Porous activated carbons derived from waste Moroccan pine cones for high-performance adsorption of bisphenol A from water.

Porous-activated carbons (ACs) derived from Moroccan pine cones (PC) were synthesised by a two step-chemical activation/carbonisation method using phosphoric acid (PC-H) and zinc chloride (PC-Z) as activating agents and used for the adsorption of bisphenol A (BPA) from water. Several techniques (TGA/DTA, FT-IR, XRD, SEM and BET) were used to determine the surface area and pore characterisation and variations during the preparation of the adsorbents. The modification significantly increased the surface area of both ACs, resulting in values of 1369.03 m2 g-1 and 1018.86 m2 g-1 for PC-H and PC-Z, respectively. Subsequent adsorption tests were carried out, varying parameters including adsorbent dosage, pH, initial BPA concentration, and contact time. Therefore, the highest adsorption capacity was observed when the BPA molecules were in their neutral form. High pH values were found to be unfavourable for the removal of bisphenol A from water. The results showed that BPA adsorption kinetics and isotherms followed pseudo-second-order and Langmuir models. Thermodynamic studies indicated that the adsorption was spontaneous and endothermic. Besides, the regeneration of spent adsorbents demonstrated their reusability. The adsorption mechanisms can be attributed to physical adsorption, hydrogen bonds, electrostatic forces, hydrophobic interactions, and π-π intermolecular forces.

A regional stocktake of maize yield vulnerability to droughts in the Horn of Africa.

Climate projections in sub-Saharan Africa predict increased frequency of droughts with parallel impacts on crop yield. The Horn of Africa is among the most vulnerable regions in Africa to these changes because agriculture in general and maize production in particularly is highly climate driven, and rain-fed. Current research approaches have mostly focused on the climatic and biophysical drivers of crop yield without including the socio-economic drivers of crop yield. This study fills this gap by investigating the vulnerability of maize yield in the Horn of Africa to climate and socio-economic indicators. The hypothesis is that there is an inverse relationship between vulnerability and adaptive capacity. The vulnerability index is a composite index that integrates sensitivity, exposure, and adaptive capacity sub-indices. Maize yield data to compute the sensitivity index were collected from FAOSTAT, precipitation data to compute the exposure index were collected from the Climate Research Unit (CRU), and the data for the proxies of adaptive capacity were collected from the readiness index database on figshare. From the results, Somalia records the highest vulnerability index of 1.15, followed by Ethiopia with a vulnerability index of 0.61. Kenya records the lowest vulnerability index of 0.33. Also, there is a positive relationship between the vulnerability, sensitivity, and the exposure indices and an inverse relationship between the vulnerability index and the adaptive capacity index. The high vulnerability index recorded in Somalia is accentuated by a low adaptive capacity index of 0.44 that is anchored on low literacy and high poverty rates. As Somalia records the lowest adaptive capacity index of 0.44, Ethiopia and Kenya record 0.91 and 0.99 respectively. This study has shown that to better understand vulnerability, a shift from the old paradigm that focuses on the climatic variables to integrating socio-economic variables or proxies of adaptive capacity which enhances our understanding of vulnerability. Though leveraging the benefits of climatic and non-climatic variables is important, the challenge so far has been on how to integrate these in the same model; a challenge this work has succinctly overcome by integrating adaptive capacity in the vulnerability equation.

COVID-19 response in Africa: impacts and lessons for environmental management and climate change adaptation.

The COVID-19 pandemic adds pressure on Africa; the most vulnerable continent to climate change impacts, threatening the realization of most Sustainable Development Goals (SDGs). The continent is witnessing an increase in intensity and frequency of extreme weather events, and environmental change. The COVID-19 was managed relatively well across in the continent, providing lessons and impetus for environmental management and addressing climate change. This work examines the possible impact of the COVID-19 pandemic on the environment and climate change, analyses its management and draws lessons from it for climate change response in Africa. The data, findings and lessons are drawn from peer reviewed articles and credible grey literature on COVID-19 in Africa. The COVID-19 pandemic spread quickly, causing loss of lives and stagnation of the global economy, overshadowing the current climate crisis. The pandemic was managed through swift response by the top political leadership, research and innovations across Africa providing possible solutions to COVID-19 challenges, and redirection of funds to manage the pandemic. The well-coordinated COVID-19 containment strategy under the African Centers for Disease Control and Prevention increased sharing of resources including data was a success in limiting the spread of the virus. These strategies, among others, proved effective in limiting the spread and impact of COVID-19. The findings provide lessons that stakeholders and policy-makers can leverage in the management of the environment and address climate change. These approaches require solid commitment and practical-oriented leadership. Supplementary Information: The online version contains supplementary material available at 10.1007/s10668-023-02956-0.

