Epidemiologic studies on short-term effects of low levels of major ambient air pollution components.

Since the development of the World Health Organization (WHO) Air Quality Guidelines for Europe, a large number of epidemiologic studies have been published documenting effects of major air pollutants on health at concentrations below existing guidelines and standards. In this review, recent studies are discussed that permit some evaluation of short-term health effects observed at exposure levels lower than the current WHO Guidelines or U.S. Environmental Protection Agency (U.S. EPA) standards. Some studies have been conducted at concentration levels that never exceeded existing guidelines or standards. Other studies have been conducted at exposure levels sometimes exceeding current guidelines or standards. The published analyses of several of these studies permit evaluation of low-level health effects either because analyses were restricted to levels not exceeding the guidelines or graphic analyses were reported suggesting effects at these low levels. For ambient ozone, effects on lung function of subjects exercising outdoors have now been documented at 1-hr maximum levels not exceeding 120 micrograms/m3, i.e., half the current U.S. EPA standard. One study even suggests that such effects occur at levels below 100 micrograms/m3. Several studies are now available documenting effects of particulate air pollution on health in the virtual absence of SO2. Effects on mortality and hospital admissions for asthma have been documented at levels not exceeding 100 micrograms/m3, expressed as 24-hr average inhalable particles PM10 concentration. Effects on lung function, acute respiratory symptoms, and medication use have been found at 24-hr average PM10 levels not exceeding 115 micrograms/m3. When the WHO Air Quality Guidelines and the U.S. EPA standard for PM10 were developed, there were no studies available on health effects of PM10. In this review, we include nine studies documenting health effects of measured PM10 at low levels of exposure, indicating that there is now an entirely new epidemiologic database that can be evaluated in the process of revising current guidelines and standards. The low levels of exposure at which effects on health were seen underscore the urgent need for such reevaluations

The relationship between environmental lead and blood lead in children : a study in environmental epidemiology

This study deals with the relationship between environmental lead and blood lead in children.Chapter 1 provides a summary of the environmental health aspects of lead. The occurrence of lead in the environment and in man is described; children are discussed as a population at risk for undue lead absorption, and the exposure-response system is briefly outlined.Chapter 2 discusses a number of methodological issues in studies on the relationship between environmental lead and blood lead in children. Lead is present in various environmental media like air, soil and dust. From all these media, lead intake by children may occur, by inhalation or ingestion. The inhalation rate per kg body weight is larger in children than in adults, due to a higher metabolism. The ingestion of dust and dirt cannot be easily quantified; at present, measurement of the lead concentration in dust and dirt usually serves as a surrogate. The concentration of lead in blood has been the major dependent variable in studies on the relationship between environmental lead exposure and internal lead exposure. The concentration of lead in blood does not only depend on intake but also on the fractional absorption of lead from the gut, and on distribution and excretion patterns within the body. All of these vary with age. Nutritional factors are important as well, for example dietary calcium, iron, phosphorus and fat. Lead is not only present in the general environment but also in food and drinking water, both of which may act as predominant sources of lead intake. Lead in food originates in part from environmental pollution, and it is still debated how large this part actually is. Lead in drinking water usually originates from pipes or storage facilities. In the United States especially, lead from crumbling paint is an important source for children; paint lead does not seem to be of general importance in The Netherlands, however.The relationship between total lead intake and the concentration of lead in blood is usually given as a curvilinear downward function. The implication of this is that at low levels of exposure, a given increase of intake is expected to result in a stronger increase in blood lead concentrations than at high levels of exposure. In some studies, it has been customary to adjust relationships between air lead and blood lead for lead in other media. As lead in the air and lead in other media like soil and dust often originate from the same source or sources, such a procedure may under-estimate the impact of environmental lead on children's blood lead.It is difficult to measure the intake of lead from the environment by children exactly. Instead, the concentration of lead in one or more environmental media is usually measured as an index of exposure.Apart from being only approximations of actual lead intake from the environment, these concentrations also tend to have large temporal and spatial variations. A decomposition of total variation into within-subjects and between- subjects variation is a weans to estimate the reliability of exposure indicators. If the within-subjects variation of exposure indicators is large compared to the between- subjects variation, the impact of environmental lead exposure on blood lead will usually be underestimated in a regression analysis.Chapter 3 reviews a number of studies from which estimates of relationships between environmental lead and children's blood lead can be obtained. Aggregate relationships are emphasized, i.e. it is not attempted to estimate the separate contributions of inhalation, ingestion of soil, dust etc. as the available data usually do not permit such an analysis. Aggregate relationships are relationships in which different indicators of lead exposure are thought to represent all environmental exposure. When the concentration of lead in air is taken as an indicator, a blood lead/air lead slope of about 3-5 μg/100 ml per μg/m 3 is obtained. When the concentration of lead in soil, street dust or house dust is taken as an indicator, most blood lead/soil (dust) lead slopes are in the order of 5.0 - 10.0 μg/100 ml per g/kg.Although the ranges of the different types of estimates are wide, the review suggests that for children, lead intake from the environment constitutes a major part of total lead intake in quite a number of situations.Chapter 4 is a description of our study on environmental lead and blood lead in children living in Rotterdam, The Hague and Zoetermeer which was performed in 1981.Blood lead concentrations in children were different between city centers and suburbs. After adjustment for a number of confounders, more than half of the difference remained. Most probably, this was caused by differences in environmental lead pollution as most indicators of lead exposure were clearly different between city centers and suburbs. In a multiple regression analysis, most exposure indicators were significantly associated with the concentration of lead in blood, after adjustment for a number of confounders. Further analysis of the origins of lead in the environment suggested that in the area under investigation, vehicular traffic was the main source.When our study results were compared with those of others, the estimated impact of environmental lead on children's blood lead was somewhat higher than in most other studies, but the difference was not great, considering the wide range in estimates which was reported in chapter 3. Theoretically, the differences can be explained by the low level of exposure which was studied, and by the use of repeated exposure measurements. As indicated in chapter 2, a given exposure difference is expected to result in a larger blood lead difference at low overall levels of PbB than at a high overall level of PbB. Also, repetition of exposure measurements leads to a more precise estimate of exposure, and can theoretically be expected to result in a higher exposure impact estimate than when exposure is only measured once, as was the case in most studies reviewed in chapter 3

