The Arabian Gulf is a highly turbid, shallow sedimentary basin whose coastal areas have been classified as optically complex Case II waters (where ocean colour sensors have been proved to be unreliable). Yet, there is no such study assessing the performance and quality of satellite ocean-colour datasets in relation to ground truth data in the Gulf. Here, using a unique set of in situ Chlorophyll-a measurements (Chl-a; an index of phytoplankton biomass), collected from 24 locations in four transects in the central Gulf over six recent research cruises (2015–2016), we evaluated the performance of VIIRS and other merged satellite datasets, for the first time in the region. A highly significant relationship was found (r = 0.795, p < 0.001), though a clear overestimation in satellite-derived Chl-a concentrations is evident. Regardless of this constant overestimation, the remotely sensed Chl-a observations illustrated adequately the seasonal cycles. Due to the optically complex environment, the first optical depth was calculated to be on average 6–10 m depth, and thus the satellite signal is not capturing the deep chlorophyll maximum (DCM at ~25 m). Overall, the ocean colour sensors’ performance was comparable to other Case II waters in other regions, supporting the use of satellite ocean colour in the Gulf. Yet, the development of a regional-tuned algorithm is needed to account for the unique environmental conditions of the Gulf, and ultimately provide a better estimation of surface Chl-a in the region.

In the State of Qatar, recent statistics show a continued increase in the motor-vehicle fleet commensurate with population growth and economic development. This trend, together with the rapid expansion of urban areas and the increased dependence on automobiles, has resulted in an increase in pollution near traffic sources, indicating that the risk of exposure to vehicles’ emissions is higher and that these emissions must be considered in terms of their spatial and temporal occurrence. So far, there are no studies conducted in Qatar to evaluate the traffic-related air pollution. This study is carried out to monitor the levels of nitrogen dioxide (NO₂) as a marker of pollution related to traffic. The aim of this study is to build a baseline for traffic-related pollution in Qatar by monitoring and modelling NO₂ emissions. The levels of traffic-related air pollution by NO₂ were investigated at six major intersections along the C-ring road. The relationship of NO₂ was established with traffic volume in each intersection during December 2012 and March–April 2013. Significant differences were established between the pollutant concentrations in each intersection. The CALifornia LINE Source Dispersion Model, version 4 air dispersion model employed had estimated the influence of the measured NO₂ concentration on the predicted NO₂ values by 31.12%. The low percentage may have accounted for the uncertainties brought by the vehicle emission factor and non-availability of temporal dynamics during the time of sampling. Non-parametric Spearman’s correlation test resulted in a significant correlation between measured and predicted values of NO₂ concentrations, r_s = 0.525 and p = 0.012.

Globally, urbanization, industrialization, and transportation have worsened urban air quality in recent decades. Using sustainable, cost-effective methods to monitor and reduce air pollution is crucial. The best Nature-based Solution (NbS) for urban environmental cleanup is plants. Roadside plants are key carriers of air pollution and have various tolerances. Ziziphus spina-christi’s air pollution tolerance was assessed using the Air Pollution Tolerance Index (APTI). The Bioconcentration Factor (BCF) examined the heavy metal accumulation capacity of Ziziphus spina-Christi’s fruits and leaves. Two sampling sites were studied: a reference location remote from human activity and a densely populated metropolitan region. Ziziphus spina-christi is considered a tolerant species in Qatar, based on its calculated value of APTI in this study. Both total chlorophyll and ascorbic acid influence APTI levels and have a strong positive correlation with APTI. BCF values in leaves were higher than fruits indicating that the leaves of Ziziphus spina-christi have a greater potential for metal absorption than its fruits. Moreover, the leaves of Ziziphus spina-christi showed a potential for mercury accumulation (BCF > 1), thus it is a good candidate to be used for phytoremediation in areas of mercury contamination. The integration of both APTI and BCF methods is significant and beneficial in advising policymakers and urban planners regarding suitable tree species for sustainable urban development.