Estimating the frequency distributions of particulate matter and their metal elements in a temple

Air quality inside Asian temples is typically poor because of the burning of incense. This study measured and analyzed concentrations of fine (PM2.5) and coarse (PM2.5-10) particulate matter and their metal elements inside a temple in central Taiwan. Experimental results showed that the concentrations of metals Cd, Ni, Pb, and Cr inside the temple were higher than those at rural, suburban, urban, and industrial areas in other studies. Three theoretical parent distributions (lognormal, Weibull, and gamma) were used to fit the measured data. The lognormal distribution was the most appropriate distribution for representing frequency distributions of PM10, PM2.5, and their metal elements. Furthermore, the central limit theorem, H-statistic-based scheme, and parametric and nonparametric bootstrap methods were used to estimate confidence intervals for mean pollutant concentrations. The estimated upper confidence limits (UCLs) of means between different methods were very consistent, because the sample coefficient of variation (CV) was < 1. When the sample CV was > 1, the UCL based on H-statistical method tended to overestimate the UCLs when compared with other methods. Confidence intervals for pollutant concentrations at different percentiles were evaluated using parametric and nonparametric bootstrap methods. The probabilities of pollutants exceeding a critical concentration were also calculated.     

Atmospheric Factors Influencing Daily Sulfate Concentrations in Chicago Air

Abstract

Confidence interval construction for central tendency is a problem of practical consequence for those who must analyze air contaminant data. Determination of compliance with relevant ambient air quality criteria and assessment of associated health risks depend upon quantifying the uncertainty of estimated mean pollutant concentrations. The bootstrap is a resampling technique that has been steadily gaining popularity and acceptance during the past several years. A potentially powerful application of the bootstrap is the construction of confidence intervals for any parameter of any underlying distribution. Properties of bootstrap confidence intervals were determined for samples generated from lognormal, gamma, and Weibull distributions. Bootstrap t intervals, while having smaller coverage errors than Student's t or other bootstrap methods, under-cover for small samples from skewed distributions. Therefore, we caution against using the bootstrap to construct confidence intervals for the mean without first considering the effects of sample size and skew. When sample sizes are small, one might consider using the median as an estimate of central tendency. Confidence intervals for the median are easy to construct and do not under-cover. Data collected by the Northeast States for Coordinated Air Use Management (NESCAUM) are used to illustrate application of the methods discussed.     

Metallic elements in particulates released during incense-burning at Tzu Yun Yen temple, Taichung, Taiwan

Concentrations of ambient suspended particulates were measured at Tzu Yun Yen temple (120°, 34′ 10”E; 24°, 16′, 12”N), using a Universal sampler and dry deposition plates. The temple is a characteristic incense-burning and semi-open sampling site. PM_2.5 concentrations for Period 1 (average 901μg/m3) were higher than those for Period 2 (average 701μg/m3). Results for average PM_2.5-10concentrations showed equal distributions in Period 1 and Period 2. Average ratios of PM_2.5/ PM₁₀ were higher in Period 1 (74%) than Period 2 (71%). In addition, the suspended particulate (PM₁₀) elements concentrations during Zhong Yuan Jie, and the first and 15th days of nong li for each month (Chinese lunar calendar) were all higher than during non-Zhong Yuan Jie and non-first and non-15th days. Furthermore, the dry deposition velocities of manganese in fine particulates (PM_2.5) and suspended particulates (PM₁₀) were 1.43 and 0.751cm/s, respectively, and the dry deposition velocities of cadmium in fine particulates (PM_2.5) and suspended particulates (PM₁₀) were 1.86 and 0.991cm/s, respectively.     