Combining stable isotope and WQI methods to study the groundwater quality: a case study in Essaouira city, Morocco.

Groundwater is an important water resource in arid and semi-arid regions. Therefore, this study aimed to assess groundwater's suitability for drinking and irrigation using the Water Quality Index (WQI) and the Irrigation Water Quality Index (IWQI). To this end, groundwater data were collected from 58 sites in 2019 (wet season) and 61 samples in 2020 (dry season) in the Meskala-Ouazzi sub-basin. The Piper diagram showed that Ca-Mg-Cl was the dominant groundwater facies type. The confinement due to COVID-19 has significantly improved the water quality of the Meskala-Ouazzi sub-basin. Instead, approximately 50% of sites showed improved water quality when calculating the WQI and IWQI. However, the sodium adsorption ratio (SAR) showed that most samples below 10 are found in all of the examined samples, which are mostly found, indicating excellent irrigation water, and the Wilcox diagram depicted 20.14% of samples lying in the unsuitable region. Stable isotopes (δ18O and δ2H) of groundwater reveal that local precipitation is the main source of recharge. However, groundwater recharge is affected by the evaporation process due to the different geological conditions caused by topographic differences in the study area. The present study is useful for proper planning and managing water resources available for consumption and irrigation.

Identifying gaps in actual and simulated/potential yield and growing season precipitation in Morocco.

The influence of growing season rainfall on agricultural production is indisputable. In Morocco, the production of crops such as barley, maize, and wheat is impacted by growing season rainfall. Due to persistent gaps in growing season rainfall and other drivers of crop yield, crops have experienced observed yields that are often below projected or potential yields. However, there are currently no studies that have quantified these gaps in yield and growing season rainfall in Morocco. To achieve this objective, time-series crop yield for all three crops and growing season rainfall data for the period 1991-2020 were collected from FAOSTAT and the World Bank climate portal, respectively. Growing season rainfall and crop yield data for the spatial variations were culled from System National de Suivi Agrometeorologique (GCMS) and the yield gaps atlas, respectively, for the same historical period. The data were subjected to bias correction to handle uncertainty. The projected/simulated crop yields and growing season rainfall were computed by regression analysis. Crop yield and growing season rainfall gaps were determined by establishing the difference between the projected and observed crop yields and rainfall data. The results show that observed and simulated wheat have a stronger relationship when compared to the other crops. Also, most years with crop yield gaps are associated with growing season rainfall gaps. Wheat records the lowest number of years with yield gaps and the highest number of years with growing season rainfall gaps during the entire data series. Therefore, even though yield gaps are strongly tied to growing season rainfall gaps, it is not the case for wheat, and therefore other drivers might be important because wheat has the lowest number of years with crop yield gaps and the highest number of years with growing season rainfall gaps. Spatially, yield and growing season rainfall gaps decline with increased latitude. The broader perspective and policy implication here is that a better understanding of yield and growing season rainfall gaps mandates an understanding of growing season rainfall and other drivers of yield. As a way forward, potential research should focus on identifying the drivers of yield gaps, sub-national experimentation at the plot level as well as on closing yield gaps through water and nutrient management.

A new index on agricultural land greenhouse gas emissions in Africa.

Africa emits the lowest amounts of greenhouse gases (GHGs) into the global GHG budget. However, the continent remains the most vulnerable continent to the effects of climate change. The agricultural sector in Africa is among the most vulnerable sectors to climate change. Also, as a dominant agricultural sector, African agriculture is increasingly contributing to climate change through GHG emissions. Research has so far focused on the effects of GHG emissions on the agricultural and other sectors with very little emphasis on monitoring and quantifying the spatial distribution of GHG emissions from agricultural land in Africa. This study develops a new index: African Agricultural Land Greenhouse Gas Index (AALGGI) that uses scores and specific scale ranges for carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) to map the spatial variations in regional GHG emissions across Africa. The data for the three main GHGs (CO2, CH4, and N20) were downloaded from FAOSTAT. The data were analyzed through the newly developed African Agricultural Land Greenhouse Gas Index (AALGGI). This is an empirical index with scores ranging from 0 to 10, with higher scores indicating higher levels of emissions. The results show that Southern and North African regions have the lowest amounts of agricultural land GHG emissions, with AALGGIs of 3.5 and 4.5, respectively. East Africa records the highest levels of GHG emissions, with an AALGGI of 8 followed by West Africa with an AALGGI of 7.5. With the continental mean or baseline AALGGI being 5.8, East and Middle Africa are above the mean AALGGI. These results underscore the fact that though Africa, in general, is not a heavy emitter of GHGs, African agricultural lands are increasingly emitting more GHGs into the global GHG budget. The low AALGGIs in the more developed parts of Africa such as Southern and North Africa are explained by their domination in other GHG emitting sectors such as industrialization and energy. The high rates of emissions in East Africa and Middle Africa are mainly linked to intensive traditional farming practices/processes and deforestation. These findings underscore the need to further leverage climate change mitigation actions and policy in Africa and most importantly the co-benefits of mitigation and adaptations in the most vulnerable regions.

