Assesment of PM10 pollution episodes in a ceramic cluster (NE Spain): proposal of a new quality index for PM10, As, Cd, Ni and Pb

Air pollution relevance analysis in the bay of Algeciras (Spain)

The aim of this work is to accomplish an in-depth analysis of the air pollution in the two main cities of the Bay of Algeciras (Spain). A large database of air pollutant concentrations and weather measurements were collected using a monitoring network installed throughout the region from the period of 2010-2015. The concentration parameters contain nitrogen dioxide (NO2), sulphur dioxide (SO2) and particulate matter (PM10). The analysis was developed in two monitoring stations (Algeciras and La Línea). The higher average concentration values were obtained in Algeciras for NO2 (28.850 µg/m3) and SO2 (11.966 µg/m3), and in La Línea for PM10 (30.745 µg/m3). The analysis shows patterns that coincide with human activity. One of the goals of this work is to develop a useful virtual sensor capable of achieving a more robust monitoring network, which can be used, for instance, in the case of missing data. By means of trends analysis, groups of equivalent stations were determined, implying that the values of one station could be substituted for those in the equivalent station in case of failure (e.g., SO2 weekly trends in Algeciras and Los Barrios show equivalence). On the other hand, a calculation of relative risks was developed showing that relative humidity, wind speed and wind direction produce an increase in the risk of higher pollutant concentrations. Besides, obtained results showed that wind speed and wind direction are the most important variables in the distribution of particles. The results obtained may allow administrations or citizens to support decisions.

Channeled PM10, PM2.5 and PM1 Emission Factors Associated with the Ceramic Process and Abatement Technologies

A sampling methodology and a mathematical data treatment were developed that enable to determine not only total suspended particulates (TSP) emitted at channeled sources but also the PM10, PM2.5, and PM1 mass fractions (w10, w2.5, and w1) and emission factors (E.F.), using a seven-stage cascade impactor. Moreover, a chemical analysis was performed to identify the elements present in these emissions. The proposed methodology was applied to different stages of the ceramic process, including ambient temperature (milling, shaping, glazing) and medium-high-temperature (spray-drying, drying, firing, and frit melting) stages. In total, more than 100 measurements were performed (pilot scale and industrial scale), which leads to a measurement time of 1500 h. Related to the mass fractions, in general, the mean values of w10 after the fabric filters operated at high performance are high and with little dispersion (75-85%), and it is also observed that they are practically independent of the stage considered, i.e., they are not significantly dependent on the initial PSD of the stream to be treated. In the case of the fine fraction w2.5, the behavior is more complex (w2.5: 30-60%), probably because the only variable is not the cleaning system, but also the nature of the processed material. Regarding abatement measures, the use of high-efficiency cleaning systems considerably reduces the emission factors obtained for fractions PM10, PM2.5, and PM1. In reference to chemical analysis, the presence of ZrO2 and Ni in the spray-drying and pressing stages, the significant concentration of ZrO2 in the glazing stage, the presence of Pb, As, and Zn in the firing stage, and the presence of Zn, Pb, Cd, and As compounds in the frits manufacturing should all be highlighted. Nevertheless, it should be pointed out that the use of some compounds, such as cadmium and lead, has been very limited in the last years and, therefore, presumably, the presence of these elements in the emissions should have been also reduced in the same way.

A simple physical-activity-based model for managing children's activities against exposure to air pollutants

Air pollution has been a major health concern worldwide, such that there is an urgent need for exposure assessments of human exposure to air pollutants. As children are more active and may experience more exposure events than adults, it is more challenging to conduct exposure assessments for children. To obtain a general understanding of the impact that children's activity, associated with their respiratory rate (IR), has on estimated exposure risks, we adopted a simple model to narrow down children's exposure behaviors to four categories, which integrated children's regular schedules and the indoor-outdoor ratio (r_I/O) of air pollutants. Although outdoor play only occupies approximately 8.6% of the total weekly time, the results indicate that, in general, outdoor play contributes to over 50% of the total exposure to air pollutants when r_I/O is less than 0.1, which is due to children's relatively large IR during high-intensity activities. When air pollutants mainly originate from indoor sources (i.e., r_I/O=3.0), indoor sitting (28%) and sleeping (36%) account for the major portion of the total exposure due to the longer exposure duration while outdoor events, including playing, walking, and sitting, account for ~15% of the total exposure. In addition, we applied a ratio function (R_M/C) to compare our simple model to a common basic model, revealing that our simulated results are consistent with the basic model, i.e., 0.94≤R_M/C≤1.12, if the r_I/O of air pollutants falls in the range between 0.5 and 1.5. The sensitivity analysis indicates that indoor or outdoor play has a larger impact on the output results than other activity-related variables because of the correspondingly largest IR. We also incorporated weather factors to adjust children's activity schedules for winter and non-winter days showing the change in the contributions of children's activities to total exposure. For example, the contribution differential of outdoor play to the total exposure between winter and non-winter days is ~8% for air pollutants with an r_I/O value of 0.1. Although other factors, such as the activity intensity level and concentration of air pollutant in the microenvironment, must be refined in future studies, our simple model can be applied as a convenient approach to arrange children's activity schedules against possible air pollutant exposure.

