This study presents a deep investigation of the physicochemical, mineralogical, textural, and thermal characteristics of an industrial kiln-treated red mud (KRM) sample, obtained from the Pavlodar Aluminum Plant, Kazakhstan. Along with the comprehensive suite of analytical techniques, market value analysis of KRM in the context of critical metals has been elucidated. According to the results obtained, KRM is primarily dominated by SiO2, Al2O3, and Fe2O3, while minor and trace concentrations of critical raw materials such as Sc, Nd, Pr, Dy, and other rare earth metals (REMs) were also present. Textural analysis reveals predominantly mesoporous structures with low specific surface areas and negligible microporosity. In addition, a screening-level contained-value assessment based on measured elemental concentrations and contemporary market prices indicates that the theoretical economic contribution of red mud is controlled by a limited number of high-value critical metals rather than by its bulk oxide constituents. These results demonstrate that both source characteristics and thermal conditioning exert a strong influence on red mud properties and resource potential. The findings support the view that red mud, despite being dominated by low-value bulk phases, warrants consideration as a secondary source of selected critical metals and provides a materials-based foundation for subsequent process optimization and techno-economic assessment within circular economy strategies.

Understanding the composition of carbonaceous aerosols, black carbon (BC) and organic aerosols (OA), remains a major challenge in atmospheric science. Using data from two aircraft campaigns with identical instrumentation over Europe and East Asia, we analyze statistical relationships between concentrations of five trace gases (CO, NO2, HCHO, O3, and SO2) with BC and OA in order to estimate carbonaceous aerosol in urban pollution plumes. We show that across both campaigns, CO is the best proxy for BC (R2 approximate to 0.6). In plumes, OA shows statistical links with NO2, O3, and CO, reflecting the combined influence of emissions, and secondary organic aerosol formation. Linear regressions based on trace gases remain limited, especially for OA, whereas the use of nonlinear machine-learning regression improves the quantification of BC and OA (R2 approximate to 0.9 for BC, R2 approximate to 0.7 for OA). However, the number of flights is limited, the results should not be interpreted as applicable to flights in other regions and seasons. Our findings indicate that co-emitted and co-produced trace gases contain information for quantifying carbonaceous aerosol in urban pollution plumes. This potential is more robust for BC, whereas OA remains more complex to estimate because it depends on multiple predictors.

India experiences severe air pollution driven by human activities. The role of anthropogenic chlorine is significant yet underexplored, with its mechanisms poorly understood and impacts largely unquantified, despite its importance in atmospheric oxidation and secondary pollutant formation. Using the GEOS-Chem chemical transport model, we quantify the impact of human-derived chlorine emissions on particulate chloride (pCl−), particulate matter (PM2.5), ClNO2, and O3 in the boundary layer over India. Comprehensive model simulations reveal major chlorine hotspots affecting nearly ~ 700 million people across the Indo-Gangetic Plain (IGP). The PM2.5 concentration increases due to pCl− formation (principally NH4Cl). Annual mean pCl− and ClNO2 increase by 4-fold and 3-fold, respectively. Regionally and seasonally, enhancements range from 0.04 − 3.6 μg m−3 for pCl−, 7-273 ppt for ClNO2, and -0.47-0.44 ppb for O3 with strongest effects in autumn and winter. Compared to other polluted hotspots in the world, for example China, O3 showed a lower sensitivity to chlorine emissions over India. Anthropogenic chlorine significantly influences India’s air quality, underscoring the need to include chlorine emission inventories and chemistry in models.

Because of their special characteristic and irreplaceable uses in the key industries of 4th industrial revolution, rare earth metals (REMs) are vital to the development of technology. Currently, the primary production and industrial extraction of REMs are concentrated in China, leading to a significant geopolitical and supply chain monopoly. The same also hinders the competitive advantages of several technological companies worldwide; concurrently, the REMs supply chain monopoly puts the USA and EU at confrontational socioeconomic challenges with China. The REMs are, on the one hand, critical for green engineering/clean technology and the fourth industrial revolution. This review explores the potential of red mud, a byproduct of the bauxite industry, as a secondary source of REMs. Red mud and other industrial wastes, such as spent batteries and coal byproducts, contain substantial amounts of REMs. Despite their significance, the valorisation of REMs from these secondary sources in general and from red mud in particular has not garnered widespread attention from policymakers and industrial stakeholders. This paper highlights the socio-economic and sustainability implications of REM extraction from red mud and emphasizes the need for greater awareness and investment in this area to mitigate supply chain criticality and promote a circular economy.