Projected changes in meteorological drought over East Africa inferred from bias-adjusted CMIP6 models.

The ongoing global warming has caused unprecedented changes in the climate system, leading to an increase in the intensity and frequency of weather and climate extremes. This study uses the sixth phase of Coupled Model Intercomparison Project (CMIP6) data to investigate projected changes in drought events over East Africa (EA) under four Shared Socioeconomic Pathway (SSP) emission scenarios (SSP1-2.6, SSP2-4.5, SSP3-4.0, and SSP5-8.5). The CMIP6 data are bias-corrected using a quantile mapping method, with the Climatic Research Unit's precipitation dataset as reference. Drought is quantified using the standardized precipitation index and different measures of drought are estimated: drought duration, drought frequency, drought severity, and drought intensity. Evaluating the accuracy and reliability of historical data before and after bias correction demonstrates the importance of the approach. The overall distribution after bias correction depicts a close agreement with observation. Moreover, the multi-model ensemble mean demonstrate superiority over individual Global Circulation Models. Projected future changes show enhancement in precipitation over most parts of EA in the far future under different SSP scenarios. However, the arid and semi-arid regions are expected to receive less amount of precipitation, whereas the highlands and lake regions are expected to receive a larger amount of precipitation increase. Furthermore, the dry areas of EA are likely to experience more frequent drought events with longer duration, stronger intensity, and severity in the far future. Overall, this study identifies possible drought hotspots over EA, enabling early preparation for such events. Supplementary Information: The online version contains supplementary material available at 10.1007/s11069-022-05341-8.

Multi-decadal analysis of water resources and agricultural change in a Mediterranean semiarid irrigated piedmont under water scarcity and human interaction.

Mediterranean piedmonts are an important hydro-agricultural systems. They constitute the junction between the mountains, where the streamflow is generated, and the surrounding plains, where the water is used. In Morocco, these traditional systems extend largely along the High Atlas Mountains. Yet, changing conditions in the Mediterranean basin as well as recurrent droughts in recent decades remain poorly understood in terms of hydrological and agricultural impacts, particularly in traditional hydro-agro-systems. The combined effects of climate variability and ineffective management of water resource dynamics may lead to increased water scarcity in these regions. The present work aims to assess the effects of climate variability and associated agricultural changes on water resources in a traditional irrigated piedmont of the Moroccan High Atlas. To that end, a trend analysis, together with change points detection, was carried out on annual and monthly precipitation, and streamflow from 1965 to 2018. Then, the standardized precipitation index (SPI) was employed to identify meteorological droughts. Also, groundwater, and spring discharge data were analyzed and discussed from 1973 to 2021. SPI outcomes revealed three major droughts, in 1981-1988, 1999-2008, and 2013-2018. Although the precipitation data showed no significant trend, except for Tahannaout station, the average annual precipitation over the piedmont area decreased by 28%. Similarly, streamflow decreased significantly by almost 40% for all stations, as did the Abainou spring's discharge. Consistent with that, groundwater level has declined dramatically over the past decades in the downstream piedmont. These decreases in water cycle components were tightly aligned with droughts. Yet, irrigation diversions were maintained in both dry and wet periods. Paradoxically, this decrease in water resources was associated with an agricultural transition from seasonal crops (cereals) to perennial crops (olive trees). This conversion is likely to amplify the water shortage, leading to groundwater resources overexploitation to satisfy the growing agricultural demand.

Temporal and spatial assessment of groundwater contamination with nitrate using nitrate pollution index (NPI), groundwater pollution index (GPI), and GIS (case study: Essaouira basin, Morocco).

