Application of artificial intelligence algorithms and low-cost sensors to estimate respirable dust in the workplace.

The Internet of Things (IoT) and low-cost sensor technology have become common tools for environmental exposure monitoring; however, their application in measuring respirable dust (RD) in the workplace remains limited. This study aimed to develop a predictive model for RD using artificial intelligence (AI) algorithms and low-cost sensors and subsequently assess its validity using a standard sampling approach. Various low-cost sensors were combined into an RD sensor module and mounted on a portable aerosol monitor (GRIMM 11-D) for two weeks. AI algorithms were used to capture data per minute over 14 days to establish predictive RD models. The best-fitting model was validated using an aluminum cyclone equipped with an air pump and polytetrafluoroethylene filters to sample the 8-hour RD for 5 days at an aircraft manufacturing company. This module was continuously monitored for two weeks to evaluate its stability. The RD concentration measured by GRIMM 11-D in a general outdoor environment over two weeks was 28.1 ± 16.1 µg/m3 (range: 2.4-85.3 µg/m3). Among the various established models, random forest regression was observed to have the best prediction capacity (R2 = 0.97 and root mean square error = 2.82 µg/m3) in comparison to the other 19 methods. Field-based validation revealed that the predicted RD concentration (35.9 ± 4.1 µg/m3, range: 32.7-42.9 µg/m3) closely approximated the results obtained by the traditional method (38.1 ± 8.9 µg/m3, range: 28.1-52.5 µg/m3), and a strong positive Spearman correlation was observed between the two (rs = 0.70). The average bias was -2.2 µg/m3 and the precision was 5.8 µg/m3, resulting in an accuracy of 6.2 µg/m3 (94.2 %). Data completeness was 99.7 % during the continuous two-week monitoring period. The developed sensor module of RD exhibited excellent predictive performance and good data stability that can be applied to exposure assessments in occupational epidemiological studies.

A hybrid model for estimating the number concentration of ultrafine particles based on machine learning algorithms in central Taiwan.

Modeling is a cost-effective measure to estimate ultrafine particle (UFP) levels. Previous UFP estimates generally relied on land-use regression with insufficient temporal resolution. We carried out in-situ measurements for UFP in central Taiwan and developed a model incorporating satellite-based measurements, meteorological variables, and land-use data to estimate daily UFP levels at a 1-km resolution. Two sampling campaigns were conducted for measuring hourly UFP concentrations at six sites between 2008-2010 and 2017-2021, respectively, using scanning mobility particle sizers. Three machine learning algorithms, namely random forest, eXtreme gradient boosting (XGBoost), and deep neural network, were used to develop UFP estimation models. The performances were evaluated with a 10-fold cross-validation, temporal, and spatial validation. A total of 1,022 effective sampling days were conducted. The XGBoost model had the best performance with a training coefficient of determination (R2) of 0.99 [normalized root mean square error (nRMSE): 6.52%] and a cross-validation R2 of 0.78 (nRMSE: 31.0%). The ten most important variables were surface pressure, distance to the nearest road, temperature, calendar year, day of the year, NO2, meridional wind, the total length of roads, PM2.5, and zonal wind. The UFP levels were elevated along the main roads across different seasons, suggesting that traffic emission is an important contributor to UFP. This hybrid model outperformed prior land use regression models and thus can provide more accurate estimates of UFP for epidemiological studies.

Sources, transport, and visibility impact of ambient submicrometer particle number size distributions in an urban area of central Taiwan.

This study applied positive matrix factorization (PMF) to identify the sources of size-resolved submicrometer (10-1000 nm) particles and quantify their contributions to impaired visibility based on the particle number size distributions (PNSDs), aerosol light extinction (bp), air pollutants (PM10, PM2.5, SO2, O3, and NO), and meteorological parameters (temperature, relative humidity, wind speed, wind direction, and ultraviolet index) measured hourly over an urban basin in central Taiwan between 2017 and 2021. The transport of source-specific PNSDs was evaluated with wind and back trajectory analyses. The PMF revealed six sources to the total particle number (TPN), surface (TPS), volume (TPV), and bp. Factor 1 (F1), the key contributor to TPN (35.0 %), represented nucleation (<25 nm) particles associated with fresh traffic emission and secondary new particle formation, which were transported from the west-southwest by stronger winds (>2.2 m s-1). F2 represented the large Aitken (50-100 nm) particles transported regionally via northerly winds, whereas F3 represented large accumulation (300-1000 nm) particles, which showed elevated concentrations under stagnant conditions (<1.1 m s-1). F4 represented small Aitken (25-50 nm) particles arising from the growth and transport of the nucleation particles (F1) via west-southwesterly winds. F5 represented large Aitken particles originating from combustion-related SO2 sources and carried by west-northwesterly winds. F6 represented small accumulation (100-300 nm) particles emitted both by local sources and by the remote SO2 sources found for F5. Overall, large accumulation particles (F3) played the greatest role in determining the TPV (66.4 %) and TPS (34.8 %), and their contribution to bp increased markedly from 17.3 % to 40.7 % as visibility decreased, indicating that TPV and TPS are better metrics than TPN for estimating bp. Furthermore, slow-moving air masses-and therefore stagnant conditions-facilitate the build-up of accumulation mode particles (F3 + F6), resulting in the poorest visibility.

