Monographie en Série : Integrated Environmental Technology Series, Lens, P. (Ed.) | International audience | Environmental Technologies to Treat Nitrogen Pollution will provide a thorough understanding of the principles and applications of environmental technologies to treat nitrogen contamination. The main focus will be on water and wastewater treatment, with additional coverage of leachates and off-gasses. The book will bring together an up-to-date compilation of the main physical, chemical and biological processes demanded for the removal of nitrogenous contaminants from water, wastewater, leachates and off-gasses. It will include a series of chapters providing a deep and broad knowledge of the principles and applications required for the treatment of nitrogen pollution. Each chapter will be prepared by recognized specialists across the range of different aspects involved in the removal of nitrogenous contaminants from industrial discharges. Environmental Technologies to Treat Nitrogen Pollution will be the first book to provide a complete review of all the different processes used for the global management of nitrogen pollution. It will also contain updated information about strategies to achieve nitrogen recovery and reuse in different industrial sectors. Several case studies will document the application of different environmental technologies to manage nitrogen pollution. This book will be of interest to lecturers and graduate students in the following subject areas: Environmental Engineering, Environmental Biotechnology, wastewater treatment plant design, water pollution control, contaminants recovery and reuse. The book will also be an attractive reference for environmental engineering consultants.

chap. 9 | International audience

International audience

peer reviewed | Most scholars support the increase in carbon dioxide (CO2) emissions as one of the major causes of the increase in global climate change. Therefore, reducing CO2 emissions from the main emitter countries, including Iran as the sixth emitter, is important to deal with the harmful effects of global climate change. Accordingly, the main aim of this paper was to analyze the social, economic, and technical factors affecting CO2 emissions in Iran. Previous studies on diverse variables affecting emissions are not very accurate and reliable as they do not consider indirect effects. This study applied a structural equation model (SEM) to estimate the direct and indirect impacts of factors on the emissions by panel data for 28 provinces of Iran from 2003 to 2019. According to geographical location, three distinct regions, the north, center, and south of Iran were considered. The findings suggest that a 1% increase in social factor directly increased CO2 emissions by 2.23% (in the north) and 1.58% (in the center), but indirectly reduced emissions by 0.41% (in the north) and 0.92% (in the center). Hence, the total effects of the social factor on CO2 emissions were estimated at 1.82%, and 0.66% in the northern, and central regions, respectively. In addition, the total effects of the economic factor on CO2 emissions were estimated at 1.52%, and 0.73% in those regions. The results of this study showed that the direct effects of a technical factor on CO2 emissions were negative in the north and center. However, they were positive in the south of Iran. Based on the empirical results of this study, three policy implications are discussed in order to control CO2 emissions in regional distinctions of Iran as follows: First, policymakers should pay attention to the social factor, i.e., the growth of human capital in the southern region with the aim of increasing sustainable development. Second, Iranian policymakers must prevent unilaterally increasing gross domestic product (GDP) and financial development in the north and center. Third, policymakers should pay attention to the technical factor, i.e., improving energy efficiency, as well as upgrading information and communications technology (ICT) in the northern and central regions, and limiting the technical factor in the southern region.

peer reviewed | A dust storm is a major environmental problem affecting many arid regions worldwide. The novel contribution of this study is combining indicators extracted from RS- and statistic-based predictive models to spatial mapping of land susceptibility to dust emissions in a very important dust source area in the borders of Iran and Iraq (Khuzestan province in Iran and Al-Basrah and Maysan provinces in Iraq). In this research, remote sensing (RS) techniques and machine learning techniques, including multivariate adaptive regression spline (MARS), random forest (RF), and logistic regression (LR), were used for dust source identification and susceptibility map preparation. To this end, 152 DSA for the period of 2005-2020 were identified in the study area. Of these DSA data, 70% was assigned to the Dust Source Susceptibility Mapping (DSSM) (training dataset) and 30% to model validation. Consequently, six factors (i.e., soil, lithology, slope, normalized vegetation differential index (NDVI), geomorphology, and land use units) were prepared as DSA's independent and effective variables. The results of all three models indicated that land use had the most impact on DSA. The validation results of these models using the test data showed sub-curves of 0.92, 0.86, and 0.76 for the RF, MARS, and LR models, respectively. Also, results showed that the RF model outperformed MARS (AUC = 0.89) and LR (AUC = 0.78) methods. In all three models, high and very high susceptibility classes generally covered a large percentage of the case study. The highest percentage of dust source points was also in this susceptibility category. Overall, the results of this study can be useful for planners and managers to control and reduce the risk of negative dust consequences.

peer reviewed | This study analyzed the potential use of Payment for Ecosystem Services (PES) as a strategy for improving water supply management. This study focused on the Siminehroud Sub-basin due to its high importance to the Basin of Urmia Lake (UL). Siminehroud is the second provider of water (by volume) to Urmia Lake. To evaluate the technical and economic feasibility of a PES scheme, the current land use map was extracted using satellite imagery. In addition, the two algorithms of Support Vector Machines (SVMs) and Maximum Likelihood (ML) are used for Landsat images classification, rather than analyzing the relationship between land use and ecosystem services. Then, the most relevant ecosystem services provided in the region were evaluated using the Benefit Transfer Method. In the last step, by designing and implementing a survey, on the one hand, the local farmers' Willingness to Accept (WTA) cash payments for reducing the area they cultivate, and on the other hand, the farmers' Willingness to Pay (WTP) for managing the water consumption were determined. The results illustrated that the WTA program is more acceptable among the beneficiaries. It is also notable that this program needs very high governmental funding. Furthermore, the results of the program indicate that the land area out of the cultivation cycle will gradually increase while the price of agricultural water will also increase.

In marine settings, anthropogenic disturbances and climate change increase the rate of biological invasions. Predicting still undescribed invasive alien species (IAS) is needed for preparing timely management responses. We tested a strategy for discovering new potential IAS using DNA in a trans-equatorial expedition onboard RV Polarstern. During one-month travel, species inside ballast water experienced oxygen depletion, warming, darkness and ammonium stress. Many organisms died but several phytoplankton and zooplankton survivors resisted and were detected through a robust combination of individual sampling, DNA barcoding and metabarcoding, new in ballast water studies. Ammonium was identified as an important influential factor to explain diversity changes in phytoplankton and zooplankton. Some species reproduced until the end of the travel. These species tolerant to travel stress could be targeted as potential IAS and prioritized for designing control measures. Introducing resistance to travel stress in biosecurity risk analysis would be recommended.