区域大气环境中PM2.5/PM10空间分布研究

提出了一种利用移动监测技术研究区域大气环境中PM_2.5/PM₁₀空间分布的方法,并在2004年12月进行了宁波市全市域PM_2.5/PM₁₀空间分布的研究。数据显示：相同路径所代表的地区PM_2.5和PM₁₀具有很好的相关性,多数路径上PM_2.5与PM₁₀数据的相关系数平方在0.95以上,而不同路径上PM_2.5与PM₁₀的比值不同。文中给出了宁波市PM_2.5/PM₁₀污染的空间分布图,直观地显示出PM_2.5/PM₁₀污染的空间分布情况,突出了污染的重点点位和地区。     

Statistical distributions of particulate matter and the error associated with sampling frequency

The distribution of particulate matter (PM) concentrations has an impact on human health effects and the setting of PM regulations. Since PM is commonly sampled on less than daily schedules, the magnitude of sampling errors needs to be determined. Daily PM data from Spokane, Washington were resampled to simulate common sampling schedules and the sampling error was computed for regulatory and distribution statistics. Probability density functions (pdf's) were fit to the annual daily data to determine the shape of the PM_2.5 and PM₈ concentration distributions and they were also fit to the less than daily sampling to determine if pdf's could be used to predict the daily high-concentration percentiles. There is an error when using a less than daily sampling schedule for all statistics. The error expressed as a percentage difference from the everyday sampling for the PM_2.5 mean was as large as 1.7, 3.4 and 7.7% and the 98th percentile error was as great as 8.8, 18 and 67% for 1-in-2 day, 1-in-3 day and 1-in-6 day sampling, respectively. For PM₈ the error in the mean was 2.5, 4.7 and 8.6% for and the error in the 99th percentile was 27, 18 and 46% for 1-in-2 day, 1-in-3 day, and 1-in-6 day sampling, respectively. The PM_2.5 and PM₈ concentration data were best fit by a three-parameter lognormal distribution and a generalized extreme value distribution, respectively. For PM_2.5 and PM₈, as the annual mean increased the mode concentration increased, but for PM₈ the shape of the distribution also flattened. Predicting the daily high percentiles from pdf's that were fit to the less than daily sampled data produced mixed results. For PM₈, the pdf's predicted high concentrations were closer to the daily percentiles than the actual less-than-daily sampling percentile while for PM_2.5 they were not.     

Concentrations,properties, and health risk of PM2.5 in the Tianjin City subway system

A campaign was conducted to assess and compare the personal exposure in L3 of Tianjin subway, focusing on PM_2.5 levels, chemical compositions, morphology analysis, as well as the health risk of heavy metal in PM_2.5. The results indicated that the average concentration of the PM_2.5 was 151.43 μg/m³ inside the train of the subway during rush hours. PM_2.5 concentrations inside car under the ground are higher than those on the ground, and PM_2.5 concentrations on the platform are higher than those inside car. Regarding metal concentrations, the highest element in PM_2.5 samples was Fe; the level of which is 17.55 μg/m³. OC is a major component of PM_2.5 in Tianjin subway. Secondary organic carbon is the formation of gaseous organic pollutants in subway. SEM–EDX and TEM–EDX exhibit the presence of individual particle with a large metal content in the subway samples. For small Fe metal particles, iron oxide can be formed easily. With regard to their sources, Fe-containing particles are generated mainly from mechanical wear and friction processes at the rail–wheel–brake interfaces. The non-carcinogenic risk to metals Cr, Ni, Cu, Zn and Pb, and carcinogenic hazard of Cr and Ni were all below the acceptable level in L3 of Tianjin subway.

     