The Arctic is heating far more rapidly than the global mean, and clarifying the influence of aerosols in this intensification demands accurate and reliable observational records. The Arctic exhibits a distinct seasonal aerosol cycle, springtime "Arctic Haze" with elevated AOD and summertime "Clean Air" with low AOD. Thus, it is critical to evaluate how well various datasets capture this seasonality relative to ground-based observations. This study analyzes spring and summer AOD variability using CAMSRA and MERRA-2 reanalyses, MODIS Terra and Aqua satellite observations, AERONET measurements, AEROSNOW retrievals, and GEOS-Chem model simulations. Results show that satellite-derived and satellite-assimilated reanalyses are far from capturing the expected seasonal Arctic Haze and Clean Air pattern, except at Bonanza Creek and Yakutsk, where anthropogenic pollution alters it. The inability of reanalyses to capture Arctic aerosol seasonality likely stems from the assimilation of satellite retrievals influenced by cloud contamination and surface reflection from snow and ice, as well as inherent biases in the underlying models used to generate these datasets. In contrast, AERONET observations and GEOS-Chem simulations consistently capture Arctic Haze in spring, driven by long-range transport, and Clean Air in summer, associated with efficient wet removal of aerosols. CAMSRA further underestimates emissions from Arctic forest fires and inadequately represents long-range pollution transport. These findings suggest that independent model simulations align more closely with ground-based observations than satellite products or reanalyses, and that adjusting wet-scavenging parameters to fit such reanalyses may misrepresent aerosol processes and their contribution to Arctic warming. Incorporating advanced retrieval algorithms like AEROSNOW into reanalyses offers a pathway to reduce these biases and improve representation of Arctic aerosol seasonality.

Aerosols influence Earth's energy balance and hydrological cycle as cloud condensation nuclei (CCN), yet uncertainties persist in how anthropogenic emissions alter their abundance and climate-relevant properties. Abrupt, large-scale reductions in human activities provided a natural experiment to quantify anthropogenic impact on aerosol-cloud-climate interactions in coastal India. Combining chemical and microphysical measurements under drastically reduced and subsequently reintroduced emission scenarios, we reveal that CCN concentrations increased by 80-250% postlockdown. This surge coincided with increased new particle formation (NPF) event frequency and enhanced particle growth rates. Postlockdown air masses shifted from marine to continental sources, revealing that anthropogenic organic matter (OM), despite lower hygroscopicity, dominated particle growth to CCN-active sizes, offsetting hygroscopicity limitations. These findings demonstrate how shifts in anthropogenic activity can strongly impact aerosol-cloud interaction potential, even under varying air mass influences, and provide a reference for understanding the atmospheric effects of future air quality interventions.

Anthropogenic mercury emissions pose significant risks to both human health and ecosystems, particularly when transformed into methylmercury. India stands as the second-largest contributor to mercury emissions, estimated at 144.7 tonnes of Hg/year, with uncertainties ranging from 75 to 330 Mg/year 1. India ratified the Minamata Convention in 2018, committing to address and mitigate mercury pollution2. Knowledge of Indian specific characteristics of mercury emission sources is essential for implementing effective mitigation strategies. However, India currently lacks a national emission inventory, with only limited estimates available3. This research explores the impact of different anthropogenic emission inventories (AMAP/UNEP-2010, EDGAR, STREETS, AMAP/UNEP-2015) on mercury concentration and deposition patterns in India. We employ nested simulations of the chemical transport model GEOS-Chem over India for the year 2013-15. The current study also investigates the impact of grid resolution and meteorology on spatial distribution of Hg concentrations and deposition using MERRA-2 and GEOS-FP meterological datasets. Additionally, the study delves into the seasonal variations of Hg concentration and deposition across different regions of India, analysing their correlation with various meteorological parameters (such as rainfall). These findings are crucial for gaining insights into the dynamics of the mercury cycle in the environment. Furthur results will be presented. References: 1.AMAP/UNEP (2013) Technical background report for the global mercury assessment 2013. Arctic Monitoring and Assessment Programme/UNEP Chemicals Branch, Oslo/Geneva 2.UNEP. Parties and Signatories Minamata Convention on Mercury. https://www.mercuryconvention.org/en/parties (accessed 2024-01-09) 3.Sharma, B. M., Bharat, G. K., Šebková, K., & Scheringer, M. (2019). Implementation of the Minamata Convention to manage mercury pollution in India: challenges and opportunities. Environmental Sciences Europe, 31, 1-12.

