Comparing meta-analysis and ecological-longitudinal analysis in time-series studies: a case study of the effects of air pollution on mortality in three Spanish cities

The objective of this paper is to introduce a diVerent approach, called the ecological-longitudinal, to carrying out pooled analysis in time series ecological studies. Because it gives a larger number of data points and, hence, increases the statistical power of the analysis, this approach, unlike conventional ones, allows the complementation of aspects such as accommodation of random effect models, of lags, of interaction between pollutants and between pollutants and meteorological variables, that are hardly implemented in conventional approaches. Design—The approach is illustrated by providing quantitative estimates of the short-termeVects of air pollution on mortality in three Spanish cities, Barcelona,Valencia and Vigo, for the period 1992–1994. Because the dependent variable was a count, a Poisson generalised linear model was first specified. Several modelling issues are worth mentioning. Firstly, because the relations between mortality and explanatory variables were nonlinear, cubic splines were used for covariate control, leading to a generalised additive model, GAM. Secondly, the effects of the predictors on the response were allowed to occur with some lag. Thirdly, the residual autocorrelation, because of imperfect control, was controlled for by means of an autoregressive Poisson GAM. Finally, the longitudinal design demanded the consideration of the existence of individual heterogeneity, requiring the consideration of mixed models. Main results—The estimates of the relative risks obtained from the individual analyses varied across cities, particularly those associated with sulphur dioxide. The highest relative risks corresponded to black smoke in Valencia. These estimates were higher than those obtained from the ecological-longitudinal analysis. Relative risks estimated from this latter analysis were practically identical across cities, 1.00638 (95% confidence intervals 1.0002, 1.0011) for a black smoke increase of 10 μg/m3 and 1.00415 (95% CI 1.0001, 1.0007) for a increase of 10 μg/m3 of sulphur dioxide. Because the statistical power is higher than in the individual analysis more interactions were statistically significant,especially those among air pollutants and meteorological variables. Conclusions—Air pollutant levels were related to mortality in the three cities of the study, Barcelona, Valencia and Vigo. These results were consistent with similar studies in other cities, with other multicentric studies and coherent with both, previous individual, for each city, and multicentric studies for all three cities

Wheat archive links long-term population dynamics of pathogens to air pollution

We used the PCR to study the presence of two plant pathogens in archived wheat samples from a long-term experiment started in 1843. The data were used to construct a unique 160-yr time-series of the abundance of Phaeosphaeria nodorum and Mycosphaerella graminicola, two important pathogens of wheat. During the period since 1970, the relative abundance of DNA of these two pathogens in the samples has reflected the relative importance of the two wheat diseases they cause in U.K. disease surveys. Unexpectedly, changes in the ratio of the pathogens over the 160-yr period were very strongly correlated with changes in atmospheric pollution, as measured by SO2 emissions. This finding suggests that long-term, economically important, changes in pathogen populations can be influenced by anthropogenically induced environmental changes.

Work performance, productivity and indoor air

Temperature, relative humidity, and air quality all affect the sensory system via thermo receptors in the skin and the olfactory system. Air quality is mainly defined by the contaminants in the air. However, the most persistent memory of any space is often its odor. Strong, emotional, and past experiences are awakened by the olfactory sense. Odors can also influence cognitive processes that affect creative task performance, as well as personal memories and moods. Besides nitrogen and oxygen, the air contains particles and many chemicals that affect the efficiency of the oxygenation process in the blood, and ultimately the air breathed affects thinking and concentration. It is important to show clients the value of spending more capital on high-quality buildings that promote good ventilation. The process of achieving indoor-air quality is a continual one throughout the design, construction, commissioning, and facilities management processes. This paper reviews the evidence.

Effect of internal partitioning on indoor air quality of rooms with mixing ventilation - basic study

The internal partitioning, which is frequently introduced in open-space planning due to its flexibility, was tested to study its effects on the room air quality as well as ventilation performance. For the study, physical tests using a small model room and numerical modeling using CFD computation were utilized to evaluate different test conditions employing mixing ventilation from the ceiling. The partition parameters, such as its location, height, and the gap underneath, as well as contaminant source location were tested under isothermal conditions. This paper summarizes the results from the study.

Different splitting techniques with application to air pollution models

Splitting techniques are commonly used when large-scale models, which appear in different fields of science and engineering, are treated numerically. Four types of splitting procedures are defined and discussed. The problem of the choice of a splitting procedure is investigated. Several numerical tests, by which the influence of the splitting errors on the accuracy of the results is studied, are given. It is shown that the splitting errors decrease linearly when (1) the splitting procedure is of first order and (2) the splitting errors are dominant. Three examples for splitting procedures used in all large-scale air pollution models are presented. Numerical results obtained by a particular air pollution model, Unified Danish Eulerian Model (UNI-DEM), are given and analysed.