Personal exposure to particulate air pollution in transport microenvironments

Personal measurements of exposure to particulate air pollution (PM₁₀, PM_2.5, PM₁) were simultaneously made during walking and in-car journeys on two suburban routes in Northampton, UK, during the winter of 1999/2000. Comparisons were made between concentrations found in each transport mode by particle fraction, between different particle fractions by transport mode, and between transport microenvironments and a fixed-site monitor located within the study area. High levels of correlation were seen between walking and in-car concentrations for each of the particle fractions (PM₁₀: r²=0.82; PM_2.5: r²=0.98; PM₁: r²=0.99). On an average, PM₁₀ concentrations were 16% higher inside the car than for the walker, but there were no difference in average PM_2.5 and PM₁ concentrations between the two modes. High PM_2.5:PM₁₀ ratios (0.6–0.73) were found to be associated with elevated sulphate levels. The PM_2.5:PM₁₀ and PM₁:PM_2.5 ratios were shown to be similar between walking and in-car concentrations. Concentrations of PM₁₀ were found to be more closely related between transport mode than either mode was with concentrations recorded at the fixed-site (roadside) monitor. The fixed-site monitor was shown to be a poor marker for PM₁₀ concentrations recorded during walking and in-car on a route over 1 km away.     

A study on variations of concentrations of particulate matter with different sizes in Lanzhou,China

Lanzhou is one of the most air-polluted cities in China and in the world, and its primary air pollutant is particulate matter (PM). Different size particulate matter (TSP, PM₁₀, PM_2.5 and PM_1.0) have different sources and affect the environment and human health differently, so it is very important to study the pollutant characteristics of different particles in order to deeply understand the pollution situation of Lanzhou city and establish reasonable preventive countermeasures. TSP, PM₁₀, PM_2.5 and PM_1.0 concentrations were simultaneously measured in Lanzhou to detect the annual and diurnal variations of concentrations of PM with different sizes and possible causes. The main results are as follows: (1) The annual distribution of monthly average concentrations for coarse particles (TSP and PM₁₀) is bimodal with the highest peak in April, which is different from the situation in other cities not affected by sand-dust events. However, the annual distribution for fine particles (PM_2.5 and PM_1.0) is unimodal with the peak in December. This difference between coarse and fine particles indicates that sand-dust events in spring carry much more coarse than fine particles to Lanzhou. This result is supported by the correlation between springtime wind speed and concentrations of PM with different sizes. (2) Under normal conditions (without dust intrusions), the diurnal distribution of coarse particle concentration in Lanzhou is bimodal. However, the distribution is trimodal during dust intrusions in April, with an extra peak in the afternoon. (3) In general, the highest concentration peaks of the diurnal variations for TSP, PM₁₀, PM_2.5 and PM_1.0 occur at about the same time. However, there are obvious differences in the occurrence time of the minimum concentrations among different kinds of PM. The differences in the occurrence time of minima between coarse and fine particles are due to their different diffusion behaviors in the atmospheric boundary layer.     

Evaluation of Time-Resolved PM2.5 Data in Urban/Suburban Areas of New Jersey

ABSTRACT

Time-resolved data is needed for public notification of unhealthful air quality and to develop an understanding of atmospheric chemistry, including insights important to control strategies. In this research, continuous fine particulate matter (PM_2.5) mass concentrations were measured with tapered element oscillating microbalances (TEOMs) across New Jersey from July 1997 to June 1998. Data features indicating the influence of local sources and long-distance transport are examined, as well as differences between 1-hr maxima and 24-hr average concentrations that might be relevant to acute health effects. Continuous mass concentrations were not significantly different from filter-collected gravimetric mass concentrations with 95% confidence intervals during any season. Annual mean PM_2.5 concentrations from July 1997 to June 1998 were 17.3, 16.4, 14.1, and 15.3 μg/m³ at Newark, Elizabeth, New Brunswick, and Camden, NJ, respectively. Monthly averaged 24- and 1-hr daily maximum PM_2.5 concentrations suggest the existence of a high PM_2.5 (May-October) and a low PM_2.5 (November-April) season.

PM_2.5 magnitudes and temporal trends were very similar across the state during high PM_2.5 events. In fact, the between-site coefficients of determination (R²) for daily PM_2.5 measurements were 84-98% for June and July. Additionally, during the most pronounced PM_2.5 episode, PM_2.5 concentrations closely tracked the daily maximum 1-hr O₃ concentrations. These observations suggest the importance of transport and atmospheric chemistry (i.e., secondary formation) to PM_2.5 episodes in New Jersey. The influence of local sources was observed in diurnal concentration profiles and annual average between-site differences. Urban wintertime data illustrate that high 1-hr maximum PM_2.5 concentrations can occur on low 24-hr PM_2.5 days.     