The Arctic is currently warming rapidly, at a rate four times higher than the global average. This warming has significant consequences, leading to increased precipitation in the Arctic. Aerosols play a crucial role in cloud formation, cloud condensation nuclei (CCNs) and ice-nucleating particles (INPs), influencing rain and snowfall. However, uncertainties remain in the modelling of aerosols and their impact on precipitation due to a lack of high-resolution spatio-temporal observations. This is particularly the case in the central Arctic cryosphere due to the presence of extensive cold, bright snow and ice surfaces coupled with widespread cloud cover. This study addresses the observational data gap and provides an opportunity to refine model simulations at different spatio-temporal scales. We achieve this by using total aerosol optical depth (AOD) datasets generated by the AEROSNOW algorithm over the extensive central Arctic cryosphere. AEROSNOW retrieves AOD data using top-of-atmosphere reflectance measurements obtained through the Advanced Along-Track Scanning Radiometer (AATSR) aboard the ENVISAT satellite, spanning from 2003 to 2011. AEROSNOW integrates an aerosol retrieval algorithm with a rigorous cloud masking scheme and intro-duces a novel quality flagging methodology tailored for the central Arctic region (≥ 72°N). Using the AEROSNOW retrieved dataset for the central Arctic, we evaluate different models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Our results show significant differences in the spatio-temporal aerosol load and its annual and seasonal variations with precipitation. In particular, there is a decrease in aerosol loading that coincides with increased precipitation along the northern periphery of Alaska and the Bering Sea. Significant discrepancies and variations of up to 6.2 mm/day in precipitation are observed between models, with higher aerosol loading leading to lower precipitation and vice versa. Furthermore, the spatially averaged multi-model mean overestimates aerosol concentrations in spring and underestimates them in summer compared to satellite observations. The CMIP6 models do not reproduce the seasonal variations in aerosol distribution seen with AEROSNOW, particularly an increase in aerosol loading during the summer coinciding with the sea ice retreat cycle. These discrepancies may be due to the lack of advanced natural aerosol formation mechanisms in the models, as a consequence of Arctic warming, and exposure to openocean emissions. In summary, our study has led us to speculate that as model sophistication increases, modelled aerosol processes become increasingly uncertain. Ultimately, this investigation has the potential to elucidate the critical link between aerosols and the prevailing rain-dominated Arctic conditions under ongoing Arctic warming in future CMIP projects.

Abstract. The concentration of carbonaceous aerosols, black carbon (BC) and organic aerosol (OA), in the atmosphere is related to co-emitted or co-produced trace gases. In this study, we investigate the most relevant proportional relationships between both BC and OA with the following trace gases: carbon monoxide (CO), formaldehyde (HCHO), nitrogen dioxide (NO2), ozone (O3), and sulfur dioxide (SO2). One motivation for selecting these trace gases is that they can be observed using remote sensing measurements from satellite instrumentation, and could therefore be used to predict spatial changes in the amounts of BC and OA. Airborne measurements are optimal for the analysis of both the composition of aerosols and trace gases in different environments ranging from unpolluted oceanic air masses to those in heavily polluted city plumes. The two aircraft campaigns of the EMeRGe (Effect of Megacities on the Transport and Transformation of Pollutants on the Regional to Global Scales) project have created a unique database, with flight plans dedicated to studying city plumes in two regions, Europe (2017) and East Asia (2018), along with identical instrumental payload. Using linear regression analysis, three relevant relationships between carbonaceous aerosol and trace gases are identified: - The BC/OA ratio observed in the Asian campaign is three times higher (≈ 0.3) than in the European campaign (≈ 0.1), whereas the Pearson correlation coefficient (R) between BC and OA is much higher in Europe (R ≈ 0.8) than in Asia (R ≈ 0.6). - The CO/BC ratio is also observed higher in the Asian campaign (≈ 240) than in the European campaign (≈ 170), whereas the R-value between CO and BC is similar for both campaigns (R ≈ 0.7). - The HCHO/OA ratio is similar in both campaigns (≈0.32), but the observed R-values between HCHO and OA is higher in Europe than in the Asia (R ≈ 0.7 compared to ≈ 0.3). By focusing on heavily polluted air masses sampled downwind in the city plumes, the ratios between the observed carbonaceous aerosols and the five trace gases change, and the R-values increase with O3 for both BC and OA (R ≈ 0.5). To assess the performance of atmospheric models with respect to the most relevant observed relationships, an air quality model ensemble is used to represent the current state of atmospheric modeling, consisting of two global and two regional simulations. The evaluation shows that these proportional relationships are not satisfactorily reproduced by the model ensemble. The relationships between BC and OA or between CO and BC are modeled with stronger correlations than the observed ones, and their higher ratios observed in Asia compared to Europe are not reproduced. Furthermore, the modeled HCHO/OA ratio is underestimated in the Asian campaign and overestimated in the European campaign. This analysis of the proportional relationships between carbonaceous aerosols and trace gases implies that the observed relationships can be used to constrain models and improve anthropogenic emission inventories. In addition, it implies that information about the lower tropospheric concentration of carbonaceous aerosols can potentially be inferred from satellite retrievals of trace gases, particularly in the plumes from megacities.

