To support the fulfillment of Sweden’s targets in term of climate change and economic growth, we need to do a distinct study to show the Environmental Kuznets Curve (EKC) pattern in different sector of the economy, as the GDP allocation, energy intensities, GHG emission, and technological development are different between sectors. This kind of study helps to figure out how the different sectors contribute to climate change and could appoint more particular and effective environment-energy policies. For this aim, we analyzed the existence of the EKC by implementing the ARDL Bound test approach in the whole and individual sectors of Sweden’s economy throughout 1990-2019. Our results indicated the contribution of a particular sector on total GHG emissions per capita. Results of the whole economy confirmed the EEKC hypothesis with a turning point in 1996, in which the AFF sector, unlike industry and service, had increased GHG emissions. Disaggregated sectoral analysis showed various results. The industry sector had efficient energy improvement. Policymakers should pay attention to AFF’s GHG emissions, as different sources of energy consumption had not impressive impact in both the short and long term. Also, effective fossil-related policies are necessary for the service sector due to the main contribution to transportation.

In Mirzapur (U.P.), a power-starved district, the UASB (Upflow Anaerobic Sludge Blanket) technique was adopted. Almost all of the available technologies do not treat heavy metals, so, is the case with the UASB also. The present study is to assess how much heavy metal can get accumulated in plant tissues in different species. The result of the present study was that the concentration of Pb(1106.31)>Zn(221.45)>Cd(49.26)>Hg(23.37) mg/Kg in the sludge while the concentration of Zn(93.35)>Pb(52.00)>Hg(16.93)>Cd(1.53) mg/Kg in the soil. When the sludge was mixed with the soil the trend got changed and the trend was Pb(596.36)>Zn(219.86)>Cd(24.70)>Hg(22.63) mg/Kg. Three different species that were chosen for the study were Basella Alba (Spinach), Solanum Lycopersicum (Tomato) & Brassica Juncea (Mustard). The trend of accumulation of studied heavy metals in the Brassica Juncea (Mustard) was Zn(85.33)>Pb(25.88)>Hg(11.23)>Cd(0.99) mg/Kg. In Solanum lycopersicum (Tomato) the trend was Pb(231.11)>Zn(108.72)>Hg(12.43)>Cd(9.41) mg/Kg  and in Basella alba (Spinach) was Zn(103.81)>Pb(83.90)>Hg(10.78)>Cd(4.18) mg/Kg. Overall the study reveals that the accumulation of heavy metals takes place in plants grown in soil mixed with sewage sludge. The reduction in the concentration of Pb, Cd, Hg and Zn in sludge mixed with soil after the harvesting of plant in case of Solanum lycopersicum were 39.38%, 47.93%, 6.18% and 49.89% respectively; while in case of Basella alba these were 25.23%, 57.53%, 71.58% and 49.16% respectively; and in case of Brassica Juncea these reduction were 25.86%, 60.80%, 70.96% and 49.04% respectively.

The removal of toxic textile dye, Congo red (CR) an azo based textile dye, was investigated from aqueous solution by low cost, eco-friendly available adsorbents such as petiole part (stem) of water lily (Nymphaea alba) under various experimental conditions.Batch experiment was carried out at varying pH, dye concentration, contact time and particle size as well as doses of the adsorbent. CR was analyzed by a UV-visible spectrophotometer. Optimum pH was found at pH 2 and 6. A relative study was done using sodium chlorite and formaldehyde treated water lily. The maximum removal of CR was obtained 94.68% using untreated water lily (UT-WL). Adsorption increased with the increase of the particle size of the adsorbent. The highest removal of CR was found at a lower dose (62.5 g/g) of the adsorbent. The Freundlich isotherm model was best fitted to equilibrium data obtained from the experiment. The adsorption kinetics successfully fitted to the pseudo-second-order kinetic model.