Errors in coarse particulate matter mass concentrations and spatiotemporal characteristics when using subtraction estimation methods

In studies of coarse particulate matter (PM_10-2.5), mass concentrations are often estimated through the subtraction of PM_2.5 from collocated PM₁₀ tapered element oscillating microbalance (TEOM) measurements. Though all field instruments have yet to be updated, the Filter Dynamic Measurement System (FDMS) was introduced to account for the loss of semivolatile material from heated TEOM filters. To assess errors in PM_10-2.5 estimation when using the possible combinations of PM₁₀ and PM_2.5 TEOM units with and without FDMS, data from three monitoring sites of the Colorado Coarse Rural–Urban Sources and Health (CCRUSH) study were used to simulate four possible subtraction methods for estimating PM_10-2.5 mass concentrations. Assuming all mass is accounted for using collocated TEOMs with FDMS, the three other subtraction methods were assessed for biases in absolute mass concentration, temporal variability, spatial correlation, and homogeneity. Results show collocated units without FDMS closely estimate actual PM_10-2.5 mass and spatial characteristics due to the very low semivolatile PM_10-2.5 concentrations in Colorado. Estimation using either a PM_2.5 or PM₁₀ monitor without FDMS introduced absolute biases of 2.4 µg/m³ (25%) to –2.3 µg/m³ (–24%), respectively. Such errors are directly related to the unmeasured semivolatile mass and alter measures of spatiotemporal variability and homogeneity, all of which have implications for the regulatory and epidemiology communities concerned about PM_10-2.5. Two monitoring sites operated by the state of Colorado were considered for inclusion in the CCRUSH acute health effects study, but concentrations were biased due to sampling with an FDMS-equipped PM_2.5 TEOM and PM₁₀ TEOM not corrected for semivolatile mass loss. A regression-based model was developed for removing the error in these measurements by estimating the semivolatile concentration of PM_2.5 from total PM_2.5 concentrations. By estimating nonvolatile PM_2.5 concentrations from this relationship, PM_10-2.5 was calculated as the difference between nonvolatile PM₁₀ and PM_2.5 concentrations.

Implications: Errors in the estimation of PM_10-2.5 concentrations using subtraction methods were shown to be related to the unmeasured semivolatile mass when using certain combinations of TEOM instruments. For the northeastern Colorado region, the absolute bias associated with this error significantly affects mean and 95th percentile values, which would affect assessment of compliance if PM_10-2.5 is regulated in the future. Estimating PM_10-2.5 mass concentrations using nonvolatile mass concentrations from collocated PM₁₀ and PM_2.5 TEOM monitors closely estimates the total PM_10-2.5 mass concentrations. A corrective model that removes the described error was developed and applied to data from two sites in Denver.

Supplemental Materials: Supplemental materials are available for this paper. Go to the publisher's online edition of the Journal of the Air & Waste Management Association.     

Near-road air pollutant concentrations of CO and PM2.5: A comparison of MOBILE6.2/CALINE4 and generalized additive models

The contribution of vehicular traffic to air pollutant concentrations is often difficult to establish. This paper utilizes both time-series and simulation models to estimate vehicle contributions to pollutant levels near roadways. The time-series model used generalized additive models (GAMs) and fitted pollutant observations to traffic counts and meteorological variables. A one year period (2004) was analyzed on a seasonal basis using hourly measurements of carbon monoxide (CO) and particulate matter less than 2.5 μm in diameter (PM_2.5) monitored near a major highway in Detroit, Michigan, along with hourly traffic counts and local meteorological data. Traffic counts showed statistically significant and approximately linear relationships with CO concentrations in fall, and piecewise linear relationships in spring, summer and winter. The same period was simulated using emission and dispersion models (Motor Vehicle Emissions Factor Model/MOBILE6.2; California Line Source Dispersion Model/CALINE4). CO emissions derived from the GAM were similar, on average, to those estimated by MOBILE6.2. The same analyses for PM_2.5 showed that GAM emission estimates were much higher (by 4–5 times) than the dispersion model results, and that the traffic-PM_2.5 relationship varied seasonally. This analysis suggests that the simulation model performed reasonably well for CO, but it significantly underestimated PM_2.5 concentrations, a likely result of underestimating PM_2.5 emission factors. Comparisons between statistical and simulation models can help identify model deficiencies and improve estimates of vehicle emissions and near-road air quality.     

