The Southeastern Anatolia Region (SEAR), the third-lowest mean annual precipitation region in Turkey, has semi-arid climate and plateau characteristics. The proximity of the region to North Africa and the Middle East dust source areas enables long-range transport of desert dust particles toward the SEAR by strong winds. Among the other dust source regions, the Arabian Peninsula has a crucial role in terms of affecting the SEAR with a high-annual frequency and high dust concentration values. We investigated the atmospheric patterns of three extreme Arabian dust episodes that affect the SEAR in this study. Dust episodes were determined using present weather (SYNOP) codes of ten stations in the SEAR during the 2014–2019 period. The source regions were found using HYSPLIT backward trajectory analysis. In this study, we benefited from synoptic maps, in situ PM₁₀ observations, numerical simulations of the WRF-Chem model, and MODIS satellite images to analyze the extreme dust episodes. The results showed that the surface low pressure over the Persian Gulf and strong southerly winds at the 700-hPa level enabled the transport of dust particles from the surface to the mid-atmospheric levels. If the center of the upper-level ridge extended from Saudi Arabia to southern Turkey, the atmospheric blocking mechanism prevented the dispersion of dense dust particles from the SEAR to its surrounding, which caused the observation of high dust concentrations in the SEAR. In general, the WRF-Chem model outputs are in good agreement with ground-based PM₁₀ concentrations and MODIS true-color images in terms of temporal and spatial distributions of dust concentrations.

In recent years, green roofs have become the subject of increasing interest because of their good aesthetic qualities, energy conservation, and ability to reduce thermal island effect and absorb greenhouse gases, especially carbon dioxide (CO₂). Given the typically significant carbon emission of construction activities, adding any extra component to a structure increases the amount of carbon to be released during the execution stage. This also applies to green roofs, which require more materials and more extensive construction activities than traditional roofs. However, plants of green roofs absorb substantial amounts of CO₂ during their lifetime, thus leaving both short- and long-term positive impacts on the building’s carbon footprint. This study investigated the short- and long-term effects of green roofs on carbon footprint, as compared to conventional roofs. For this investigation, the CO₂ uptake of eight plant species with suitable drought- and cold-resistant properties was measured by infrared gas analysis (IRGA), and the effect of green roof on the building’s carbon footprint was analyzed using the software Design Builder. The results showed that building a green roof instead of a traditional roof increases the carbon emission of the construction process by 4.6 kg/m² of roof area. Investigations showed that, under high light intensities (1500–2000 μmol/m² s), Sedum acre L. has the best performance in compensating the extra carbon emission imposed on the construction process (in 264 days only). Under low light intensities (1000–1500 μmol/m² s), Frankenia laevis showed the best increase in the amount of carbon uptake (2.27 kg/m² year).

E-waste generation has become a serious environmental challenge worldwide. Taizhou of Zhejiang Province, situated on the southeast coastline of China, has been one of the major e-waste dismantling areas in China for the last 40 years. In this review, we focused on the polychlorinated biphenyl (PCB) trends in environmental compartments, burden and impact to humans, food safety, and health risk assessment from Taizhou, China. The review suggested that PCBs showed dynamic trends in air, soil, water, biodiversity, and sediments. Soils and fish samples indicated higher levels of PCBs than sediments, air, water, and food items. PCB levels decreased in soils with the passage of time. Agriculture soils near the e-waste recycling sites showed more levels of total PCBs than industrial soils and urban soils. Dioxin-like PCB levels were higher in humans near Taizhou, suggesting that e-waste pollution could influence humans. Compared with large-scale plants, simple household workshops contributed more pollution of PCBs to the environment. Pollution index, hazard quotient, and daily intake were higher for PCBs, suggesting Taizhou should be given priority to manage the e-waste pollution. The elevated body burden may have health implications for the next generation. The areas with stricter control measures, strengthened laws and regulations, and more environmentally friendly techniques indicated reduced levels of PCBs. For environment protection and health safety, proper e-waste dismantling techniques, environmentally sound management, awareness, and regular monitoring are very important.

