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Big datasets of air-quality pollutants and weather data allow us to review trends of NO 2 , NO, O 3 , and global radiation (GR), for Lisbon, Porto and Coimbra, with regard to the historical period of 2010–2018. GR is expected to have a considerable impact on photochemical reactions of the O 3 formation mechanism. We aim to characterize daily, monthly, and yearly trends. We explore Weekday (WD) versus weekend (WE), and seasonality of O 3 and NO 2 . We are interested to know these pollutant peak concentration variations over the years and investigate if parallels can be drawn between urban mobility indicators and these pollutants. For this purpose, economic data, European emission standards, and car stock data (fuel, age, and number of vehicles) are cross-analyzed. How are they correlated? Has it impacted NO 2 and O 3 variations? How do different air-quality monitoring stations (AQMS), traffic and non-traffic, compare? How is Lisbon NO x -O 3 correlated? What are its implications for future scenarios? Results show that urban mobility trends and economic events are correlated with NO 2 and O 3 variability. Weekend effect has a partial relationship with urban mobility trends and economy as it is relatively well correlated for Lisbon but not for Porto and Coimbra. Nonetheless, weekend effect for the period of 2010–2018 is overall trending upwards for all cities. In Lisbon and Coimbra, O 3 concentrations also trend upwards during the same 2010–2018 period but for Porto they do not. Regardless, for the period of 2015–2018, after the economic recession, the upwards trends of both weekend effect and overall O 3 concentrations are clear for all AQMS. For AQMS peak values comparison, Lisbon traffic AQMS registered an annual averaged 8-hour daily max O 3 concentration of 34.4 ppb while Lisbon non-traffic AQMS presented 39.1 ppb. Altogether, annual 8-hour daily maximum values for 2010–2018 traffic AQMS in Lisbon show an inverse relationship with fuel sales, and have concentrations fluctuating between 28–35 ppb, which is slightly higher than the 2001–2010 historical European range of 27–31 ppb. Lastly, for the 8 years data in Lisbon, it has been shown that a negative NO x -O 3 correlation exists, and the study location might be VOC–sensitive. This means that as NO x concentrations decrease, O 3 concentrations become exponentially higher. Further research into VOCs with better data availability is required to make more concise claims. Regardless, it can be inferred that in a future scenario where mitigation continues to escalate, through O 3 emission standards and an aggressive shift of car stock to electric vehicles, achieving unprecedented rises in O 3 concentrations could be observed.
Angelo Soares; Ricardo Deus; Carla Barroso; Carla Silva. Urban Ground-Level O3 Trends: Lessons from Portuguese Cities, 2010–2018. Atmosphere 2021, 12, 183 .
AMA StyleAngelo Soares, Ricardo Deus, Carla Barroso, Carla Silva. Urban Ground-Level O3 Trends: Lessons from Portuguese Cities, 2010–2018. Atmosphere. 2021; 12 (2):183.
Chicago/Turabian StyleAngelo Soares; Ricardo Deus; Carla Barroso; Carla Silva. 2021. "Urban Ground-Level O3 Trends: Lessons from Portuguese Cities, 2010–2018." Atmosphere 12, no. 2: 183.
Ground-level ozone in cities is increasing mainly due to traffic exhaust aftertreatment devices, i.e., tailpipe catalytic converters. The chemical reaction of O3 formation indicates radiation and nitrogen oxides as main players. Thus, we investigate correlations between O3, global radiation, nitrogen oxides, temperature, and precipitation in several periods of the year (2017) near a traffic roundabout in Lisbon city (coordinates 38°44’55’’ lat, −9°08’56’’ long). The weekend effect, school break versus school period, day and night, and seasonal effect were explored. Low-cost sensors (LCS) of O3, NOx, and temperature were tested to see if they can be used to get historical data on other cities and locations. The main innovation is the calibration of the sensor directly with real data (uncontrolled environment). Raw data were compared and led us to conclude that MQ-131 has a better performance than the MICS-4514 sensor. The results indicate that the diurnal cycle of ozone concentration has a mid-day peak around 1–2 pm and a lower nighttime concentration below 5 ppb Weekends and school break period (251 days a year) have the highest values of Ozone, this is due to lower NOx emissions and thus lower levels of ozone destruction reaction (NOx-titration reaction). August is a hotspot month with a maximum concentration of 71 ppb.