Secondary inorganic aerosol chemistry and its impact on atmospheric visibility over an ammonia-rich urban area in Central Taiwan.

This study investigated the hourly inorganic aerosol chemistry and its impact on atmospheric visibility over an urban area in Central Taiwan, by relying on measurements of aerosol light extinction, inorganic gases, and PM2.5 water-soluble ions (WSIs), and simulations from a thermodynamic equilibrium model. On average, the sulfate (SO42-), nitrate (NO3-), and ammonium (NH4+) components (SNA) contributed ∼90% of WSI concentrations, which in turn made up about 50% of the PM2.5 mass. During the entire observation period, PM2.5 and SNA concentrations, aerosol pH, aerosol liquid water content (ALWC), and sulfur and nitrogen conversion ratios all increased with decreasing visibility. In particular, the NO3- contribution to PM2.5 increased, whereas the SO42- contribution decreased, with decreasing visibility. The diurnal variations of the above parameters indicate that the interaction and likely mutual promotion between NO3- and ALWC enhanced the hygroscopicity and aqueous-phase reactions conducive for NO3- formation, thus led to severely impaired visibility. The high relative humidity (RH) at the study area (average 70.7%) was a necessary but not sole factor leading to enhanced NO3- formation, which was more directly associated with elevated ALWC and aerosol pH. Simulations from the thermodynamic model depict that the inorganic aerosol system in the study area was characterized by fully neutralized SO42- (i.e. a saturated factor in visibility reduction) and excess NH4+ amidst a NH3-rich environment. As a result, PM2.5 composition was most sensitive to gas-phase HNO3, and hence NOx, and relatively insensitive to NH3. Consequently, a reduction of NOx would result in instantaneous cuts of NO3-, PM2.5, and ALWC, and hence improved visibility. On the other hand, a substantial amount of NH3 reduction (>70%) would be required to lower the aerosol pH, driving more than 50% of the particulate phase NO3- to the gas phase, thereby making NH3 a limiting factor in shifting PM2.5 composition.

Insights to the 3D internal morphology and metal oxidation states of single atmospheric aerosol particles by synchrotron-based methodology.

The morphology and metal oxidation states of atmospheric aerosols are pertinent to their formation processes and ensuing interactions with surrounding gases, vapors and other environments upon deposition, such as human respiratory tract, soil and water. Although much progress has been made in recent years through single-particle techniques, considerably less is known with respect to the three-dimensional (3D) internal morphology of single atmospheric aerosol particles due to the limited penetration depth of electron microscopy. In this study, for the first time, a novel synchrotron-based transmission X-ray microscopy (TXM) methodology has been developed to visualize the 3D internal chemical mixing state and structure of single particles. The results show that the TXM is more applicable to the imaging of solid particles containing high-density elements, e.g., iron (Fe), aluminum (Al), silicone (Si), carbon (C) and sulfur (S), and/or solid particles of sizes larger than about 100 nm. In addition, the TXM is capable to reveal the fine 3D topographic features of single particles. The derived 3D internal and external information would be difficult to discern in the 2D images from electron microscopy. The TXM 3D images illustrate that aerosol particles exhibit complex internal mixing state and structure, e.g., homogeneously-, heterogeneously-mixed, multiple inclusions, fibrous, porous, and core-shell configuration. When coupled with the synchrotron-based X-ray fluorescence spectrometry (XRF) and absorption near-edge spectroscopy (XANES) of an X-ray nanoprobe in the energy range of 4-15 keV, the 3D morphology of single particles is further supplemented with the spatial distribution and oxidation sates of selected elements, including Fe, vanadium (V), manganese (Mn), chromium (Cr) and arsenic (As). The presented cross-platform, synchrotron-based methodology shows promise in complementing existing single-particle techniques and providing new insights to the heterogeneity of single-particle micro-physicochemical states relevant to the aerosol chemistry, optical properties, and their environmental and health impacts.