In this paper, magnetic MnFe₂O₄/mSiO₂ nanocomposites were successfully synthesized, and the activation performance of the materials for persulfate was evaluated by the degradation efficiency of perfluorooctanoic acid. The structure of the catalyst was proved to be a core–shell structure by several characterization methods. The mesoporous silicon coating can effectively avoid the agglomeration of MnFe₂O₄ and at the same time increase the contact area with the reactants. A comparison of different catalyst addition conditions demonstrates that MnFe₂O₄/mSiO₂ can effectively activate the persulfate. The optimal reaction conditions were investigated by several key influencing factors. It was experimentally demonstrated that about 90% of PFOA (10 mg·L⁻¹) could be decomposed under the conditions of 0.4 g·L⁻¹ MnFe₂O₄/mSiO₂ and PS, pH 5.68, and 25 °C within 4 h; the defluorination rate reached 58.33%. In addition, the cyclability and stability tests demonstrated that MnFe₂O₄/mSiO₂ is a stable material that can be recycled. Furthermore, XPS characterization and radical scavenging experiments demonstrated that sulfate radicals (SO₄·⁻) and hydroxyl radicals (OH) play a major role in the reaction of MnFe₂O₄/mSiO₂ activated PS. Subsequently, the degradation products were detected by high-performance liquid chromatography tandem triple quadrupole mass spectrometry, indicating that the degradation of PFOA is a gradual process of defluorination and decarbonization in the presence of free radicals. Finally, the metal leaching rate is tested to prove that the material meets environmental requirements while reacting efficiently. In conclusion, this study shows that MnFe₂O₄/mSiO₂ is an easily recoverable and highly efficient and stable material that has great potential for PS activation to treat organic pollutants in water.

Climate change and tourism’s interaction and vulnerability have been among the most hotly debated topics recently. In this context, the study focuses on how CO₂ emissions, the primary cause of global warming and climate change, respond to changes in tourism development. In order to do so, the impact of tourism development on CO₂ emissions in the most visited countries is investigated. A panel data from 2000 to 2017 for top 70 tourist countries are analysed using a spatial econometric method to investigate the spatial effect of tourism on environmental pollution. The direct, indirect, and overall impact of tourism on CO₂ emissions are estimated using the most appropriate generalized nested spatial econometric (GNS) method. The findings reveal that tourism has a positive direct effect and a negative indirect effect; both are significant at the 1% level. The negative indirect effect of tourism is greater than its direct positive effect, implying an overall significantly negative impact. Further, the outcome of financial development and CO₂ emissions have an inverted U-shaped and U-shaped relationship in direct and indirect impacts. Population density, trade openness, and economic growth significantly influence environmental pollution. In addition, education expenditure and infrastructure play a significant moderating role among tourism and environmental pollution. The results have important policy implications as they establish an inverted-U-shaped relationship among tourism and CO₂ emissions and indicate that while a country’s emissions initially rise with the tourism industry’s growth, it begins declining after a limit.

The influence of lightweight expanded clay aggregate (LECA) on the physico-mechanical properties and microstructure of geopolymer mortar containing slag binder alkali-activated with sodium silicate solution before and after exposure to thermal loads was investigated. In the current procedure, siliceous sand was partially substituted with LECA fine aggregate at levels of 0%, 25%, 50%, 75%, and 100%, by volume. The effect of LECA on the performance before exposure was evaluated by measuring flowability, water absorption, bulk density, thermal conductivity, and compressive strength. To monitor the behavior after exposure, a batch of specimens having the same composition was subjected to high temperatures in the range of 400–1000 °C for 2 h with a heating rate of 5 °C/min. In a similar fashion, mass loss and residual compressive strength were determined. New phase-based geopolymers were examined using Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). The findings indicated that the incorporation of LECA up to 100% as an alternative to siliceous sand aggregate in geopolymer mortar has an adverse effect on compressive strength and water absorption, but has a positive effect on workability, thermal conductivity, and relative strength after exposure to elevated temperatures.

