespiratory health problem, and demonstrate the hourly variations in PM₁₀, SO₂, NO_x, CO and O₃. Back-trajectory analysis was applied to track the arrival of exotic PM₁₀ intrusions, the main controls on air pollutants were identified, and the typical hourly pattern on ambient concentrations during 2007 was profiled. Emphasis was placed on “worst case” data (>90th percentile), when health effects are likely to be greatest. The data show marked daytime variations in pollutants result from rush-hour traffic-related pollution spikes, midday industrial SO₂ maxima, and afternoon O₃ peaks. African dust intrusions enhance PM₁₀ levels at whatever hour, whereas European PM incursions produce pronounced evening peaks due to their transport direction (across an industrial traffic corridor). Transient peak profiling moves us closer to the reality of personal outdoor exposure to inhalable pollutants in a given urban area. We argue that such an approach to monitoring data potentially offers more to air pollution health effect studies than using only 24 h or annual averages.     

Spatial and temporal variability in urban fine particulate matter concentrations

Identification of hot spots for urban fine particulate matter (PM(2.5)) concentrations is complicated by the significant contributions from regional atmospheric transport and the dependence of spatial and temporal variability on averaging time. We focus on PM(2.5) patterns in New York City, which includes significant local sources, street canyons, and upwind contributions to concentrations. A literature synthesis demonstrates that long-term (e.g., one-year) average PM(2.5) concentrations at a small number of widely-distributed monitoring sites would not show substantial variability, whereas short-term (e.g., 1-h) average measurements with high spatial density would show significant variability. Statistical analyses of ambient monitoring data as a function of wind speed and direction reinforce the significance of regional transport but show evidence of local contributions. We conclude that current monitor siting may not adequately capture PM(2.5) variability in an urban area, especially in a mega-city, reinforcing the necessity of dispersion modeling and methods for analyzing high-resolution monitoring observations.