Assessing the Relationship between Personal Particulate and Gaseous Exposures of Senior Citizens Living in Baltimore,MD

ABSTRACT

We conducted a multi-pollutant exposure study in Baltimore, MD, in which 15 non-smoking older adult subjects (>64 years old) wore a multi-pollutant sampler for 12 days during the summer of 1998 and the winter of 1999. The sampler measured simultaneous 24-hr integrated personal exposures to PM₂₅, PM₁₀, SO₄ ^2-, O₃, NO₂, SO₂, and exhaust-related VOCs.

Results of this study showed that longitudinal associations between ambient PM_2.5 concentrations and corresponding personal exposures tended to be high in the summer (median Spearman's r = 0.74) and low in the winter (median Spearman's r = 0.25). Indoor ventilation was an important determinant of personal PM_2.5 exposures and resulting personal-ambient associations. Associations between personal PM₂₅ exposures and corresponding ambient concentrations were strongest for well-ventilated indoor environments and decreased with ventilation. This decrease was attributed to the increasing influence of indoor PM_{2 5} sources. Evidence for this was provided by SO₄ ^2-measurements, which can be thought of as a tracer for ambient PM₂₅. For SO₄ ^2-, personal-ambient associations were strong even in poorly ventilated indoor environments, suggesting that personal exposures to PM_2.5 of ambient origin are strongly associated with corresponding ambient concentrations. The results also indicated that the contribution of indoor PM_2.5 sources to personal PM_2.5 exposures was lowest when individuals spent the majority of their time in well-ventilated indoor environments.

Results also indicate that the potential for confounding by PM_2.5 co-pollutants is limited, despite significant correlations among ambient pollutant concentrations. In contrast to ambient concentrations, PM_2.5 exposures were not significantly correlated with personal exposures to PM_2.5-10, PM_2.5 of non-ambient origin, O₃, NO₂, and SO₂. Since a confounder must be associated with the exposure of interest, these results provide evidence that the effects observed in the PM_2.5 epidemiologic studies are unlikely to be due to confounding by the PM_2.5 co-pollutants measured in this study.     

Airborne particle PM2.5/PM10 mass distribution and particle-bound PAH concentrations near a medical waste incinerator

This study attempts to determine the influence of air quality in a residential area near a medical waste incineration plant. Ambient air concentrations of polycyclic aromatic hydrocarbons (PAHs), PM₁₀ and PM_2.5 (PM—particulate matter) were determined by collecting air samples in areas both upwind and downwind of the plant. The differences in air pollutant levels between the study area and a reference area 11 km away from the plant were evaluated.Dichotomous samplers were used for sampling PM_2.5 and PM₁₀ from ambient air. Two hundred and twenty samples were obtained from the study area, and 100 samples were taken from a reference area. Samples were weighed by an electronic microbalance and concentrations of PM_2.5 and PM₁₀ were determined. A HPLC equipped with a fluorescence detector was employed to analyze the concentrations of 15 PAHs compounds adsorbed into PM_2.5 and PM₁₀.The experimental results indicated that the average concentrations of PM_2.5 and PM₁₀ were 30.34±17.95 and 36.81±20.45 μg m⁻³, respectively, in the study area, while the average ratio of PM_2.5/PM₁₀ was 0.82±0.01. The concentrations of PM_2.5 and PM₁₀ of the study area located downwind of the incinerator were significantly higher than the study area upwind of the incinerator (P<0.05).The concentration of PAHs in PM_2.5 in the study area was 2.2 times higher than in the reference area (P<0.05). Furthermore, the benzo(a)pyrene concentrations in PM_2.5 and PM₁₀ were 0.11±0.05 ng m⁻³ and 0.12±0.06 ng m⁻³ in the study area, respectively. The benzo(a)pyrene concentrations of PM_2.5 and PM₁₀ in the study area were 7 and 5.3 times higher than in the reference area (P<0.05), respectively.The study indicated that the air quality of PM_2.5, PM₁₀ and PAHs had significant contamination by air pollutants emitted from a medical waste incineration factory, representing a public health problem for nearby residences, despite the factory being equipped with a modern air pollution control system.     

