We analyzed the urban development sustainability in five major urban areas of Algeria by the standard of the UN Sustainability Development Goal indicator SDG 11.3.1, which focuses on the ratio of land consumption rate to population growth rate. We utilized the annual global artificial impervious area (GAIA) dataset to characterize land-use and population data from the two censuses carried out by the National Office of Statistics (ONS) for 2008 and 2018. We discuss the prevailing relationship between urban land consumption rate and population growth rate at the smallest territorial and population census unit scale. We confirm that the indicator SDG 11.3.1 is nonlinear and that while, for example, the wilaya of Tlemcen as a whole appears to be on a sustainable path, twenty-one of its communes are not. We found that overall, and for most of its communes, the wilaya of Oran seems to have an urban land use commensurable to its population growth, but in the wilaya of Algiers, out of fifty-seven communes, only fourteen have a tendency towards sustainable development. However, the latter wilaya hosts the country’s capital and includes government buildings that are uninhabited but are accounted for as land consumed, and as such, the relationship between urban land consumption and population growth is biased. The wilaya of Annaba showed large discrepancies in terms of land use and population growth rates, and the evolution of these quantities is not homogenous across communes and not sustainable. In the Saharan wilaya of Ghardaia, the development is not homogeneous in all communes, with smaller communes undergoing buildup increases of more than 150% over the decade. Finally, in all communes where population growth exceeded urban land growth, there will be overcrowding, an aspect neither the SDG 11.3.1 nor the impervious surface per capita indicator captures. This result, in addition to other limitations, makes SDG 11.3.1 incomplete for the determination of the sustainable development in urban areas.

This study aims to elucidate the influence of meteorological conditions on particle levels in Cergy-Pontoise. It explores the temporal variability of PM10 pollution days by associating them with the vertical temperature profile derived from conventional radiosondes from 2013 to 2022 (regional station). The results indicate that nearly 80% of exceedance days were associated with thermal inversions, primarily observed in winter and typically lasting 1 to 3 days. Analysis of winter thermal inversion characteristics suggests that those linked to pollution primarily occur near the ground, with higher intensity in December (12.1 °C) and lower in February (10.3 °C). Persistent inversions (extended nocturnal by diurnal inversion) account for 91.4% of the total inversions associated with high concentrations. Captive balloon soundings and temperature measurements at different altitudes were conducted during the winter of 2022/2023 to clarify thermal inversion in the Oise Valley at the center of Cergy-Pontoise. The results highlight three nocturnal wind circulation mechanisms in the valley, including downslope flow, circulation influenced by an urban heat island, and mechanical air evacuation under an inversion layer towards the less steep East side of the valley. Analysis of PM with the temperature gradient in the Oise Valley shows a significant correlation, suggesting an increase in concentrations during locally detected inversions and a decrease during atmospheric disturbance.

During the last decades, Morocco has recorded substantial urbanization and faced challenges related to urban sprawl and encroachment on fertile lands. This paper reviews several studies assessing urban sustainability development in 27 Moroccan urban areas using the UN’s Sustainable Development Goal (SDG) indicator 11.3.1, i.e., the ratio of Land Consumption Rate (LCR) to Population Growth Rate (PGR). Among the 27 urban areas reviewed, analysis of SDG 11.3.1 data revealed that only 7 exhibited trends towards sustainable urban development, while the remaining 20 showed a divergence from the sustainability objectives. We analyze the studies, conducted between 2020 and 2023, describing in depth the relationship between LCRs and PGRs, and provide a comprehensive summary of the SDG 11.3.1 outcome, discussing along the way methodological variations, and introducing a new concept for the evaluation of urban land consumption. The review reveals disparate regional urban development trends, emphasizing the need for local land tenure rules. Additionally, the study discusses how the SDG 11.3.1 reacts under the influence of several parameters such as land characteristics, climate, and geographic location. While the study acknowledges the limitations of SDG 11.3.1, it found that the indicator provides valuable insights into trends and comparisons, and should offer assistance to stakeholders, urban planners, and decision makers in their pursuit of sustainable development. However, these identified limitations underscore the need for a more comprehensive and multidimensional urban sustainability development indicator, capable of better addressing the complexities of the urban environment.