Elevated emissions of volatile and nonvolatile nanoparticles from heavy-duty diesel engine running on diesel-gas co-fuels.

This study experimentally examines the effects of four diesel-gas co-fuels, two engine loads and an aftertreatment on regulated and unregulated emissions from a 6-cylinder natural-aspirated direct-injection heavy-duty diesel engine (HDDE) with an engine dynamometer. Fuel energy of ultra-low-sulfur diesel was substituted with 10% and 20% of gas fuels, including pure H2, CH4, and two CH4-CO2 blends. The particle number size distributions of volatile and nonvolatile nanoparticles were measured under ambient temperature and after 300 °C heating, respectively. The results show that the gas fuels caused increases of hydrocarbon emission, slight changes of NOx emission, and decreases of opacity. All four gas fuels resulted in elevated emissions of both volatile and nonvolatile nanoparticles at 25% and 75% load, in the range of 29% to 390%. The increased emissions of volatile nanoparticles were variable and without obvious trends. Special attentions should be given to the addition of H2 under high load, during which significant increases of volatile nanoparticles could be formed not only post-combustion (up to 1376%), but also post-diesel oxidation catalyst plus diesel particulate filter (DOC + DPF). The nonvolatile nanoparticles, on the other hand, could be effectively removed by the retrofitted DOC + DPF, with efficiency >98.2%. A noteworthy fraction of solid particles of sizes <23 nm were found in the exhaust, not being accounted for by current regulatory emission standard.

Quantifying the impacts of PM2.5 constituents and relative humidity on visibility impairment in a suburban area of eastern Asia using long-term in-situ measurements.

The deterioration of visibility due to air pollutants and relative humidity has been a serious environmental problem in eastern Asia. In most previous studies, chemical compositions of atmospheric particles were provided using filter-based offline analyses, which were unable to provide long-term and in-situ measurements that resolve sufficient temporal variations of air pollution and meteorology, hindering the resolution of the relationship between air quality and visibility. Here, we present a year-long continuously measured data from a comprehensive suite of online instruments to investigate diurnal and seasonal impacts of the aerosol chemical compositions in PM2.5 on visibility seasonally and diurnally. The measured dry aerosol extinction at λ = 550 nm reached a closure with that predicted by aerosol compositions within 12%. However, the hygroscopic growth of particles under ambient RH could enhance the aerosol extinction by a factor of 2-6, matching the perceptive visibility of the public. Particulate ammonium nitrate was most sensitive to reducing visibility, while ammonium sulfate contributed the most to the light extinction. In spring and winter, the monsoon and stagnant air masses reduced the visibility and increased PM2.5 (>35 µg m-3). The moisture was found to substantially enhance the light extinction under RH = 60-90%, reducing visibility by approximately 15 km, largely attributed to hygroscopic inorganic salts. This study serves as a metric to highlight the need to consider the influence of RH, and aqueous reactions in producing secondary inorganic aerosols on atmospheric visibility, underpinning the more accurate mitigation strategies of air pollution.

Chemically and temporally resolved oxidative potential of urban fine particulate matter.

Vehicle emissions are an important source of particulate matter (PM) in urban areas and have well-known adverse health effects on human health. Oxidative potential (OP) is used as a quantification metric for indexing PM toxicity. In this study, by using a liquid spot sampler (LSS) and the dithiothreitol (DTT) assay, the diurnal OP variation was assessed at a ground-level urban monitoring station. Besides, since the monitoring station was adjacent to the main road, the correlation between OP and traffic volume was also evaluated. PM components, including metals, water-soluble inorganic aerosols (WSIAs), black carbon (BC), and polycyclic aromatic hydrocarbons (PAHs), were also simultaneously monitored. The daytime and evening mean ±â€¯std volume-normalized OP (OPv) were 0.46 ±â€¯0.27 and 0.48 ±â€¯0.26 nmol/min/m3, and exhibited good correlations with PM1.0 and BC; however, these concentrations were only weakly correlated with mass-normalized OP (OPm). The mean ±â€¯std OPm was higher in the daytime (41.3 ±â€¯13.8 pmol/min/µg) than in the evening (36.1 ±â€¯11.5 pmol/min/µg). According to the PMF analysis, traffic emissions dominated the diurnal OP contribution. Organic matter and individual metals associated with non-exhaust traffic emissions, such as Mn, Fe, and Cu, contributed substantially to OP. Diurnal variations of PAH concentrations suggest that photochemical reactions could enhance OP, highlighting the importance of atmospheric aging on PM toxicity.