More die of heartbreak : en andere misverstanden over milieu en gezondheid

Rede Landbouwuniversiteit Wageningen, 6 mei 199

The effect of industry-related air pollution on lung function and respiratory symptoms in school children

Background: Heavy industry emits many potentially hazardous pollutants into the air which can affect health. However, the effects of air pollution from heavy industry on lung function and respiratory symptoms have been investigated scarcely. Our aim was to investigate the associations of long-term air pollution from heavy industry with lung function and respiratory symptoms in school children. Methods: A cross-sectional lung function study was conducted among school children (7-13 years) in the vicinity of an area with heavy industry. Lung function measurements were conducted during school hours. Parents of the children were asked to complete a questionnaire about the health of their children. A dispersion model was used to characterize the additional individual-level exposures to air pollutants from the industry in the area. Associations between PM2.5 and NOX exposure with lung function and presence of respiratory symptoms were investigated by linear and/or logistic regression analysis. Results: Participation in the lung function measurements and questionnaires was 84% (665/787) and 77% (603/787), respectively. The range of the elevated PM2.5 and NOX five years average concentrations (2008-2012) due to heavy industry were 0.04-1.59 μg/m3 and 0.74-11.33 μg/m3 respectively. After adjustment for confounders higher exposure to PM2.5 and NOX (per interquartile range of 0.56 and 7.43 μg/m3 respectively) was associated with lower percent predicted peak expiratory flow (PEF) (B -2.80%, 95%CI -5.05% to - 0.55% and B -3.67%, 95%CI -6.93% to - 0.42% respectively). Higher exposure to NOX (per interquartile range of 7.43 μg/m3) was also associated with lower percent forced vital capacity (FVC) and percent predicted forced expiration volume in 1 s (FEV1) (B -2.30, 95% CI -4.55 to - 0.05 and B -2.73, 95%CI -5.21 to - 0.25 respectively). No significant associations were found between the additional exposure to PM2.5 or NOX and respiratory symptoms except for PM2.5 and dry cough (OR 1.40, 95%CI 1.00 to 1.94). Conclusion: Exposure to PM2.5 and NOX from industry was associated with decreased lung function. Exposure to PM2.5 was also associated with parents' reports of dry cough among their children

Production of ceramics from coal fly ash

Dense ceramics are produced from fly ash from REK Bitola, Republic of Macedonia. Four types of fly ash from electro filters and one from the collected zone with particles < 0.063 mm were the subject of this research. Consolidation was achieved by pressing (P= 133 MPa) and sintering (950, 1000, 1050 and 11000C and heating rates of 3 and 100/min). Densification was realized by liquid phase sintering and solid state reaction where diopside [Ca(Mg,Al)(Si,Al)2O6] was formed. Ceramics with optimal properties (porosity 2.96±0.5%, bending strength - 47.01±2 MPa, compressive strength - 170 ±5 MPa) was produced at 1100ºC using the heating rate of 10ºC/min

Thresholds: observations on motion capture.

This paper theoretically situates research that explores motion capture data visualization using customized software tools such as MxCap.01. The value of software like MxCap.01 lies in its visualization capabilities including the ability to scale the re-presentation of the force, direction and intensity of movement but also do so within a temporal and emotive structuring

Robustness of intra urban land-use regression models for ultrafine particles and black carbon based on mobile monitoring.

Land-use regression (LUR) models for ultrafine particles (UFP) and Black Carbon (BC) in urban areas have been developed using short-term stationary monitoring or mobile platforms in order to capture the high variability of these pollutants. However, little is known about the comparability of predictions of mobile and short-term stationary models and especially the validity of these models for assessing residential exposures and the robustness of model predictions developed in different campaigns. We used an electric car to collect mobile measurements (n = 5236 unique road segments) and short-term stationary measurements (3 × 30min, n = 240) of UFP and BC in three Dutch cities (Amsterdam, Utrecht, Maastricht) in 2014-2015. Predictions of LUR models based on mobile measurements were compared to (i) measured concentrations at the short-term stationary sites, (ii) LUR model predictions based on short-term stationary measurements at 1500 random addresses in the three cities, (iii) externally obtained home outdoor measurements (3 × 24h samples; n = 42) and (iv) predictions of a LUR model developed based upon a 2013 mobile campaign in two cities (Amsterdam, Rotterdam). Despite the poor model R(2) of 15%, the ability of mobile UFP models to predict measurements with longer averaging time increased substantially from 36% for short-term stationary measurements to 57% for home outdoor measurements. In contrast, the mobile BC model only predicted 14% of the variation in the short-term stationary sites and also 14% of the home outdoor sites. Models based upon mobile and short-term stationary monitoring provided fairly high correlated predictions of UFP concentrations at 1500 randomly selected addresses in the three Dutch cities (R(2) = 0.64). We found higher UFP predictions (of about 30%) based on mobile models opposed to short-term model predictions and home outdoor measurements with no clear geospatial patterns. The mobile model for UFP was stable over different settings as the model predicted concentration levels highly correlated to predictions made by a previously developed LUR model with another spatial extent and in a different year at the 1500 random addresses (R(2) = 0.80). In conclusion, mobile monitoring provided robust LUR models for UFP, valid to use in epidemiological studies