No abstract

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.

The process of removing organic components from wastewater as BOD5 through wastewater treatment plants has been proven to be a significant source of greenhouse gas emissions, mainly methane CH4, carbon dioxide CO2 and nitrous oxide N2O. The reduction of these emissions has attracted more interest given their major contribution to global warming. This study was able to identify and estimate the amount of methane and CO2 emissions on a monthly basis by a simple modeling approach and an empirical method (IPCC) for N2O emissions, in the case of Ain-Taoujdate wastewater treatment plant, throughout the years 2013, 2018 and 2019. The results showed that anaerobic ponds were the main source of on-site emissions with 66% of total contribution and 33% for facultative ponds, followed by the energy consumption of the pumping station as off-site GHG emissions.

In the last decades, the world population rate has been gradually increasing, this population growth has faced intense urban expansion and the rapid development of the agricultural and industrial sectors. This change had an impact on the mode of land use. In the face of this problem, several strategies have been created for monitoring and predicting possible future scenarios on rhythm of land use change. The CA-Markov model used in this research allows to predict future land use trends on the basis of the classified maps of 1987, 1999, 2011 and 2019. Simulating and tracking these maps is a major challenge. The latter provides important information in terms of data, methods and models to be used to create a realistic and sustainable process of territory planning for environmentalists, planners and local authorities. The combination of the Markov chain and cellular automata has been used to qualitatively and quantitatively simulate and evaluate future land use trends in coastal Chaouia, Morocco. To achieve this purpose, two maps were developed for the two years of 2027 and 2035. By using kappa, the global success of the modelling was 89.22% and 82.12% respectively in 2011 and 2019 for the projected land use map. The results confirm that forests have been affected by intensive agricultural uses. This increase in agricultural use is due to the impact of the constant increase in the development of the agroeconomic and demographic sectors. This situation indicates the need to create new approach to management to protect the sustainability of land use in coastal Chaouia.