Measurements of ultrafine particles and other vehicular pollutants inside school buses in South Texas

Increasing evidence has demonstrated toxic effects of vehicular emitted ultrafine particles (UFPs, diameter < 100 nm), with the highest human exposure usually occurring on and near roadways. Children are particularly at risk due to immature respiratory systems and faster breathing rates. In this study, children’s exposure to in-cabin air pollutants, especially UFPs, was measured inside four diesel-powered school buses. Two 1990 and two 2006 model year diesel-powered school buses were selected to represent the age extremes of school buses in service. Each bus was driven on two routine bus runs to study school children’s exposure under different transportation conditions in South Texas. The number concentration and size distribution of UFPs, total particle number concentration, PM_2.5, PM₁₀, black carbon (BC), CO, and CO₂ levels were monitored inside the buses. The average total particle number concentrations observed inside the school buses ranged from 7.3 × 10³ to 3.4 × 10⁴ particles cm^?3, depending on engine age and window position. When the windows were closed, the in-cabin air pollutants were more likely due to the school buses’ self-pollution. The 1990 model year school buses demonstrated much higher air pollutant concentrations than the 2006 model year ones. When the windows were open, the majority of in-cabin air pollutants came from the outside roadway environment with similar pollutant levels observed regardless of engine ages. The highest average UFP concentration was observed at a bus transfer station where approximately 27 idling school buses were queued to load or unload students. Starting-up and idling generated higher air pollutant levels than the driving state. Higher in-cabin air pollutant concentrations were observed when more students were on board.     

Effects of Wind Direction on Coarse and Fine Particulate Matter Concentrations in Southeast Kansas

Abstract

Field data for coarse particulate matter ([PM] PM₁₀) and fine particulate matter (PM_2.5) were collected at selected sites in Southeast Kansas from March 1999 to October 2000, using portable MiniVol particulate samplers. The purpose was to assess the influence on air quality of four industrial facilities that burn hazardous waste in the area located in the communities of Chanute, Independence, Fredonia, and Coffeyville. Both spatial and temporal variation were observed in the data. Variation because of sampling site was found to be statistically significant for PM₁₀ but not for PM_2.5. PM₁₀ concentrations were typically slightly higher at sites located within the four study communities than at background sites. Sampling sites were located north and south of the four targeted sources to provide upwind and downwind monitoring pairs. No statistically significant differences were found between upwind and downwind samples for either PM₁₀ or PM_2.5, indicating that the targeted sources did not contribute significantly to PM concentrations. Wind direction can frequently contribute to temporal variation in air pollutant concentrations and was investigated in this study. Sampling days were divided into four classifications: predominantly south winds, predominantly north winds, calm/variable winds, and winds from other directions. The effect of wind direction was found to be statistically significant for both PM₁₀ and PM_2.5. For both size ranges, PM concentrations were typically highest on days with predominantly south winds; days with calm/variable winds generally produced higher concentrations than did those with predominantly north winds or those with winds from “other” directions. The significant effect of wind direction suggests that regional sources may exert a large influence on PM concentrations in the area.     