Occupational noise exposure and its association with incident hyperglycaemia: a retrospective cohort study.

Noise pollution is reported to be associated with diabetes, but few studies have elucidated the associations between noise frequency characteristics. We aimed to evaluate the relationships between different noise frequency components and incident hyperglycaemia. An industry-based cohort of 905 volunteers was enrolled and followed up to 2012. Octave-band frequencies of workstation noise and individual noise levels were measured in 2012 to classify subjects' exposures retrospectively. We applied Cox regression models to estimate the relative risk (RR) of hyperglycaemia. An increased RR for hyperglycaemia of 1.80 (95% confidence interval [CI]: 1.04, 3.10) was found among subjects exposed to ≥ 85 A-weighted decibels (dBA) compared with those exposed to < 70 dBA. The high-exposure groups at frequencies of 31.5, 63, 125, 250, 500, 1000, and 2000 Hz had a significantly higher risk of hyperglycaemia (all p values < 0.050) than the low-exposure groups. A 5-dB increase in noise frequencies at 31.5, 63, 125, 250, 500 Hz, and 1000 Hz was associated with an elevated risk of hyperglycaemia (all p values < 0.050), with the highest value of 1.27 (95% CI: 1.10, 1.47) at 31.5 Hz (p = 0.001). Occupational noise exposure may be associated with an increased incidence of hyperglycaemia, with the highest risk observed at 31.5 Hz.

An instantaneous spatiotemporal model for predicting traffic-related ultrafine particle concentration through mobile noise measurements.

People living near roadways are exposed to high concentrations of ultrafine particles (UFP, diameter < 100 nm). This can result in adverse health effects such as respiratory illness and cardiovascular diseases. However, accurately characterizing the UFP number concentration requires expensive sets of instruments. The development of an UFP surrogate with cheap and convenient measures is needed. In this study, we used a mobile measurement platform with a Fast Mobility Particle Sizer (FMPS) and sound level meter to investigate the spatiotemporal relations of noise and UFP and identify the hotspots of UFP. UFP concentration levels were significantly influenced by temporal and spatial variations (p < 0.001). We proposed a Generalized Additive Models to predict UFP number concentration in the study area. The model uses noise and meteorological covariates to predict the UFP number concentrations at an industrial site in Taichung, Taiwan. During the one year sampling campaign from fall 2013 to summer 2014, mobile measurements were performed at least one week for each season, both on weekdays and weekends. The proposed model can explain 80% of deviance and has coefficient of determination (R2) of 0.77. Moreover, the developed UFP model was able to adequately predict UFP concentrations, and can provide people with a convenient way to determine UFP levels. Finally, the results from this study could help facilitate the future development of noise mobile measurement.

Mass-size distribution and concentration of metals from personal exposure to arc welding fume in pipeline construction: a case report.

We investigate exposure to welding fume metals in pipeline construction, which are responsible for severe respiratory problems. We analyzed air samples obtained using size-fractioning cascade impactors that were attached to the welders performing shielded metal and gas tungsten arc welding outdoors. Iron, aluminum, zinc, chromium, manganese, copper, nickel, and lead concentrations in the water-soluble (WS) and water-insoluble (WI) portions were determined separately, using inductively coupled plasma mass spectrometry. The mass-size distribution of welding fume matches a log-normal distribution with two modes. The metal concentrations in the welding fume were ranked as follows: Fe>Al>Zn>Cr>Mn>Ni>Cu>Pb. In the WS portion, the capacities of metals dissolving in water are correlated with the metal species but particle sizes. Particularly, Zn, Mn, and Pb exhibit relatively higher capacities than Cu, Cr, Al, Fe, and Ni. Exposure of the gas-exchange region of the lungs to WS metals were in the range of 4.9% to 34.6% of the corresponding metals in air by considering the particle-size selection in lungs, metal composition by particle size, and the capacities of each metal dissolving in water.

PM2.5 components and outpatient visits for asthma: A time-stratified case-crossover study in a suburban area.

