Comparison of Short-Term Variations (15-Minute Averages) in Outdoor and Indoor PM2.5 Concentrations

ABSTRACT

Measurements of 15-min average PM_2.5 concentrations were made with a real-time light-scattering instrument at both outdoor (central monitoring sites in three communities) and indoor (residential) locations over two seasons in the Minneapolis-St. Paul metropolitan area. These data are used to examine within-day variability of PM_2.5 concentrations indoors and outdoors, as well as matched indoor-to-outdoor (I/O) ratios. Concurrent gravimetric measurements of 24-hr average PM_2.5 concentrations were also obtained as a way to compare real-time measures with this more traditional metric. Results indicate that (1) within-day variability for both indoor and outdoor 15-min average PM_2.5 concentrations was substantial and comparable in magnitude to day-to-day variability for 24hr average concentrations; (2) some residences exhibited substantial variability in indoor aerosol characteristics from one day to the next; (3) peak values for indoor short-term (15-min) average PM_2.5 concentrations routinely exceeded 24-hr average outdoor values by factors of 3-4; and (4) relatively strong correlations existed between indoor and outdoor PM_2.5 concentrations for both 24-hr and 15-min averages.     

Geochemical behaviour of dissolved trace elements in a monsoon-dominated tropical river basin,Southwestern India

The study presents a 3-year time series data on dissolved trace elements and rare earth elements (REEs) in a monsoon-dominated river basin, the Nethravati River in tropical Southwestern India. The river basin lies on the metamorphic transition boundary which separates the Peninsular Gneiss and Southern Granulitic province belonging to Archean and Tertiary–Quaternary period (Western Dharwar Craton). The basin lithology is mainly composed of granite gneiss, charnockite and metasediment. This study highlights the importance of time series data for better estimation of metal fluxes and to understand the geochemical behaviour of metals in a river basin. The dissolved trace elements show seasonality in the river water metal concentrations forming two distinct groups of metals. First group is composed of heavy metals and minor elements that show higher concentrations during dry season and lesser concentrations during the monsoon season. Second group is composed of metals belonging to lanthanides and actinides with higher concentration in the monsoon and lower concentrations during the dry season. Although the metal concentration of both the groups appears to be controlled by the discharge, there are important biogeochemical processes affecting their concentration. This includes redox reactions (for Fe, Mn, As, Mo, Ba and Ce) and pH-mediated adsorption/desorption reactions (for Ni, Co, Cr, Cu and REEs). The abundance of Fe and Mn oxyhydroxides as a result of redox processes could be driving the geochemical redistribution of metals in the river water. There is a Ce anomaly (Ce/Ce*) at different time periods, both negative and positive, in case of dissolved phase, whereas there is positive anomaly in the particulate and bed sediments. The Ce anomaly correlates with the variations in the dissolved oxygen indicating the redistribution of Ce between particulate and dissolved phase under acidic to neutral pH and lower concentrations of dissolved organic carbon. Unlike other tropical and major world rivers, the effect of organic complexation on metal variability is negligible in the Nethravati River water.     

Retrospective exposure assessment in a chemical research and development facility

The objective of this exposure assessment was to reconstruct cumulative historical exposures for workers who have been exposed to multiple chemicals and chemical groups to better understand a cluster of brain cancers within a research and development lab. Chemicals of interest, including acrylates, bis-chloromethyl ether (BCME), chloromethyl methyl ether (CMME), isothiazolones and nitrosoamines, were selected on the basis of the plausibility of penetrating the blood-brain barrier and the uniqueness of the chemical's biological activity.In a complicated exposure setting such as a chemical R&D facility, multiple exposure estimation methods were needed. First, similarly exposure groups (SEGs) were created for these materials based on department group, time period of the department's existence and function associated with job titles. A probabilistic framework for assessing exposures was developed using Bayesian analysis of historical monitoring data, mathematical exposure modeling and professional judgments of current and former industrial hygienists at the facility were used to reconstruct the exposure history for acrylates, BCME and CMME for each SEG over the time period of interest. Since sufficient measurement data for isothiazolones and nitrosoamines were not available, the exposure histories for each SEG for these chemicals were estimated. This was done using objective formaldehyde levels and subjective employee interviews. The interviews assessed workplace determinants of exposure as distinct surrogates for estimating inhalation and dermal exposures. The exposure assessments by these methods were compared against each other to estimate the potential for exposure misclassification. A job exposure matrix (JEM) was constructed that contained the exposures obtained from above multiple approaches for each of these chemical groups for each SEG for each year of interest. The combination of methods used in this work is a unique and potentially helpful framework that can be used in analogous workplace settings involving multiple exposures with incomplete objective measurement information.     