Groundwater aquifers in Morocco's coastal regions are under serious threat as a result of climate change. This study was conducted to evaluate and map the quality of water resources, by evaluating the level of pollution of the groundwater in the Meskala-Ouazzi sub-basin, a coastal area of Essaouira based on the physico-chemical analysis of 58 samples using a geographic information system (GIS) technique, analytical analysis, nitrate pollution index (NPI), and groundwater pollution index (GPI). The diagram piper of the study area is dominated by Cl-Ca-Mg, Cl-Na, HCO3-Ca-Mg, and SO4-Ca types. The concentrations of nitrate ranged from 2 to 175 mg/L. It was discovered that 22% of the groundwater samples had nitrate amounts greater than the World Health Organization's recommended maximum allowable level of 50 mg/L. The NPI ranged between - 0.9 and 7.8. According to the classification of NPI, 44.8% of the total groundwater samples represent clean water, indicating that the groundwater in the study area is suitable for irrigation. GPI values ranging from 0.6 to 3.7, with an average of 1.7, identifies 37.9% of all groundwater samples as low polluted. The inverse distance weighting (IDW) approach was used to generate a spatial distribution map, which indicates that appropriate groundwater is present in the sub-upstream basin's part. Overall, the forte concentration in groundwater samples detected in western and central areas showed that the nitrate originated from large amounts of nitrogen fertilizer used by humans in agricultural activities during periods of irrigation. The low tritium (δ3H) content shows that the aquifer recharge is stale water and excessive use of fertilizers leads to groundwater pollution faster over time.

Morocco's coastal aquifers: Recent observations, evolution and perspectives towards sustainability.

During the last decades, the coastal areas of Morocco have witnessed an intense socioeconomic development associated with a continuous population growth and urban extension. This has led to an overexploitation of coastal aquifers leading to a degradation of their water quality. In order to obtain large scale overview on the quality status of Morocco's coastal aquifers (MCA) to assist national water managers to make informed decisions, a comprehensive scrutinization of the MCA against common indicators and using unified methods is essential. In this study, databases from thirteen MCA were analyzed, using multivariate statistical approaches and graphical methods in order to investigate the degree of mineralization in each aquifer and to identify the main salinization processes prevailing in groundwater. The results showed that the dominant groundwater types are Na-Cl, Ca-Mg-Cl, Ca-Mg-SO4, Ca-Mg-HCO3 and Ca-HCO3-Cl. The Gibbs diagram and the seawater contribution (0-37%) indicate that the mineralization is mainly due to the seawater intrusion and water-rock interaction. The salinity degree diagram illustrates that almost all groundwater samples are located in the moderate to very saline zone, indicating that MCA are recharged by water from variable sources. The groundwater quality assessment shows a deterioration, particularly by seawater intrusion and significant nitrate pollution. The temporal evolution confirm that the MCA are influenced by seawater namely in the Atlantic part. The Wilcox and USSL diagram indicate that the majority of sampled water are unsuitable for irrigation uses. In addition, and by referring to the WHO and the Moroccan standards for water potability, large number of samples from the groundwaters of the MCA is not fully adequate for drinking purposes. A set of management actions (e,g., artificial recharge) are proposed in order to mitigate the effect of groundwater overexploitation and seawater intrusion to ensure the sustainability of MCA.

Vulnerability of maize, millet, and rice yields to growing season precipitation and socio-economic proxies in Cameroon.

In sub-Saharan Africa growing season precipitation is affected by climate change. Due to this, in Cameroon, it is uncertain how some crops are vulnerable to growing season precipitation. Here, an assessment of the vulnerability of maize, millet, and rice to growing season precipitation is carried out at a national scale and validated at four sub-national scales/sites. The data collected were historical yield, precipitation, and adaptive capacity data for the period 1961-2019 for the national scale analysis and 1991-2016 for the sub-national scale analysis. The crop yield data were collected for maize, millet, and rice from FAOSTAT and the global yield gap atlas to assess the sensitivity both nationally and sub-nationally. Historical data on mean crop growing season and mean annul precipitation were collected from a collaborative database of UNDP/Oxford University and the climate portal of the World Bank to assess the exposure both nationally and sub-nationally. To assess adaptive capacity, literacy, and poverty rate proxies for both the national and regional scales were collected from KNOEMA and the African Development Bank. These data were analyzed using a vulnerability index that is based on sensitivity, exposure, and adaptive capacity. The national scale results show that millet has the lowest vulnerability index while rice has the highest. An inverse relationship between vulnerability and adaptive capacity is observed. Rice has the lowest adaptive capacity and the highest vulnerability index. Sub-nationally, this work has shown that northern maize is the most vulnerable crop followed by western highland rice. This work underscores the fact that at different scales, crops are differentially vulnerable due to variations in precipitation, temperature, soils, access to farm inputs, exposure to crop pest and variations in literacy and poverty rates. Therefore, caution should be taken when transitioning from one scale to another to avoid generalization. Despite these differences, in the sub-national scale, western highland rice is observed as the second most vulnerable crop, an observation similar to the national scale observation.