In urban areas, road transportation is the main source of pollutants, and weather impacts spatiotemporal variation of air quality. In this paper, we demonstrate the spatiotemporal variabilities of particulate matter (PM₁₀ and PM_2.5) and NO₂ in the south of Paris, with an emphasis on the comparison of air pollutant levels between COVID-19 lockdown and non-lockdown days according to meteorological conditions. The influence of COVID-19 lockdowns could be region-specific. Thus, it is worthwhile to conduct investigations across different regions and via different methodologies. This manuscript contains data that could be relied upon to evaluate available options for mitigation of urban air pollution. Using Airparif data and mobile survey data collected by Aeroqual 500 sensors, this study confirms that road traffic seems to be the determining factor of air quality in the southern part of Paris. The daily average concentrations of NO₂, PM_2.5 and PM₁₀ calculated in 2020 show a strong spatiotemporal variability explained by the type of weather on the one hand and by the proximity of emission sources on the other hand. Mobile surveys show that during lockdowns in 2020, when the weather was stable, in 13th arrondissement of Paris, NO₂ values exceeded 250 µg/m³ with PM₁₀ values over 70 µg/m³, mainly in three locations: the area between Rue Tolbiac and Rue Nationale, along Rue de Chevaleret, and on Boulevard Périphérique.

Daily atmospheric concentrations of the pollutants PM₁₀ and O₃ vary according to weather types. This study aims to identify the weather patterns associated with PM₁₀ and O₃ pollution episodes from 2009 to 2020. Episodes characterized by exceedance of World Health Organization standards were identified, and their duration and persistence were studied. The results show that air pollution days are associated with three atmospheric patterns for PM₁₀ and four for O₃. The dominant weather pattern corresponds to an anticyclonic situation in central and Eastern Europe with a ridge of high pressure over France at the surface and 500-hPa geopotential height. For PM₁₀, the persistent high-concentration sequences were found to be associated with a thermal inversion constraining the vertical dispersion of pollutants. For O₃, the four weather types responsible for ozone pollution all have a higher occurrence in summer. The highest percentage (46% of days) is associated with the presence of a ground-level barometric marsh (an area of the atmosphere between two weather systems where the pressure varies slightly but is slightly low) and a ridge at 500 hPa (weather type T1). Similarly, thermal inversions and thermal winds cause pollution to persist beyond 8 consecutive days. Significance Statement: Air quality is not only influenced by ground-level emissions, but also by complex meteorological processes that can contribute to pollutant accumulations. The importance of this research is that the prediction of these processes helps to prevent the development of extreme concentrations near the surface. The results of this study provide a better understanding of how characteristic weather patterns in the Cergy-Pontoise conurbation impact PM₁₀ and O₃ pollutant levels. These impacts are expressed by the intensity and frequency of pollution episodes.

This study employed a network comprising 16 fixed “Ecosmart” sensors deployed in the Cergy‐Pontoise conurbation. Continuous measurements of PM₁₀, PM_2.5, and NO₂, significant pollutants in the Paris region, were conducted from April 8 to June 6, 2022. The collected data were represented as statistically composite spatial matrices due to the heterogeneous urban landscape and the overlapping of multiple pollution sources. Temporal variations on a daily basis were influenced by both traffic and meteorological conditions. Daytime, characterized by denser traffic compared to nighttime, exhibited higher concentrations of PM₁₀ and PM_2.5. Conversely, NO₂ concentration levels displayed two peaks associated with traffic volume, and relatively elevated nocturnal values compared with midday due to atmospheric vertical stability during the nighttime phase. The analysis of weather‐type impacts revealed that during unstable weather conditions, elevated particle concentrations stemmed from dust resuspension from the ground and long‐range transport. Maximum NO₂ concentrations were observed during stable weather conditions, whereas minimum concentrations occurred during unstable weather.