Pollution Weather Prediction System: Smart Outdoor Pollution Monitoring and Prediction for Healthy Breathing and Living

Air pollution has been a looming issue of the 21st century that has also significantly impacted the surrounding environment and societal health. Recently, previous studies have conducted extensive research on air pollution and air quality monitoring. Despite this, the fields of air pollution and air quality monitoring remain plagued with unsolved problems. In this study, the Pollution Weather Prediction System (PWP) is proposed to perform air pollution prediction for outdoor sites for various pollution parameters. In the presented research work, we introduced a PWP system configured with pollution-sensing units, such as SDS021, MQ07-CO, NO2-B43F, and Aeroqual Ozone (O₃). These sensing units were utilized to collect and measure various pollutant levels, such as PM2.5, PM10, CO, NO₂, and O₃, for 90 days at Symbiosis International University, Pune, Maharashtra, India. The data collection was carried out between the duration of December 2019 to February 2020 during the winter. The investigation results validate the success of the presented PWP system. In the conducted experiments, linear regression and artificial neural network (ANN)-based AQI (air quality index) predictions were performed. Furthermore, the presented study also found that the customized linear regression methodology outperformed other machine-learning methods, such as linear, ridge, Lasso, Bayes, Huber, Lars, Lasso-lars, stochastic gradient descent (SGD), and ElasticNet regression methodologies, and the customized ANN regression methodology used in the conducted experiments. The overall AQI values of the air pollutants were calculated based on the summation of the AQI values of all the presented air pollutants. In the end, the web and mobile interfaces were developed to display air pollution prediction values of a variety of air pollutants.

The role of forest in mitigating the impact of atmospheric dust pollution in a mixed landscape

Atmospheric dust pollution, especially particulate matter below 2.5 μm, causes 3.3 million premature deaths per year worldwide. Although pollution sources are increasingly well known, the role of ecosystems in mitigating their impact is still poorly known. Our objective was to investigate the role of forests located in the surrounding of industrial and urban areas in reducing atmospheric dust pollution. This was tested using lichen transplants as biomonitors in a Mediterranean regional area with high levels of dry deposition. After a multivariate analysis, we have modeled the maximum pollution load expected for each site taking into consideration nearby pollutant sources. The difference between maximum expected pollution load and the observed values was explained by the deposition in nearby forests. Both the dust pollution and the ameliorating effect of forested areas were then mapped. The results showed that forest located nearby pollution sources plays an important role in reducing atmospheric dust pollution, highlighting their importance in the provision of the ecosystem service of air purification.

Separating natural from anthropogenic causes of impairment in Zebra mussel (Dreissena polymorpha) populations living across a pollution gradient

The relationship between the reproductive stage, the total lipid content and eight broadly used biochemical stress responses were used to assess seasonal and pollutant effects across eleven different zebra mussel (Dreissena polymorpha) populations from the Ebro and Mijares river basin, Spain. Biochemical markers included superoxide dismutase (SOD), catalase (CAT), glutathione (GSH), glutathione S transferase (GST), multixenobiotic transporter activity (MXR), lactate dehydrogenase (LDH), lipid peroxidation (LPO) and single strand DNA breaks. Principal component analyses of zebra mussel responses across an annual cycle, showed a marked gonad stage component in total lipid content and biochemical responses. The same response pattern was observed across the populations sampled along a broad geographical and pollution gradient. Population differences on the gonad developmental stage were highly correlated with most of the measured responses and unrelated with the pollution gradient. Conversely, bioaccumulation of organic and inorganic contaminant residues was more related to pollution sources than with the reproductive cycle. These results indicate that the reproductive cycle is the major factor affecting the temporal and spatial variation of the studied markers in D. polymorpha.