The impact of airborne particulate matter on pediatric hospital admissions for pneumonia among children in Jinan,China: A case-crossover study

This study aims to examine the effect of short-term changes in the concentration of particulate matter of diameter ≤2.5 µm (PM_2.5) and ≤10 µm (PM₁₀) on pediatric hospital admissions for pneumonia in Jinan, China. It explores confoundings factors of weather, season, and chemical pollutants. Information on pediatric hospital admissions for pneumonia in 2014 was extracted from the database of Jinan Qilu Hospital. The relative risk of pediatric hospital admissions for pneumonia was assessed using a case-crossover approach, controlling weather variables, day of the week, and seasonality. The single-pollutant model demonstrated that increased risk of pediatric hospital admissions for pneumonia was significantly associated with elevated PM_2.5 concentrations the day before hospital admission and elevated PM₁₀ concentrations 2 days before hospital admission. An increment of 10 μg/m³ in PM_2.5 and PM₁₀ was correlated with a 6% (95% CI 1.02–-1.10) and 4% (95% CI 1.00–1.08) rise in number of admissions for pneumonia, respectively. In two pollutant models, PM_2.5 and PM₁₀ remained significant after inclusion of sulfur dioxide or nitrogen dioxide but not carbon monoxide. This study demonstrated that short-term exposure to atmospheric particulate matter (PM_2.5/PM₁₀) may be an important determinant of pediatric hospital admissions for pneumonia in Jinan, China.

Implications: This study demonstrated that short-term exposure to atmospheric particulate matter (PM_2.5/PM₁₀) may be an important determinant of pediatric hospital admissions for pneumonia in Jinan, China, and suggested the relevance of pollutant exposure levels and their effects. As a specific group, children are sensitive to airborne particulate matter. This study estimated the short-term effects attribute to other air pollutants to provide references for relevant studies.     

Impact of Covid-19 partial lockdown on PM2.5, SO2, NO2, O3, and trace elements in PM2.5 in Hanoi,Vietnam

Covid-19 lockdowns have improved the ambient air quality across the world via reduced air pollutant levels. This article aims to investigate the effect of the partial lockdown on the main ambient air pollutants and their elemental concentrations bound to PM_2.5 in Hanoi. In addition to the PM_2.5 samples collected at three urban sites in Hanoi, the daily PM_2.5, NO₂, O₃, and SO₂ levels were collected from the automatic ambient air quality monitoring station at Nguyen Van Cu street to analyze the pollution level before (March 10th–March 31st) and during the partial lockdown (April 1st–April 22nd) with “current” data obtained in 2020 and “historical” data obtained in 2014, 2016, and 2017. The results showed that NO₂, PM_2.5, O₃, and SO₂ concentrations obtained from the automatic ambient air quality monitoring station were reduced by 75.8, 55.9, 21.4, and 60.7%, respectively, compared with historical data. Besides, the concentration of PM_2.5 at sampling sites declined by 41.8% during the partial lockdown. Furthermore, there was a drastic negative relationship between the boundary layer height (BLH) and the daily mean PM_2.5 in Hanoi. The concentrations of Cd, Se, As, Sr, Ba, Cu, Mn, Pb, K, Zn, Ca, Al, and Mg during the partial lockdown were lower than those before the partial lockdown. The results of enrichment factor (EF) values and principal component analysis (PCA) concluded that trace elements in PM_2.5 before the partial lockdown were more affected by industrial activities than those during the partial lockdown.