The effects of fine particles (PM2.5) on asthma have been widely confirmed by epidemiological research studies. However, a limited number of studies have investigated the relationship between exposure to different PM2.5 components and asthma. We characterized the PM2.5 components in a suburban site of central Taiwan and conducted a time-stratified case-crossover study to elaborate the effects of daily concentration of each PM2.5 component on asthma outpatient visits. We retrieved asthma outpatient claims for individuals less than 20 years old with a residential address in the Shalu district, Taiwan, from the National Health Insurance Research Database during 2000-2010. Multiple linear regression models were used to back extrapolate the historic concentration of individual components of PM2.5 from 2000 through to 2010, including black carbon (BC) and eight ions, namely, sulfate, nitrate (NO3-), ammonium, chloride, potassium (K+), magnesium, calcium, sodium. The odds ratio (OR) with a 95% confidence interval (CI) of individual PM2.5 components on asthma was estimated by conditional logistic regression. A total of 887 asthma outpatient visits with individuals who have an average age of 7.96±3.88 years were selected. After adjusting for confounders, we found an interquartile range (IQR) increase in BC level, an IQR increase in NO3- level, and an IQR increase in K+ level that were all associated with the increased risk of asthma outpatient visits from the current day (OR = 1.18, 95% CI: 1.05-1.34; OR = 1.11, 95% CI: 1.01-1.21; and OR = 1.16, 95% CI: 1.04-1.30, respectively). The effects of these components on asthma were stronger in the cold season than in the warm season. However, we did not find any lagging effects. The results suggest that exposure to NO3-, BC, and K+ derived from industry-related combustion or motor vehicles emission sources may increase the risk of asthma outpatient visits, particularly during the cold season.

Occupational Noise Frequencies and the Incidence of Hypertension in a Retrospective Cohort Study.

Occupational noise exposure is associated with cardiovascular disease, but little is known about the contributions of noise frequency components. This retrospective study investigated the relationship between exposure to different noise frequencies and the incidence of hypertension. A cohort of 1,002 volunteers from 4 machinery and equipment manufacturing companies in Taichung, Taiwan, was followed from 1973 to 2012. Personal noise measurements and environmental octave-band analyses were performed to divide subjects into different exposure groups. Cox regression models were used to estimate the relative risk of hypertension. Participants exposed to ≥80 A-weighted decibels (dBA) over 8 years had a higher relative risk of hypertension (relative risk = 1.38, 95% confidence interval: 1.02, 1.85) compared with those exposed to <75 dBA. Significant exposure-response patterns were observed between incident hypertension and stratum of noise exposure at frequencies of 250 Hz, 1 kHz, 2 kHz, 4 kHz, and 8 kHz. The strongest effect was found at 4 kHz; a 20-dBA increase in noise exposure at 4 kHz was associated with a 34% higher risk of hypertension (relative risk = 1.34, 95% confidence interval: 1.01, 1.77). Occupational noise exposure may be associated with an increased risk of hypertension, and the 4 kHz component of occupational noise exposure may have the strongest relationship with hypertension.

Carbonaceous composition changes of heavy-duty diesel engine particles in relation to biodiesels, aftertreatments and engine loads.

Three biodiesels and two aftertreatments were tested on a heavy-duty diesel engine under the US FTP transient cycle and additional four steady engine loads. The objective was to examine their effects on the gaseous and particulate emissions, with emphasis given to the organic and elemental carbon (OC and EC) in the total particulate matter. Negligible differences were observed between the low-sulfur (B1S50) and ultralow-sulfur (B1S10) biodiesels, whereas small reductions of OC were identified with the 10% biodiesel blend (B10). The use of diesel oxidation catalyst (DOC1) showed moderate reductions of EC and particularly OC, resulting in the OC/EC ratio well below unity. The use of DOC plus diesel particulate filter (DOC2+DPF) yielded substantial reductions of OC and particularly EC, resulting in the OC/EC ratio well above unity. The OC/EC ratios were substantially above unity at idle and low load, whereas below unity at medium and high load. The above changes in particulate OC and EC are discussed with respect to the fuel content, pollutant removal mechanisms and engine combustion conditions. Overall, the present study shows that the carbonaceous composition of PM could change drastically with engine load and aftertreatments, and to a lesser extent with the biodiesels under study.

Reducing emissions of persistent organic pollutants from a diesel engine by fueling with water-containing butanol diesel blends.

