Calibration of SO2 and NO2 Electrochemical Sensors via a Training and Testing Method in an Industrial Coastal Environment.

Low-cost sensors can provide inaccurate data as temperature and humidity affect sensor accuracy. Therefore, calibration and data correction are essential to obtain reliable measurements. This article presents a training and testing method used to calibrate a sensor module assembled from SO2 and NO2 electrochemical sensors (Alphasense B4 and B43F) alongside air temperature (T) and humidity (RH) sensors. Field training and testing were conducted in the industrialized coastal area of Quintero Bay, Chile. The raw responses of the electrochemical (mV) and T-RH sensors were subjected to multiple linear regression (MLR) using three data segments, based on either voltage (SO2 sensor) or temperature (NO2). The resulting MLR equations were used to estimate the reference concentration. In the field test, calibration improved the performance of the sensors after adding T and RH in a linear model. The most robust models for NO2 were associated with data collected at T < 10 °C (R2 = 0.85), while SO2 robust models (R2 = 0.97) were associated with data segments containing higher voltages. Overall, this training and testing method reduced the bias due to T and HR in the evaluated sensors and could be replicated in similar environments to correct raw data from low-cost electrochemical sensors. A calibration method based on training and sensor testing after relocation is presented. The results show that the SO2 sensor performed better when modeled for different segments of voltage data, and the NO2 sensor model performed better when calibrated for different temperature data segments.

Field performance of a low-cost sensor in the monitoring of particulate matter in Santiago, Chile.

Integration of low-cost air quality sensors with the internet of things (IoT) has become a feasible approach towards the development of smart cities. Several studies have assessed the performance of low-cost air quality sensors by comparing their measurements with reference instruments. We examined the performance of a low-cost IoT particulate matter (PM10 and PM2.5) sensor in the urban environment of Santiago, Chile. The prototype was assembled from a PM10-PM2.5 sensor (SDS011), a temperature and relative humidity sensor (BME280) and an IoT board (ESP8266/Node MCU). Field tests were conducted at three regulatory monitoring stations during the 2018 austral winter and spring seasons. The sensors at each site were operated in parallel with continuous reference air quality monitors (BAM 1020 and TEOM 1400) and a filter-based sampler (Partisol 2000i). Variability between sensor units (n = 7) and the correlation between the sensor and reference instruments were examined. Moderate inter-unit variability was observed between sensors for PM2.5 (normalized root-mean-square error 9-24%) and PM10 (10-37%). The correlations between the 1-h average concentrations reported by the sensors and continuous monitors were higher for PM2.5 (R2 0.47-0.86) than PM10 (0.24-0.56). The correlations (R2) between the 24-h PM2.5 averages from the sensors and reference instruments were 0.63-0.87 for continuous monitoring and 0.69-0.93 for filter-based samplers. Correlation analysis revealed that sensors tended to overestimate PM concentrations in high relative humidity (RH > 75%) and underestimate when RH was below 50%. Overall, the prototype evaluated exhibited adequate performance and may be potentially suitable for monitoring daily PM2.5 averages after correcting for RH.

Secondary particles formed from the exhaust of vehicles using ethanol-gasoline blends increase the production of pulmonary and cardiac reactive oxygen species and induce pulmonary inflammation.

BACKGROUND: Ethanol vehicles release exhaust gases that contribute to the formation of secondary organic aerosols (SOA). OBJECTIVE: To determine in vivo toxicity resulting from exposure to SOA derived from vehicles using different ethanol-gasoline blends (E0, E10, E22, E85W, E85S, E100). METHODS: Exhaust emissions from vehicles using ethanol blends were delivered to a photochemical chamber and reacted to produce SOA. The aerosol samples were collected on filters, extracted, and dispersed in an aqueous solutions and intratracheally instilled into Sprague Dawley rats in doses of 700 µg/0.2 ml. After 45 min and 4 h pulmonary and cardiac chemiluminescence (CL) was measured to estimate the amount of reactive oxygen species (ROS) produced in the lungs and heart. Inflammation was measured by differential cell count in bronchoalveolar lavages (BAL). RESULTS: Statistically and biologically significant differences in response to secondary particles from the different fuel formulations were detected. Compared to the control group, animals exposed to SOA from gasoline (E0) showed a significantly higher average CL in the lungs at 45 min. The highest CL averages in the heart were observed in the groups exposed to SOA from E10 and pure ethanol (E100) at 45 min. BAL of animals exposed to SOA from E0 and E85S had a significant increased number of macrophages at 45 min. BAL neutrophil count was increased in the groups exposed to E85S (45 min) and E0 (4 h). Animals exposed to E0 and E85W had increased BAL lymphocyte count compared to the control and the other exposed groups. DISCUSSION: Our results suggest that SOA generated by gasoline (E0), followed by ethanol blends E85S and E85W, substantially induce oxidative stress measured by ROS generation and pulmonary inflammation measured by the recruitment of white blood cells in BAL.