Despite the considerable contributions of remittances to households and economic advancements, their environmental implications have received little attention in empirical research. This study was, therefore, conducted to help fill that gap, using Ghana as an evidence. In achieving the above goal, robust econometric methods that control for endogeneity, heteroscedasticity and serial correlation among others, were engaged for the analysis. From the results, the studied variables were first-differenced stationary and cointegrated in the long run. The elasticities of the predictors were explored via the FMOLS, DOLS and CCR estimators, and from the results, remittance inflows worsened the ecological quality in Ghana through high CO₂ emissions. Also, population growth and energy utilization were not friendly to the country’s environment; however, technological innovations improved environmental quality in the nation via low CO₂ effusions. The VECM was employed to examine the path of causalities amidst the series, and from the results, there were bidirectional causalities between remittance inflows and CO₂ emissions and between population growth and CO₂ emanations. Also, a causation from energy utilization to CO₂ effluents was discovered; however, there was no causality between technological innovations and CO₂ exudates in the country. Based on the findings, it was recommended among others that, authorities should enact regulations to control the activities of polluting industries that are being financed by remittances. Also, households and individuals should minimize their use of remittances to finance carbon-intensive items, like automobiles and air-conditioners among others, that add to environmental pollution in the country.

The foundation for many solar energy uses as well as economic and environmental concerns is global solar irradiation information. However, due to solar irradiation and measurement variations, reliable worldwide statistics on solar irradiation are frequently impossible or challenging to acquire. In addition, more precise forecasts of solar irradiation play an increasingly important role in electric energy planning and management due to integrating photovoltaic solar systems into power networks. Hence, this paper proposes a new hybrid model for 1-h ahead solar irradiation forecasting called LGC-GMDH (local gravitational clustering-group method of data handling). The novel LGC-GMDH model is based on local clustering that adequately captures the underlying features of the solar irradiation time series. Each cluster is then forecasted using the GMDH method, which is a self-organized system capable of handling very complicated nonlinear problems. Finally, these local forecasts are reconstructed in order to obtain the global forecast. Comparative study between the proposed model and the traditional individual models such as backpropagation neural network (BP), supporting vector machines (SVM), long short-term memory (LTSM), and hybrid models such as BP-MLP, RNN-MLP, LSTM-MLP hybrid wavelet packet decomposition (WPD), convolutional neural network (CNN) with LSTM-MLP, and ANFIS clustering shows that the proposed model overcomes conventional model deficiencies and achieves more precise predicting outcome.

Environmental pollution is becoming more and more prevalent in China, accompanied by the excessive expansion of the country’s foreign direct investment in the scale of resource-based industries. This article uses the panel data of 276 prefecture-level cities in China from 2003 to 2016 to estimate the impact of environmental regulation on foreign direct investment by employing the spatial Durbin model. The empirical results show that firstly, environmental regulation, and foreign direct investment have an obvious spatial correlation. Secondly, environmental regulation significantly inhibits foreign direct investment and has significant negative space spillover. Thirdly, non-eastern cities’ environmental regulation has significantly greater inhibitory effects on foreign direct investment than eastern cities, and the key cities’ environmental regulation has greater inhibitory effects than ordinary cities. Finally, from the perspective of industrial upgrading and resource configuration and environmental regulation has significantly promoted foreign direct investment and has significant negative space spillovers. Therefore, the reasonable use of environmental regulatory measures through industrial upgrading and resource configuration to attract clean, capital-intensive, and technology-intensive enterprises and to achieve the effect of “decontamination and clean” for foreign-funded enterprises is critical.

This paper seeks to explore the potential function of technological innovation and clean power in mitigating the ecological footprint in the N-11 nations during the phase 1992–2015 by applying panel cointegration analysis. The outcomes of the panel cointegration test signify the occurrence of a long-run relation among the clean energy (CE) variable, the ecological footprint (EF) variable, the per capita GDP (Y) variable, the financial development (FIN) variable, and technological innovation (TI) variable. The outcomes of the VECM signify a long-run causal relation from the ecological footprint (EF) variable to the clean energy (CE) variable, the GDP per capita (Y) variable, and technological innovation (TI) variable. This implies that the environmental degradation faced by the N-11 countries leads to shifting toward clean energy sources and technological innovation in the long run. Thus, the N-11 countries are in need to design policies that enhance shifting toward environmentally friendly energy sources.