ABSTRACT
Nitrogen dioxide (NO2) air pollution provides valuable information for quantifying NOx emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO2 emission strengths derived from three-year (April 2018 - March 2021) TROPOMI observations by combining a wind-assigned anomaly approach and a Machine Learning (ML) method, the so-called Gradient Descent. This combined approach is firstly applied to the Saudi Arabian capital city Riyadh, as a test site, and yields a total emission rate of 1.04×1026 molec./s. The ML-trained anomalies fit very well with the wind-assigned anomalies with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO2 emissions are apparent at several sites where the cement plant and power plants are located and over areas along the highways. Using the same approach, an emission rate of 1.80×1025 molec./s is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable to the CAMS inventory. Weekly variations of NO2 emission are highly related to anthropogenic activities, such as the transport sector. The NO2 emissions were reduced by 24% at weekends in Riyadh, and high reductions are found near the city center and the areas along the highway. An average weekend reduction estimate of 30% in Madrid is found. The regions with dominant sources are located in the east of Madrid, where the residential areas and the Madrid-Barajas airport are located. Additionally, the NO2 emissions decreased by 21% in March-June 2020 compared to the same period in 2019 induced by the COVID-19 lockdowns in Riyadh. A much higher reduction (60%) is estimated for Madrid where a very strict lockdown policy was implemented. The high emission strengths during lockdown only persist in the residential areas and cover smaller areas during weekdays than at weekends. The spatial patterns of NO2 emission strengths during lockdown are similar to those observed at weekends in both cities. Though our analysis is limited to two cities as testing examples, the method has proved to provide reliable and consistent results. Therefore, it is expected to be suitable for other trace gases and other target regions. [ FROM AUTHOR] Copyright of Atmospheric Measurement Techniques Discussions is the property of Copernicus Gesellschaft mbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
The goals globally assumed related to social and environmental challenges, plus the COVID-19 pandemic, have pointed to the need of reducing private vehicle mobility and articulating proximity structures in cities. This task must not ignore the demand for mobility generated by the functional configuration of urban areas after the metropolitan expansion processes carried out in the recent decades. On the basis of mobility data, this work analyses the evolution of retail and leisure centralities in Madrid Urban Area between 1996 and 2018, and its effects on proximity, sustainable mobility modes, and socio-spatial segregation. The results show a remarkable transformation of the functional structure during this period, which is unfavorable to the objectives pursued. Compared to 1996, the centralities based on pedestrian mobility and proximity have lost relative weight and relevance, while new peripheral sections highly dependent on private vehicles have gained new centrality. © 2022, Universidad de Chile, Instituto de la Vivienda. All rights reserved.
ABSTRACT
In this work, the evolution of the fine particulate air pollution (of size below one μm) produced by the vehicles when driving along several roads of Madrid is studied. Measurements were taken with portable near real-time sensors of Diffusion Charging (DC) and Photoelectric Charging (PC) while driving along the roads. The obtained measurement profiles basically consist of spikes when measuring in the exhaust plumes of preceding vehicles and a background level of mixed aged exhaust that forms when high traffic intensity exist. The DC sensor measures air concentration of the particles Total Active Surface (TAS) and the PC sensor was calibrated to measure the air concentration of Particle bound Polycyclic Aromatic Hydrocarbons (PPAH). The amount of adsorbed PAH per active surface (the PC/DC ratio) is a measure of particles toxicity. Both sensors are sensible to ultra-fine particles of size below 0.1 μm. The measured median values of DC and PC, for the years 1999, 2001, 2005, 2006, 2016, 2017, 2020 and 2021, are plotted as well as their median PC/DC ratio. Examples of measurement profiles are also shown including measurements during COVID-19 driving restrictions. During these restrictions, we could conclude that our measured particulate air pollution of fine and ultrafine particles is caused by "polluting-vehicles" still coexisting in the vehicle fleet of Madrid, which do not fulfill the latest Euro standard because they are too old or have no/malfunctioning catalytic converter and/or diesel particle filter (DPF). The changes of the measured median of the DC and PC values are discussed based on already known results of implemented vehicle technologies for reducing emissions, the evolution of the vehicle fleet fulfilling the increasingly demanding Euro standards, the traffic count, the PC and DC working principles, the evolution of the exhaust emission when exiting the pipe, and on the sulfur content reductions in diesel. The main factors that allowed the large reduction of the median values of both DC and PC (from 1167 ± 57 mm2/m3 and 990 ± 54 ng/m3 in 1999 to 263 ± 14 mm2/m3 and 124 ± 7 ng/m3 in 2021 respectively) as well as the changes in the PC/DC ratio was, according to our findings, the diesel sulfur content reduction and the implementation of the Diesel Oxidation Catalysis (DOC) and the DPF. • Decrease in the total active surface of fine particles in the air of the city of Madrid since 1999. • Decrease in PAH adsorbed on fine particles in the air along the roads of the city of Madrid since 1999. • Evolution of on-road fine and ultrafine exhaust particle emissions in Madrid since 1999. • Drastic localized increase of air suspended fine particles caused by specific polluting vehicles. • Changes in the on-road fine and ultrafine exhaust particles toxicity in Madrid since 1999. [ FROM AUTHOR] Copyright of Atmospheric Environment is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
The COVID-19 pandemic was the worst public, economic and social health crisis in Spain since the Civil War. This virus caused thousands of deaths and hundreds of thousands of infections, with Catalonia and Madrid as the most affected territories. A first exploratory analysis shows, with the scarce reliable data available so far, that this pandemic has had a special impact on urban areas with higher population density and pollution levels, while rural areas, despite having a much higher at-risk population and a much more precarious healthcare system, have proven to be much more resilient to coronavirus expansion. All this opens the door to revaluing the importance of the rural environment as an analytical category and as a space for opportunities and life in the face of present and future pandemics and not just problems and crises. © 2022, Universitat Autonoma de Barcelona. All rights reserved.
ABSTRACT
Due to the rapid expansion of the COVID-19 pandemic, many countries ordained lockdowns, establishing different restrictions on people's mobility. Exploring to what extent these measures have been effective is critical in order to better respond to similar future scenarios. This article uses anonymous mobile phone data to study the impact of the Spanish lockdown on the daily dynamics of the Madrid metropolitan area (Spain). The analysis has been carried out for a reference week prior to the lockdown and during several weeks of the lockdown in which different restrictions were in place. During these weeks, population distribution is compared during the day and at night and presence profiles are obtained throughout the day for each type of land use. In addition, a spatial multiple regression analysis is carried out to determine the impact of the different land uses on the local population. The results in the reference week, pre-COVID-19, show how the population in activity areas increases in each time slot on a specific day and how in residential areas it decreases. However, during the lockdown, activity areas cease to attract population during the day and the residential areas therefore no longer show a decrease. Only basic essential commercial activities, or others that require the presence of workers (industrial or logistics) maintain some activity during lockdown.