Abstract. An air quality model ensemble is used to represent the current state-of-the-art in atmospheric modeling, composed of two global forecasts and two regional simulations. The model ensemble assessment focuses on both carbonaceous aerosols, i.e. black carbon (BC) and organic aerosol (OA), and five trace gases during two aircraft campaigns of the EMeRGe (Effect of Megacities on the Transport and Transformation of Pollutants on the Regional to Global Scales) project. These campaigns, designed with similar flight plans for Europe and Asia, along with identical instrumentation, provide a unique opportunity to evaluate air quality models with a specific focus on city plumes. The observed concentration ranges for all pollutants are reproduced by the ensemble in the various environments sampled during the EMeRGe campaigns. The evaluation of the air quality model ensemble reveals differences between the two campaigns, with carbon monoxide (CO) better reproduced in East Asia, while other studied pollutants exhibit a better agreement in Europe. These differences may be associated to the modeling of biomass burning pollution during the EMeRGe Asian campaign. However, the modeled CO generally demonstrates good agreement with observations with a correlation coefficient (R) of ≈ 0.8. For formaldehyde (HCHO), nitrogen dioxide (NO2), ozone (O3) and BC the agreement is moderate (with R ranging from 0.5 to 0.7), while for OA and SO2 the agreement is weak (with R ranging from 0.2 to 0.3). The modeled wind speed shows very good agreement (R ≈ 0.9). This supports the use of modeled pollutant transport to identify flight legs associated with pollution originating from major population centers targeted among different flight plans. City plumes are identified using a methodology based on numerical tracer experiments, where tracers are emitted from city centers. This approach robustly localizes the different city plumes in both time and space, even after traveling several hundred kilometers. Focusing on city plumes, the fractions of high concentration are overestimated for BC, OA, HCHO, and SO2, which degrades the performance of the ensemble. This assessment of air quality models with collocated airborne measurements provides a clear insight into the existing limitations in modeling the composition of carbonaceous aerosols and trace gases, especially in city plumes.

Mercury (Hg), a ubiquitous atmospheric trace metal posing serious health risks, originates from natural and anthropogenic sources. India, the world's second-largest Hg emitter and a signatory to the Minamata Convention, is committed to reducing these emissions. However, critical gaps exist in our understanding of the spatial and temporal distribution of Hg across the vast Indian subcontinent due to limited observational data. This study addresses this gap by employing the GEOS-Chem model with various emission inventories (UNEP2010, WHET, EDGAR, STREETS, and UNEP2015) to simulate Hg variability across the Asian domain, with a specific focus on India from 2013 to 2017. Model performance was evaluated using ground-based GMOS observations and available literature data. Emission inventory performance varied across different observational stations. Hence, we employed ensemble results from all inventories. The maximum relative bias for Total Gaseous Mercury (TGM) and Gaseous Elemental Mercury (GEM; Hg0) concentrations is about +/- 20%, indicating simulations with sufficient accuracy. Total Hg wet deposition fluxes are highest over the Western Ghats and the Himalayan foothills due to higher rainfall. During the monsoon, the Hg wet deposition flux is about 65.4% of the annual wet deposition flux. Moreover, westerly winds cause higher wet deposition in summer over Northern and Eastern India. Total Hg dry deposition flux accounts for 72-74% of total deposition over India. Hg0 dry deposition fluxes are higher over Eastern India, which correlates strongly with the leaf area index. Excluding Indian anthropogenic emissions from the model simulations resulted in a substantial decrease (21.9% and 33.5%) in wet and total Hg deposition fluxes, highlighting the dominant role of human activities in Hg pollution in India. Fragile ecosystems (Western Ghats and Himalayas), and major rice cultivation areas are vulnerable to highest Hg deposition. Indian anthropogenic emissions strongly influence deposition fluxes with varying regional impacts.

