Effects of ammonia from livestock farming on lichen photosynthesis

This study investigated if atmospheric ammonia (NH₃) pollution around a sheep farm influences the photosynthetic performance of the lichens Evernia prunastri and Pseudevernia furfuracea. Thalli of both species were transplanted for up to 30 days in a semi-arid region (Crete, Greece), at sites with concentrations of atmospheric ammonia of ca. 60 μg/m³ (at a sheep farm), ca. 15 μg/m³ (60 m from the sheep farm) and ca. 2 μg/m³ (a remote area 5 km away). Lichen photosynthesis was analysed by the chlorophyll a fluorescence emission to identify targets of ammonia pollution. The results indicated that the photosystem II of the two lichens exposed to NH₃ is susceptible to this pollutant in the gas-phase. The parameter PI_ABS, a global index of photosynthetic performance that combines in a single expression the three functional steps of the photosynthetic activity (light absorption, excitation energy trapping, and conversion of excitation energy to electron transport) was much more sensitive to NH₃ than the F_V/F_M ratio, one of the most commonly used stress indicators.     

Determination of direct and fugitive PM emissions in a Mediterranean harbour by means of classic and novel tracer methods

Remodelling works are frequent in harbour areas, given that they must adapt to rapidly changing market requirements. Depending on their nature (construction, demolition, etc.), these works may be carried out during long periods of time and thus exert a significant impact on the air quality at the harbours and their surroundings. The air quality at the Valencia harbour was studied during an enlargement project. Four sampling stations aimed to cover the major dust-emitting activities in the harbour. In addition, a sampling campaign was carried out to collect dust materials at their emission sources (e.g., loading and unloading of clinker and petroleum coke, as well as the enlargement works). Differences obtained between PM levels at the monitoring sites were correlated with the distance between sampling stations and enlargement works and/or harbour operations, as well as with the preferential wind direction. In all cases, the days with the highest PM_10 levels were linked to wind directions coinciding with the location of the enlargement works or the clinker and petroleum coke stocks. Classic source apportionment methodologies (PCA and CMB) were applied to the data, but their interpretation was complex due to the similar chemical signatures of PM originating from direct and fugitive emissions from stocked materials (e.g., clinker), and the enlargement works. To overcome this difficulty, a novel non-statistical approach was used to obtain quantitative estimations of the contributions from sources (petroleum coke and clinker), based on the correlation between specific PM components (e.g., carbonaceous species) and source tracers (e.g., V). Finally, a qualitative test using phenolphthalein was devised to identify the presence of clinker on the filters, which provided positive results. This novel tracer approach is thus recommended for harbour authorities.     

Assessment of present and future risk to Italian forests and human health: Modelling and mapping

A review of ozone pollution in Italy shows levels largely above the thresholds established by EU regulation for vegetation and human health protection. The Italian air quality monitoring network appears quantitatively inadequate to cover all the territorial surface, because of scarcity and unequal distribution of monitoring sites. By applying the integrated assessment model RAINS-Italy to the year 2000, the whole of Italy exceeds the AOT40 critical level for forest, while Northern and central areas show strong potential of O₃ impact on human health with ∼11% of territory >10 O₃-induced premature deaths. Two scenarios for the year 2020, the Current Legislation and the Maximum Technical Feasible Reduction, show a reduction of AOT40Forest by 29% and 44%, SOMO35 by 31% and 47%, and O₃-induced premature deaths by 32% and 48%, compared to 2000. RAINS-Italy can be used to improve the map quality and cover areas not reached by the national monitoring network.     

Secondary arsenic minerals in the environment: A review

Information on arsenic (As) speciation in solid materials is critical for many environmental studies concerned with As stability and/or mobility in natural As-impacted soils and mining or industrial sites contaminated by As. The investigation of these systems has provided evidence for a number of secondary As minerals that have often played a significant role in As mobility in the solid phase–water system. This paper presents a list of environmentally important secondary As minerals in contaminated soil and waste systems, summarizes the information about their origin, occurrence, environmental stability and thermodynamics, and proposes several important avenues for further investigation.     

建设项目竣工验收现场平行样控制指标研究

依据建设项目竣工环境保护验收中污水监测的要求,通过积累大量验收监测质量检查的实验数据,运用数理统计的方法,以化学需氧量和氨氮两个项目为例,建立了质控数据的评价方法,并确定了现场平行样偏差指标的限値。     

Statistical Analysis of Air Pollutants and Meteorological Parameters in Afyon, Turkey

In this study, the relation between sulfur dioxide (SO₂) and particulate matter (PM) concentrations periodically measured in the city of Afyon’s atmosphere with meteorological factors such as precipitation, humidity, temperature, wind velocity, and inversion were investigated. The mean values of SO₂ and PM concentrations measured during the winter months of October–March 1990–1999 were correlated with the meteorological parameters of the same period. Simple and multiple linear regression analysis were utilized to evaluate the contribution of meteorological variables. The statistical results show that the pollutants, i.e., SO₂ and PM are dependent upon humidity, temperature, and inversion at the 1% significance level; while the dependence of both pollutants with temperature is negative when those of humidity and inversion are positive. Two models in which temperature and inversion are dependent with multiple variables are recommended for predicting the contribution of meteorological parameters on SO₂ and PM. In addition, the relationship between humidity, temperature, and inversion with pollutants is also determined using nonlinear (polynomial) models.     

