Scielo RSS <![CDATA[Clean Air Journal]]> vol. 31 num. 2 lang. es <![CDATA[SciELO Logo]]> <![CDATA[<b>Modeling tropospheric ozone and particulate matter in Tunis, Tunisia using generalized additive model</b>]]> The main purpose of this paper is to analyze the sensitivity of tropospheric ozone and particulate matter concentrations to changes in local scale meteorology with the aid of meteorological variables (wind speed, wind direction, relative humidity, solar radiation and temperature) and intensity of traffic using hourly concentration of NO X, which are measured in three different locations in Tunis, (i.e. Gazela, Mannouba and Bab Aliwa). In order to quantify the impact of meteorological conditions and precursor concentrations on air pollution, a general model was developed where the logarithm of the hourly concentrations of O3 and PM10 were modeled as a sum of non-linear functions using the framework of Generalized Additive Models (GAMs). Partial effects of each predictor are presented. We obtain a good fit with R² = 85% for the response variable O3 at Bab Aliwa station. Results show the aggregate impact of meteorological variables in the models explained 29% of the variance in PM10 and 41% in O3. This indicates that local meteorological condition is an active driver of air quality in Tunis. The time variables (hour of the day, day of the week and month) also have an effect. This is especially true for the time variable "month" that contributes significantly to the description of the study area. <![CDATA[<b>Quantifying potential particulate matter intake dose in a low-income community in South Africa</b>]]> Understanding how exposure to particulate matter impacts human health is complex. Personal exposure is a function of the pollution concentrations measured at any given place and time. The health impacts of this exposure are, in part, determined by how high pollutant concentrations are and how much pollution can potentially enter the body. This study considered data gathered in the winter of 2013 in a low-income community on the Mpumalanga Highveld, South Africa, which is a geographical area known for its high air pollution levels. Data collected by GPS monitors worn by individuals in the community were used to understand in which microenvironments people spend most of their time. Participants spent time in five main micro-environments: (highest rank first) inside a house, directly outside a house, on a dirt road, on a tar road, and on an open field. Eight days' worth of ambient, indoor and personal particulate matter measurements were paired with individual GPS positioning data for one study participant. We identified pollutant concentrations where the person spent time and how much particulate matter the person potentially inhaled. Highest concentrations were measured inside the dwelling and directly outside the dwelling of the individual. When comparing directly (ranging from 0.02 -0.76 mg) - and indirectly (0.02 - 0.34 mg) derived time-weighted potential intake doses, directly derived intake doses were higher and more likely to represent how much particulate matter was potentially inhaled by the participant. This study suggests that people living in communities on the Mpumalanga Highveld are exposed to unacceptably high air pollution levels in places in which they spend most of their time. Direct exposure and intake dose assessments are an important element of environmental health studies to supplement data collected by stationary monitors in order to better understand exactly what people are breathing. <![CDATA[<b>Does apparent temperature modify the effects of air pollution on respiratory disease hospital admissions in an industrial area of South Africa?</b>]]> BACKGROUND: Temperature and air pollution are often treated as separate risk factors and very few studies investigated effect modification by temperature on air pollution, and the impact of this interaction on human health in Africa. This study therefore investigated the modifying effects of temperature on the association between air pollution and respiratory disease (RD) hospital admissions in South Africa. METHODS: RD admission data (ICD10 J00-J99) were obtained from two hospitals located in Secunda, South Africa beween 1 January 2011 to 31 October 2016. Ambient NO2, SO2, PM, PM25, temperature and relative humidity data were obtained from the South African Weather Services. A case-crossover epidemiological study design was applied and lag0-1 was used. Models were adjusted for public holidays and apparent temperature (Tapp). Days were classified as warm (Tapp&gt;75th percentile), cold (Tapp<25th percentile) and normal (Tapp 25th-75th percentile. RESULTS: Of the 14 568 RD admissions, approximately an equal number of females and males were admitted. The average daily NO2, SO2, PM25 and PM10 levels were 12.4 μg/m³, 8.5 μg/m³, 32.3 μg/m³ and 68.6 μg/m³, respectively. Overall, a 10 μg/m³ increase in SO2 on warm days was associated with an increase in RD hospital admissions: 8.5% (95% Conf. Int: 0.4%, 17.2%) and 8.4% (95% Conf. Int: 0.3%, 17.1%) after adjustment for PM25 and PM, respectively. However, increasing PM25 or PM10 levels was associated with an increase in RD hospital admissions on normal days,after adjusting for SO2. On cold days there were significant associations between the SO2 and RD admissions among the 0-14 year age group, after adjusting for either PM25 (6.5%; 95% Conf.Int: 0.9%, 12.4%) or PM10 (5.5%; 95% Conf.Int: 0.3%, 11.1%. CONCLUSIONS: These results indicate that the risk of RD hospital admission due to ambient air pollution exposure is different on cold, normal and warm days in Secunda.