The manufacture of water-containing butanol diesel blends requires no excess dehydration and surfactant addition. Therefore, compared with the manufacture of conventional bio-alcohols, the energy consumption for the manufacture of water-containing butanol diesel blends is reduced, and the costs are lowered. In this study, we verified that using water-containing butanol diesel blends not only solves the tradeoff problem between nitrogen oxides (NOx) and particulate matter emissions from diesel engines, but it also reduces the emissions of persistent organic pollutants (POPs), including polycyclic aromatic hydrocarbons, polychlorinated dibenzo-p-dioxins and dibenzofurans, polychlorinated biphenyls, polychlorinated diphenyl ethers, polybrominated dibenzo-p-dioxins and dibenzofurans, polybrominated biphenyls and polybrominated diphenyl ethers. After using blends of B2 with 10% and 20% water-containing butanol, the POP emission factors were decreased by amounts in the range of 22.6%-42.3% and 38.0%-65.5% on a mass basis, as well as 18.7%-78.1% and 51.0%-84.9% on a toxicity basis. The addition of water-containing butanol introduced a lower content of aromatic compounds and most importantly, lead to more complete combustion, thus resulting in a great reduction in the POP emissions. Not only did the self-provided oxygen of butanol promote complete oxidation but also the water content in butanol diesel blends could cause a microexplosion mechanism, which provided a better turbulence and well-mixed environment for complete combustion.

Fine particle, ozone exposure, and asthma/wheezing: effect modification by glutathione S-transferase P1 polymorphisms.

BACKGROUND: There are limited studies on the role of interaction between exposure to ambient air pollution and glutathione-S-transferase (GST) P1 on the risk of asthma/wheezing among children, which provided suggestive, but inconclusive results. METHODS: To assess the joint effect of air pollutants and GSTP1 on asthma/wheezing, we conducted a nationwide cross-sectional study of 3,825 children in Taiwan Children Health Study. The studied determinants were three GSTP1 Ile105Val (rs 1695) genotypes (Ile-Ile; Ile-Val and Val-Val) and expoure to ambient air pollutants. We used routine air-pollution monitoring data for ozone (O(3)) and particles with an aerodynamic diameter of 2.5 µm or less (PM(2.5)). The effect estimates were presented as odds ratios (ORs) per interquartile changes for PM(2.5) and O(3). FINDINGS: In a two-stage hierarchical model adjusting for confounding, the risk of asthma was negatively associated with PM(2.5) (adjusted odds ratio (OR) 0.60; 95% confidence interval (CI) 0.45, 0.82) and O(3) (OR 0.74; 95% CI 0.60, 0.90) among Ile105 homozygotes, but positively associated with PM(2.5) (OR 1.52; 95% CI 1.01, 2.27) and O(3) (OR 1.19; 95% CI 0.91, 1.57) among those with at least one val105 allele (interaction p value = 0.001 and 0.03, respectively). A similar tendency of effect modification between PM(2.5) and O(3) and GSTP1 on wheezing was found. CONCLUSION: Children who carried Ile105 variant allele and exposed to PM(2.5) and O(3) may be less likely to occurrence of asthma/wheezing.

A pilot study for determining the optimal operation condition for simultaneously controlling the emissions of PCDD/Fs and PAHs from the iron ore sintering process.

In this study, the cost-benefit analysis technique was developed and incorporated into the Taguchi experimental design to determine the optimal operation combination for the purpose of providing a technique solution for controlling both emissions of PCDD/Fs and PAHs, and increasing both the sinter productivity (SP) and sinter strength (SS) simultaneously. Four operating parameters, including the water content, suction pressure, bed height, and type of hearth layer, were selected and all experimental campaigns were conducted on a pilot-scale sinter pot to simulate various sintering operating conditions of a real-scale sinter plant. The resultant optimal combination could reduce the total carcinogenic emissions arising from both emissions of PCDD/Fs and PAHs by 49.8%, and increase the sinter benefit associated with the increase in both SP and SS by 10.1%, as in comparison with the operation condition currently used in the real plant. The ANOVA results indicate that the suction pressure was the most dominant parameter in determining the optimal operation combination. The above result was theoretically plausible since the higher suction pressure provided more oxygen contents leading to the decrease in both PCDD/F and PAH emissions. But it should be noted that the results obtained from the present study were based on pilot scale experiments, conducting confirmation tests in a real scale plant are still necessary in the future.