Angelo Roldão Soares; Duarte Neto; Tiago Avelino; Carla Silva. Ground Level Ozone Formation Near a Traffic Intersection: Lisbon “Rotunda De Entrecampos” Case Study. Energies 2020, 13, 1562 .
AMA StyleAngelo Roldão Soares, Duarte Neto, Tiago Avelino, Carla Silva. Ground Level Ozone Formation Near a Traffic Intersection: Lisbon “Rotunda De Entrecampos” Case Study. Energies. 2020; 13 (7):1562.
Chicago/Turabian StyleAngelo Roldão Soares; Duarte Neto; Tiago Avelino; Carla Silva. 2020. "Ground Level Ozone Formation Near a Traffic Intersection: Lisbon “Rotunda De Entrecampos” Case Study." Energies 13, no. 7: 1562.
The lower cost of sensors is making possible the acquisition of big data sets in several applications and research areas. Indoor air quality and commuter exposure to pollutants are some of these areas, which can have impacts on our livelihood. The main objective of this exploratory research was to assemble portable equipment along with a prototype, one low-cost and easy to replicate in any location worldwide. We answer how CO2, noise and energy expenditure compare in different transportation modes with indoor environments (metro, bus and car). It was intended to be carried by a subject on all commutes. The low-cost equipment assembled has the ability to measure ambient CO2, noise levels, heart rate and geographic coordinates. The field campaign was conducted on an urban commuting route, in Lisbon city, between Rossio (downtown of Lisbon city) and Campo Grande (near FCUL campus). It took place during 3 weeks in school break and 3 weeks in the school period to grasp some differences between these periods of the year. The heart rate data was used to calculate the subject energy expenditure and the geographic coordinate data allowed for time and spatial analysis using a geospatial software package. Our measurements totaled 70 one-way trips and 358,140 data points. Temporal and spatial analysis yielded the following results: The metro presents the lowest median CO2 concentrations of 693 ppm and the bus the highest with 1085 ppm. The bus had an equivalent continuous sound average (Leq) of 75 dBA, while the metro had 85.2 dBA. Based on the metabolic equivalent of task (MET) calculations, the metro displays the least sedentary behavior, while the bus presents the most sedentary behavior with up to 96.5% of its commute spent in this classification. The metro was the fastest mode of transportation based on the consistency of its travel times compared to the bus, which despite also being consistent, was slower by 1.8 times. The car measurement values reside in the middle of the metro and bus results. Despite this, it is considered the worst mode of transportation, as it goes against the idea of a less congested and clean city. It also has a highly variable commuting time, which sometimes makes it slower than the metro, especially during the school period. According to our results, we concluded that the metro had efficient indoor ventilation while the bus did not. There were several instances of inefficient ventilation with concentrations exceeding 1000 ppm, particularly between Restauradores and Saldanha due to overcrowding. Referring to the health impacts of noise, the metro dBA levels are not sustained for enough time to have any measurable negative impact. Sensor performance was considered acceptable for the CO2 sensor. The dBA and heart rate (HR) sensors were considered acceptable to sometimes irregular in nature, which was expected and taken into consideration.
Angelo Soares; Cristina Catita; Carla Silva. Exploratory Research of CO2, Noise and Metabolic Energy Expenditure in Lisbon Commuting. Energies 2020, 13, 861 .
AMA StyleAngelo Soares, Cristina Catita, Carla Silva. Exploratory Research of CO2, Noise and Metabolic Energy Expenditure in Lisbon Commuting. Energies. 2020; 13 (4):861.
Chicago/Turabian StyleAngelo Soares; Cristina Catita; Carla Silva. 2020. "Exploratory Research of CO2, Noise and Metabolic Energy Expenditure in Lisbon Commuting." Energies 13, no. 4: 861.