     

Measurements of Ultrafine Particles and Other Vehicular Pollutants inside a Mobile Exposure System on Los Angeles Freeways

Abstract

A mobile exposure and air pollution measurement system was developed and used for on-freeway ultrafine particle health effects studies. A nine-passenger van was modified with a high-efficiency particulate air (HEPA) filtration system that can deliver filtered or unfiltered air to an exposure chamber inside the van. State-of-the-art instruments were used to measure concentration and size distribution of fine and ultrafine particles and the concentration of carbon monoxide (CO), black carbon (BC), particle-bound polycyclic aromatic hydrocarbons (PAHs), fine particulate matter (PM_2.5) mass, and oxides of nitrogen (NO_x) inside the exposure chamber. This paper presents the construction and technical details of the van and air pollutant concentrations collected in 32 2-hr runs on two major Los Angeles freeways, Interstate 405 (I-405; mostly gasoline traffic) and Interstate 710 (I-710; large proportion of heavy-duty diesel traffic). More than 97% of particles were removed when the flow through the filter box was switched from bypass mode to filter mode while the vehicle was driving on both freeways. The filtration system thus provides a great particulate matter exposure contrast while keeping gas-phase pollutant concentrations the same. Under bypass mode, average total particle number concentration observed inside the exposure chamber was around 8.4 × 10⁴ and 1.3 × 10⁵ particles cm^-3 on the I-405 and the I-710 freeways, respectively. Bimodal size distributions were consistent and similar for both freeways with the first mode around 16–20 nm and the second mode around 50–55 nm. BC and particle-bound PAH concentrations were more than two times greater on the I-710 than on the I-405 freeway. Very weak correlations were observed between total particle number concentrations and other vehicular pollutants on the freeways.     

Seasonal variation of ionic species in fine particles at Qingdao,China

Totally nine measurement campaigns for ambient particles and SO₂ have been conducted during the period of 1997–2000 in Qingdao in order to understand the characteristics of the particulate matter in coastal areas of China. The mass fractions of PM_2.5, PM_2.5−10 and PM_>10 in TSP are 49%, 25% and 26%, respectively. The size distribution of particles mass concentrations in Qingdao shows bi-modal distribution. Mass fraction percentages of water-soluble ions in PM_2.5, PM_2.5−10 and PM_>10 decreased from 62% to 35% and 21%. In fine particles, sulfate, nitrate and ammonium, secondary formed compounds, are major components, totally accounting for 50% of PM_2.5 mass concentration.The ratios of sulfate, chloride, ammonium and potassium in PM_2.5 for heating versus non-heating periods are 1.34, 1.80, 1.56 and 1.44, respectively. The ratio of nitrate is 3.02 and this high ratio could be caused by reduced volatilization at lower temperature. Sulfate concentrations are higher than nitrate in PM_2.5. The chemical forms of sulfate and nitrate are probably (NH₄)₂SO₄ and NH₄NO₃ and chloride depletion was observed.Backward trajectory analysis reflected possible influence of air pollutant transport to Qingdao local aerosol pollution.     

Prescribed Burns and Wildfires in Colorado: Impacts of Mitigation Measures on Indoor Air Particulate Matter

Abstract

Wildfires and prescribed burns are receiving increasing attention as sources of fine particulate matter (PM_2.5). The goal of this research project was to understand the impact of mitigation strategies for residences impacted by scheduled prescribed burns and wildfires. Pairs of residences were solicited to have PM_2.5 concentrations monitored inside and outside of their houses during four fires. The effect of using air cleaners on indoor PM_2.5 was investigated, as well as the effect of keeping windows closed. Appropriately sized air cleaners were provided to one of each pair of residences; occupants of all of the residences were asked to keep windows shut and minimize opening of exterior doors. Additionally, residents were asked to record all of the activities that may be a source of particulate matter, such as cooking and cleaning. Measurements were made during one prescribed burn and three wildfires during the 2002 fire season. Outdoor 24‐hr average PM_2.5 concentrations ranging from 6 to 38 µg/m³ were measured during the fires, compared with levels of 2–5 µg/m³ during background measurements when no fires were burning. During the fires, PM_2.5 was <3 µg/m³ inside all of the houses with air cleaners installed. This corresponds with a decrease of 63–88% in homes with the air cleaners operating when compared with homes without air cleaners. In the homes without the air cleaners, measured indoor concentrations were 58–100% of the concentrations measured outdoors.