Air pollution caused by various anthropogenic activities and biomass burning continues to be a major problem in India. To assess the effectiveness of current air pollution mitigation measures, we used a 3D global chemical transport model to analyze the projected optical depth of carbonaceous aerosol (AOD) in India under representative concentration pathways (RCP) 4.5 and 8.5 over the period 2000-2100. Our results show a decrease in future emissions, leading to a decrease in modeled AOD under both RCPs after 2030. The RCP4.5 scenario shows a 48-65% decrease in AOD by the end of the century, with the Indo-Gangetic Plain (IGP) experiencing a maximum change of ~25% by 2030 compared to 2010. Conversely, RCP8.5 showed an increase in AOD of ~29% by 2050 and did not indicate a significant decrease by the end of the century. Our study also highlights that it is likely to take three decades for current policies to be effective for regions heavily polluted by exposure to carbonaceous aerosols, such as the IGP and eastern India. We emphasize the importance of assessing the effectiveness of current policies and highlight the need for continued efforts to address the problem of air pollution from carbonaceous aerosols, both from anthropogenic sources and biomass burning, in India.

The central Arctic cryosphere is influenced by the Arctic amplification (AA) and is warming faster than the lower latitudes. AA affects the formation, loss, and transport of aerosols. Efforts to assess the underlying processes determining aerosol variability are currently limited due to the lack of ground-based and space-borne aerosol observations with high spatial coverage in this region. This study addresses the observational gap by making use of total aerosol optical depth (AOD) datasets retrieved by the AEROSNOW algorithm over the vast cryospheric region of the central Arctic during Arctic spring and summer. GEOS-Chem (GC) simulations combined with AEROSNOW-retrieved data are used to investigate the processes controlling aerosol loading and distribution at different temporal and spatial scales. For the first time, an integrated study of AOD over the Arctic cryosphere during sunlight conditions was possible with the AEROSNOW retrieval and GC simulations. The results show that the spatial patterns observed by AEROSNOW differ from those simulated by GC. During spring, which is characterized by long-range transport of anthropogenic aerosols in the Arctic, GC underestimates the AOD in the vicinity of Alaska in comparison with AEROSNOW retrieval. At the same time, it overestimates the AOD along the Bering Strait, northern Europe, and the Siberian central Arctic sea-ice regions, with differences of −12.3 % and 21.7 %, respectively. By contrast, GC consistently underestimates AOD compared with AEROSNOW in summer, when transport from lower latitudes is insignificant and local natural processes are the dominant source of aerosol, especially north of 70° N. This underestimation is particularly pronounced over the central Arctic sea-ice region, where it is −10.6 %. Conversely, GC tends to overestimate AOD along the Siberian and Greenland marginal sea-ice zones by 19.5 % but underestimates AOD along the Canadian Archipelago by −9.3 %. The differences in summer AOD between AEROSNOW data products and GC-simulated AOD highlight the need to integrate improved knowledge of the summer aerosol process into existing models in order to constrain its effects on cloud condensation nuclei, on ice nucleating particles, and on the radiation budget over the central Arctic sea ice during the developing AA period.

Waste Electrical and Electronic Equipment is generated in large amounts annually and is continuously increasing in number owing to the growing global population and increasing standards of living. Liquid Crystal Display (LCD) waste is a secondary resource of precious and strategic metals, including indium (In). This study was conducted to maximize the solubilization of In from glass cullet recovered by crushing the LCD panel of a flat-panel display for industrial applications during leaching. In leaching tests, various factors (e.g., the type and acidity of the mineral acid, leaching temperature, pulp density, and oxidizing agent) were investigated to improve the In leaching efficiency. Finally, using the reuse method of a hydrochloric acid leaching solution, the LCD waste was leached seven times to concentrate the In at 646 ppm.