Spatiotemporal variability of submicrometer particle number size distributions in an air quality management district.

First measurements of ambient 10-1000 nm particle number concentrations (N(TOT)) and size distributions were made at an urban, coastal, mountain and downwind site within the Central Taiwan Air Quality Management District during a cold and a warm period. The primary objectives were to characterize the spatial and temporal variability of the size-fractionated submicrometer particles and their relationships with copollutants and meteorological parameters. The results show that the ultrafine particles (<100 nm) are the major contributor to the N(TOT). The mean N(TOT) was highest at the urban site, whereas lower and comparable at the three other sites. Although the mean N(TOT) at each site showed insignificant differences between study periods, their diurnal patterns and size distribution modal characteristics were modestly to substantially different between study sites. Correlation analyses of time-resolved collocated aerosol, copollutants and meteorological data suggest that the observed variability is largely attributable to the local traffic and to a lesser extent photochemistry and SO(2) possibly from combustion sources or regional transport. Despite sharing a common traffic source, the ultrafine particles were poorly correlated with the accumulation particles (100-1000 nm), between which the latter showed strong positive correlation with the PM(2.5) and PM(10). Overall, the N(TOT) and size distributions show modest spatial heterogeneity and strong diurnal variability. In addition, the ultrafine particles have variable sources or meteorology-dependent formation processes within the study area. The results imply that single-site measurements of PM(2.5), PM(10) or N(TOT) alone and without discriminating particle sizes would be inadequate for exposure and impact assessment of submicrometer particle numbers in a region of diverse environments.

Noise frequency components and the prevalence of hypertension in workers.

Epidemiological studies have demonstrated a relationship between noise exposure and hypertension, but the association between hypertension and noise frequency components remains unclear. This cross-sectional study investigated the association between noise exposure at different frequencies and the prevalence of hypertension in 188 screw-manufacturing workers. Participants were divided into one high-noise-exposure group (≥80 A-weighted decibel, [dBA]; n=68) and two reference groups, including 68 low-noise-exposure workers (75.8±3.2 dBA) and 52 office workers (61.5±0.5dBA). Personal noise exposure and environmental octave-band analyses were performed at work. Multiple logistic regression models were used to estimate odds ratios (ORs) for hypertension between different noise-exposure categories after adjustment for potential confounders. Male workers exposed to noise levels at high frequencies of 2000, 4000 or 8000Hz had a higher but non-significant risk of hypertension. Those exposed to ≥80dBA for 2-4years, 4-6years and more than 6years had a 4.43-fold (95% CI=1.21-16.15), 1.21-fold (95% CI=0.35-4.21) and 0.95-fold (95% CI=0.16-5.60) risk of hypertension, respectively, compared with reference workers. A significant association was only observed in male workers exposed to ≥70dBA at 4000Hz for 2-4years (adjusted OR=4.22; 95% CI=1.15-15.49) and was not found at other frequencies for any periods. These findings suggest that occupational noise exposure above 80dBA for specific periods may be associated with hypertension, and noise frequency at 4000Hz may have the greatest effect on hypertension.

Effects of biodiesel, engine load and diesel particulate filter on nonvolatile particle number size distributions in heavy-duty diesel engine exhaust.

Diesel engine exhaust contains large numbers of submicrometer particles that degrade air quality and human health. This study examines the number emission characteristics of 10-1000 nm nonvolatile particles from a heavy-duty diesel engine, operating with various waste cooking oil biodiesel blends (B2, B10 and B20), engine loads (0%, 25%, 50% and 75%) and a diesel oxidation catalyst plus diesel particulate filter (DOC+DPF) under steady modes. For a given load, the total particle number concentrations (N(TOT)) decrease slightly, while the mode diameters show negligible changes with increasing biodiesel blends. For a given biodiesel blend, both the N(TOT) and mode diameters increase modestly with increasing load of above 25%. The N(TOT) at idle are highest and their size distributions are strongly affected by condensation and possible nucleation of semivolatile materials. Nonvolatile cores of diameters less than 16 nm are only observed at idle mode. The DOC+DPF shows remarkable filtration efficiency for both the core and soot particles, irrespective of the biodiesel blend and engine load under study. The N(TOT) post the DOC+DPF are comparable to typical ambient levels of ≈ 10(4)cm(-3). This implies that, without concurrent reductions of semivolatile materials, the formation of semivolatile nucleation mode particles post the after treatment is highly favored.