Mass, surface area and number metrics in diesel occupational exposure assessment

While diesel aerosol exposure assessment has traditionally been based on the mass concentration metric, recent studies have suggested that particle number and surface area concentrations may be more health-relevant. In this study, we evaluated the exposures of three occupational groups-bus drivers, parking garage attendants, and bus mechanics-using the mass concentration of elemental carbon (EC) as well as surface area and number concentrations. These occupational groups are exposed to mixtures of diesel and gasoline exhaust on a regular basis in various ratios. The three groups had significantly different exposures to workshift TWA EC with the highest levels observed in the bus garage mechanics and the lowest levels in the parking ramp booth attendants. In terms of surface area, parking ramp attendants had significantly greater exposures than bus garage mechanics, who in turn had significantly greater exposures than bus drivers. In terms of number concentrations, the exposures of garage mechanics exceeded those of ramp booth attendants by a factor of 5-6. Depending on the exposure metric chosen, the three occupational groups had quite different exposure rankings. This illustrates the importance of the choice of exposure metric in epidemiological studies. If these three occupational groups were part of an epidemiological study, depending on the metric used, they may or may not be part of the same similarly exposed group (SEG). The exposure rankings (e.g., low, medium, or high) of the three groups also changes with the metric used. If the incorrect metric is used, significant misclassification errors may occur.     

Enhanced bioleaching of copper from circuit boards of computer waste by Acidithiobacillus ferrooxidans

Environmental Chemistry Letters - Computer circuit boards are a major electronic waste containing higher concentrations of copper, gold and silver. These metals may be recovered by bioleaching, an...     

Mesoporous carbon nanospheres derived from agro-waste as novel antimicrobial agents against gram-negative bacteria

Environmental Science and Pollution Research - Porous carbon nanospheres were synthesized from agro-waste garlic peels by a one-pot facile and easy to scale-up pyrolysis method. Surface morphology...     

Study of specific energy and friction coefficient in minimum quantity lubrication grinding using oil-based nanolubricants

An investigation on minimum quantity lubrication (MQL) grinding was carried out with the scope of documenting the process efficiency of oil-based nanolubricants. The nanolubricants were composed of MoS₂ nanoparticles (<100 nm) over coated with organic agents, dispersed in two different base oils—mineral oil (paraffin) and vegetable oil (soybean). Surface grinding tests were carried out on cast iron and EN 24 steel under different lubrication conditions—MQL using nanolubricants (varying compositional chemistry and concentration of nanoparticles), pure base oils (without nanoparticles) and base oils containing MoS₂ microparticles (3–5 μm), and flood grinding using water-based coolant. Specific energy, friction coefficient in grinding and G-ratio were used as measurands for determining the process efficiency. Results show that MQL grinding with nanolubricants increases the process efficiency by reducing energy consumption, frictional losses at the wheel–workpiece interface and tool wear. The process efficiency is also found to increase with increasing nanoparticle concentration. Soybean and paraffin based-nanolubricant performed best for steel and cast iron, respectively, showing a possible functional relationship between the compositional chemistry of nanolubricant and the workpiece material, which will be the goal of future work.     

Dissolved trace element biogeochemistry of a tropical river, Southwestern India

River Swarna, a small tropical river originating in Western Ghats (at an altitude of 1,160 m above mean sea level) and flowing in the southwest coast of India discharges an average of 54 m³s^?1 of water into the Arabian Sea, of which significant part is being discharged during the monsoon. No studies have been made yet on the water chemistry of the Swarna River basin, even as half a million people of Udupi district use it for domestic and irrigational purposes. As large community in this region depends on the freshwater of Swarna River, there is an urgent need to study the trace element geochemistry of this west flowing river for better water management and sustainable development. The paper presents the results on the biogeochemistry of dissolved trace elements in the Swarna River for a period of 1 year. The results obtained on the trace elements show seasonal effect on the concentrations as well as behavior and thus forming two groups, discharge driven (Li, Be, Al, V, Cr, Ni, Zr, In, Pb, Bi and U) and base flow driven (groundwater input; Mn, Fe, Co, Cu, Ga, Zn, As, Se, Rb, Sr, Ag, Cd, Cs, Ba and Tl) trace elements in Swarna River. The biogeochemical processes explained through Hierarchical Cluster Analysis show complexation of Fe, Ga and Ba with dissolved organic carbon, redox control over Mn and Tl and biological control over V and Ni. Also, the water quality of Swarna River remains within the permissible limits of drinking water standards.     

Comparison of two estimation methods for surface area concentration using number concentration and mass concentration of combustion-related ultrafine particles

Recent research has suggested that the adverse health effects caused by nanoparticles are associated with their surface area (SA) concentrations. In this study, SA was estimated in two ways using number and mass concentrations and compared with SA (SA_meas) measured using a diffusion charger (DC). Aerosol measurements were made twice: once starting in October 2002 and again starting in December 2002 in Mysore, India in residences that used kerosene or liquefied petroleum gas (LPG) for cooking. Mass, number, and SA concentrations and size distributions by number were measured in each residence. The first estimation method (SA_PSD) used the size distribution by number to estimate SA. The second method (SA_INV) used a simple inversion scheme that incorporated number and mass concentrations while assuming a lognormal size distribution with a known geometrical standard deviation. SA_PSD was, on average, 2.4 times greater (range = 1.6–3.4) than SA_meas while SA_INV was, on average, 6.0 times greater (range = 4.6–7.7) than SA_meas. The logarithms of SA_PSD and SA_INV were found to be statistically significant predictors of the logarithm of SA_meas. The study showed that particle number and mass concentration measurements can be used to estimate SA with a correction factor that ranges between 2 and 6.