Solar driven nitrous acid formation on building material surfaces containing titanium dioxide: A concern for air quality in urban areas?

The photoenhanced uptake of nitrogen dioxide (NO₂) to the surface of commercially available self-cleaning window glass has been studied under controlled laboratory conditions. This material is one of an array of modern building products which incorporate titanium dioxide (TiO₂) nanoparticles and are finding increasing use in populated urban areas. Amongst the principal drivers for the use of these materials is that they are thought to facilitate the irreversible removal of pollutants such as NO₂ and organic molecules from the atmosphere and thus act to remediate air quality. While it appears that TiO₂ materials do indeed remove organic molecules from built environments, in this study we show that the photoenhanced uptake of NO₂ to one example material, self-cleaning window glass, is in fact accompanied by the substantial formation (50–70%) of gaseous nitrous acid (HONO). This finding has direct and serious implications for the use of these materials in urban areas. Not only is HONO a harmful respiratory irritant, it is also readily photolysed by solar radiation leading to the formation of hydroxyl radicals (OH) together with the re-release of NO_x as NO. The net effect of subsequent OH initiated chemistry can then be the further degradation of air quality through the formation of secondary pollutants such as ozone and VOC oxidation products. In summary, we suggest that a scientifically conceived technical strategy for air quality remediation based on this technology, while widely perceived as universally beneficial, could in fact have effects precisely opposite to those intended.     

Characterization of distribution of pesticide residues in crop units

The characteristic features of distribution of pesticide residues in crop units and single sample increments were studied based on more than 19,000 residue concentrations measured in root vegetables, leafy vegetables, small-, medium- and large-size fruits representing 20 different crops and 46 pesticides. Log-normal, gamma and Weibull distributions were found to provide the best fit for the relative frequency distributions of individual residue data sets. The overall best fit was provided by lognormal distribution. The relative standard deviation of residues (CV) in various crops ranged from 15–170%. The 100–120 residue values being in one data set was too small to identify potential effects of various factors such as the chemical and physical properties of pesticides and the nature of crops. Therefore, the average of CV values, obtained from individual data sets, were calculated and considered to be the best estimate for the likely variability of unit crop residues for treated field (CV = 0.8) and market samples (CV = 1.1), respectively. The larger variation of residues in market samples was attributed to the potential mixing of lots and varying proportion of non-detects. The expectable average variability of residues in composited samples can be calculated from the typical values taking into account the sample size.     

Ambient nitrogen oxides exposure and early childhood respiratory illnesses

Acute respiratory infections are common in children below 5 years and recent studies suggest a possible link with air pollution. In this study, we investigated the association between ambient nitrogen oxides (NO_x) and bronchitis or upper airway inflammation.This longitudinal study was conducted in Teplice and Prachatice districts, Czech Republic. Children were followed from birth to 4.5 years of age. Data were compiled from medical records at delivery and at follow up, and from self-administered questionnaires from the same two time points. Air pollution monitoring data were used to estimate exposure over five different averaging periods ranging from three to 45 days prior to an episode. To quantify the association between exposure and outcome, while accounting for repeated measure correlation we conducted logistic regression analysis using generalized estimating equations.During the first 2 years of life, the adjusted rate ratio for bronchitis associated with interquartile increase in the 30-day average NO_x was 1.31 [95% confidence interval (CI): 1.07, 1.61] and for two to 4.5 year olds, it was 1.23 (95% CI: 1.01, 1.49). The 14-day exposure also had stable association across both age groups: below 2 years it was 1.25 (95% CI: 1.06, 1.47) and for two to 4.5 years it was 1.21 (95% CI: 1.06, 1.39). The association between bronchitis and NO_x increased with child's age in the under 2 years group, which is a relatively novel finding.The results demonstrate an association between NO_x and respiratory infections that are sufficiently severe to come to medical attention. The evidence, if causal, can be of public health concern because acute respiratory illnesses are common in preschool children.     

Neural network forecasting of air pollutants hourly concentrations using optimised temporal averages of meteorological variables and pollutant concentrations

The new method for the forecasting hourly concentrations of air pollutants is presented in the paper. The method was developed for a site in urban residential area in city of Zagreb, Croatia, for four air pollutants (NO₂, O₃, CO and PM₁₀). Meteorological variables and concentrations of the respective pollutant were taken as predictors. A novel approach, based on families of univariate regression models, was employed in selecting the averaging intervals for input variables. For each variable and each averaging period between 1 and 97 h, a separate model was built. By inspecting values of the coefficient of correlation between measured and modelled concentrations, optimal averaging periods for each variable were selected. A new dataset for building the forecasting model was then calculated as temporal moving averages (running means) of former variables. A multi-layer perceptron type of neural networks is used as the forecasting model. Index of agreement, calculated for the entire dataset including the data for model building, ranged from 0.91 to 0.97 for the respective pollutants. As suggested by the analysis of the relative importance of the input variables, different agreements for different pollutants are likely due to different sources and production mechanisms of investigated pollutants. A comparison of the new method with more traditional method, which takes hourly averages of the forecast hour as input variables, showed similar or better performance. The model was developed for the purpose of public-health-oriented air quality forecasting, aiming to use a numerical weather forecast model for the prediction of the part of input data yet unknown at the forecasting time. It is to expect that longer term averages used as inputs in the proposed method will contribute to smaller input errors and the greater accuracy of the model.