Monitoring and modeling of household air quality related to use of different Cookfuels in Paraguay.

In Paraguay, 49% of the population depends on biomass (wood and charcoal) for cooking. Residential biomass burning is a major source of fine particulate matter (PM2.5 ) and carbon monoxide (CO) in and around the household environment. In July 2016, cross-sectional household air pollution sampling was conducted in 80 households in rural Paraguay. Time-integrated samples (24 hours) of PM2.5 and continuous CO concentrations were measured in kitchens that used wood, charcoal, liquefied petroleum gas (LPG), or electricity to cook. Qualitative and quantitative household-level variables were captured using questionnaires. The average PM2.5 concentration (µg/m3 ) was higher in kitchens that burned wood (741.7 ± 546.4) and charcoal (107.0 ± 68.6) than in kitchens where LPG (52.3 ± 18.9) or electricity (52.0 ± 14.8) was used. Likewise, the average CO concentration (ppm) was higher in kitchens that used wood (19.4 ± 12.6) and charcoal (7.6 ± 6.5) than in those that used LPG (0.5 ± 0.6) or electricity (0.4 ± 0.6). Multivariable linear regression was conducted to generate predictive models for indoor PM2.5 and CO concentrations (predicted R2  = 0.837 and 0.822, respectively). This study provides baseline indoor air quality data for Paraguay and presents a multivariate statistical approach that could be used in future research and intervention programs.

Afecciones respiratorias por el uso de leña y carbón en comunidades de Paraguay

Introducción: El uso de combustibles sólidos está asociado con más de 4 millones de muertes prematuras anuales en el mundo, especialmente de mujeres y niños. El uso del carbón y la leña son todavía muy prevalentes en Paraguay donde el 21% de la población urbana y 71% de la población rural utilizan estos combustibles para cocinar. Objetivo: Describir el uso de energía en los hogares de dos comunidades en Paraguay, una semi urbana y una rural. Metodología: Se trata de un estudio de tipo descriptivo y de corte transverso que se realizó por medio de una encuesta en 250 casas seleccionadas aleatoriamente. Resultados: El análisis de los datos obtenidos muestra que más del 74% de los hogares usan carbón vegetal, ya sea como combustible principal o secundario, el gas licuado del petróleo (GLP) es más usado en la comunidad semiurbana (59% > 43%) y la leña es más usada en la comunidad rural (49.6% >22.8%). El uso de leña implica un mayor tiempo destinado a la recolección, acondicionamiento y cocinado de alimentos. El uso de leña y carbón se hace predominantemente al aire libre (84% de los hogares) en cocinas sin chimenea. Se encontró una mayor prevalencia de enfermedades respiratorias en los hogares que utilizan carbón o leña (45%> 29%). El uso de electricidad para cocinar no es muy prevalente (únicamente el 7% lo usa como combustible principal). Conclusión: El uso de carbón y leña en los hogares del Paraguay es alto lo que tiene repercusiones en la salud y favorece las condiciones de inequidad social en el país. Se considera que una buena alternativa al uso de biomasa en Paraguay sería la electricidad, debido a que cuenta con grandes recursos hidroeléctricos y la red eléctrica cubre a casi la totalidad de la población (99%).

Introduction: The use of solid fuels is associatedwith more than 4 million premature deaths annually in the world, especially in women and children. The use of charcoal and firewood is still very prevalent in Paraguay, where 21% of the urban population and 71% of the rural population use these fuels for cooking. Objective: To describe the use of energy in the homes of two communities in Paraguay, a semi-urban and a rural one. Material and Methods: This was a descriptive and cross-sectional study that was carried out by means of a survey in 250 randomly selected households. Results: The analysis of the data obtained showed that more than 74% of households used charcoal, either as a primary or a secondary fuel. Liquefied petroleum gas (LPG) was more commonly used in the semi-urban community (59%> 43%) and firewood was more used in the rural community (49.6%> 22.8%). The use of firewood implies a longer time for the collection, preparation and cooking of food. The use of firewood and charcoal was predominantly outdoors ( 84 % of households) in kitchens without a fireplace. A higher prevalence of respiratory diseases was found in households that used charcoal or firewood (45%> 29%). The use of electricity for cooking was not very prevalent (only 7% used it as the main fuel). Conclusion: The prevalence of the use of charcoal and wood in homes was high and has repercussions on collective health and favors the conditions of social inequality in the country. We suggest that promotion of electricity for cooking would be a viable clean alternative, because the country has large hydroelectric resources and the electric network covers almostthe entire population(99%).