Currently, more than 55% of global indium production is consumed for indium tin oxide (ITO) production because of its excellent display properties mainly driven by demand for flat panel displays (FPDs) or LCDs. At the end of life, the waste LCD flows to the e-waste stream, accounts for 12.5% of the global e-waste, and is forecasted to be increasing progressively. These waste LCDs are potential wealth for indium that poses a threat to the environment. The volume of waste LCD generation is a global as well as national concern from a waste management perspective. Techno-economical recycling of this waste can be a panacea to the challenges associated with the lack of commercial technology and extensive research. Hence, a mass production capable of beneficiation and classification of ITO concentrate from waste LCD panels has been investigated. The mechanical beneficiation process for waste LCDs consists of five steps of operation, i.e., (i) size reduction by shredding by jaw milling, (ii) further size reduction to feed for ball milling, (iii) ball milling, (iv) classification to enrich ITO concentrate, and (v) characterization ITO concentrate and confirmation. The bench-scale process developed is intended to integrate with our indigenously developed dismantling plant (which can handle 5000 tons per annum) to handle separated waste LCD glass for indium recovery. Once scaled up, it can be integrated for continuous operation synchronized with the LCD dismantling plant.

The COVID lockdown presented an interesting opportunity to study the anthropogenic emissions from different sectors under relatively cleaner conditions in India. The complex interplays of power production, industry, and transport could be dissected due to the significantly reduced influence of the latter two emission sources. Here, based on measurements of cloud condensation nuclei (CCN) activity and chemical composition of atmospheric aerosols during the lockdown, we report an episodic event resulting from distinct meteorological conditions. This event was marked by rapid growth and high hygroscopicity of new aerosol particles formed in the SO 2 plume from a large coal-fired power plant in Southern India. These sulfate-rich particles had high CCN activity and number concentration, indicating high cloud-forming potential. Examining the sensitivity of CCN properties under relatively clean conditions provides important new clues to delineate the contributions of different anthropogenic emission sectors and further to understand their perturbations of past and future climate forcing.

Progressively and projected integration of rare earth metals (REMs) in modern technologies, especially in the clean energy, consumer electronics, aerospace, automotive, and defense sectors, place REMs as critical raw materials in the supply chain and strategic metal from the fourth industrial revolution perspective. Current REM production from the primary mineral resources in the supply chain versus industrial demand is at a bottleneck. Alternatively, REM-bearing anthropogenic wastes are pertinent and potent to addressing the critical supply chain bottleneck. Although secondary REM resources are prudent to address the critical supply chain bottleneck, the absence of effective and efficient technologies to recover these REMs from anthropogenic waste imposes challenges and provides opportunities. Hence, this review analyses and discusses the significance of anthropogenic wastes for REM recovery, the status of recycling technologies for sustainable valorization of REMs, challenges, and opportunities. The current review covers the potential quantitative REM wealth locked in various anthropogenic waste like (i) spent rare earth permanent magnets, (ii) spent batteries, (iii) spent tri-band REM phosphors, (iv) bauxite industry residue red mud, (v) blast furnace slag and (v) coal mines, and coal byproducts and status of valorization technologies for circularizing the REMs. In industrial waste like red mud, steelmaking slag, blast furnace slag, and coal fly ash typically 109,000, 2000, 39,000, and 354,000 tons of REM get scrapped, respectively, in a conservative estimation. In the years 2020 and 2021, respectively, 240,000 and 280,000 tons of REM were produced by mine production in contrast to 504,000 tons of REM that were scrapped with REM-bearing industrial waste. This review revealed that total REM currently getting scrapped with anthropogenic waste versus projected REM demand for the years 2022, 2023, 2024, and 2025 could be standing at 2.66, 2.51, 2.37, and 2.23, respectively. Our investigation revealed that efficient recovery of REMs from anthropogenic waste is significant and promising but associated with challenges like lack of industrial-scale valorization process, lack of a clear strategy, road map, policy, effort, funding, and diversified research.

This paper addresses the separation of platinum and palladium from the chloride solutions by liquid-liquid extraction using Alamine 308 as an extractant. The effect of different process parameters such as the concentrations of HCl, NaCl, platinum, and palladium in the aqueous solution, and the concentration of Alamine 308 in the organic phase, on the separation behavior, was evaluated. While selective stripping of platinum was achieved using NaSCN, palladium was selectively stripped with (NH2)(2)CS. The process can ensure the separation and recovery of both platinum and palladium with 99.99% purity from a mixed solution of platinum and palladium chlorides.