Safe and clean water is essential for all living beings. Consumption of polluted water which is contaminated with iron may cause serious health implications. Therefore, removal of Fe3+ from wastewater is prerequisite for further uses. The present study intended to prepare activated charcoal (AC) from Borassus flabellifer male flower (BF) for the removal of Fe3+ ions from wastewater in a cost effective way. BFAC was produced based on carbonization method. Surface morphology and elemental composition were investigated by Scanning Electron Microscopy and Energy Dispersive X-Ray Spectroscopy. Additionally surface charge was determined by iodine number and zero point charge calculation. Batch adsorption studies were monitored using UV-visible spectroscopy. The obtain results showed a maximum adsorption at pH 8 with 0.3g adsorbent dosage at 50ppm initial Fe3+ ion concentration for 130 min contact time. The analysis of adsorption isotherm was in good agreement with both Langmuir and Freundlich adsorption isotherms. The Fe3+ removal method was found to be controlled by 1st order kinetics mechanism. However, the production cost was much cheaper and the removal performance was comparatively better than other commercial charcoals. Hence, BFAC could be used as a commercial charcoal in rural area of Bangladesh for purification of waste water.

Previous studies have shown that certain urban elements and arsenic are significantly concentrated in the surface soils of Hamedan, the largest city in western Iran. This study was carried out to assess the non-cancer and cancer risks ‎from exposure to these potentially harmful elements (As, Cd, Cr, Cu, Ni, Pb, and Zn) for Hamedan residence. In so doing, thirty-one urban and three background soil samples were analyzed by ICP-MS and the Risk Assessment Model established by the USEPA was applied to assess the health risk. It was found that the hazard index values for all the concerned ‎elements are below 1, which indicates negligible to low non-carcinogenic risk for the exposed population. Nevertheless, some close to threshold values were recognized for As, Cr, and Pb implying that these elements have the potential to cause non-cancer risk for Hamedan citizens in case of long-term overexposure. The contribution of HQ-ingestion to total HI was the highest while the health effect associated with the inhalation exposure was trivial. Children were found to be more susceptible to potentially harmful elements than adults. ‎The cancer risk calculation revealed that both children and adults are at increasing risk of developing ‎cancer over a lifetime through ingestion, inhalation, and skin contact. All of the verified elements exceeded the ‎tolerable level (1×10-6) of cancer risk however arsenic and chromium were found to be the most carcinogenic ‎elements followed by Pb, Ni, and Cd. The carcinogenic risks were moderate for adults and high for ‎children. This study indicates the necessity of designing effective strategies to reduce elemental ‎pollution and to mitigate adverse human health effects of PHEs in Hamedan.‎

Ozone(O3), and its precursors, Benzene (C6H6), Nitrogen Dioxide(NO2), Carbon Monoxide (CO) and meteorological parameters Temperature, Relative Humidity and Wind Speed were measured in urban air of two sites of significant spatial variations, Delhi Milk Scheme (DMS), Sadipur and Netaji Subhash Chander Institute of Technology(NSIT) Dwarka, during 2017–2018. Samples collected by Central Pollution Control Board (CPCB) has been analysed. The concentrations of Benzene, Nitrogen dioxide and Carbon monoxide were found to be more at DMS than NSIT site in winter season (11.137±3.258, 5.540±1.441, 55.333±12.741, 44.667±10.066μg/m3, 1.433±0.058, 1.033±0.287mg/m3 respectively) and summer season (3.167±1.222, 2.233±0.929, 50.333±2.082, 31.333±6.658μg/m3, 0.743±0.151, 0.443±0.051mg/m3 respectively) while Ozone was found to be more at NSIT than DMS site (40.333±3.215, 34.433±2.503μg/m3 respectively). The maximum concentrations of Benzene for the DMS and NSIT sites, respectively, were 32.4μg/m3 and 17.7μg/m3 and was observed in the month of November while minimum were 1.0μg/m3 and 0.6μg/m3 and was observed in the month of June. For Ozone, the maximum concentrations for the DMS and NSIT sites, respectively, were 100μg/m3 and 101μg/m3 and was observed in the month of June while minimum were 33.0μg/m3 and 28.0μg/m3 and was observed in the month of February and December respectively. Regression analyses were performed to correlate O3 concentrations with C6H6, NO2 and CO in order to infer their possible sources. The study reveals that there is significant correlation of O3 with C6H6 (r2=0.475) and CO (r2=0.985) in summer at DMS and with C6H6 (r2=0.902) & NO2(r2=0.728) in winter at NSIT. The correlation of O3, C6H6, NO2 and CO with Temperature, Relative Humidity and Wind Speed has also been investigated to understand their influence on these pollutants.

Air pollution is considered a global concern due to its impacts on human life and the urban environment. Therefore, precise modeling techniques are necessary to predict air quality in congested areas such as megacities. Recently, machine learning algorithms such as Neural Networks show significant possibilities in air quality studies. This paper proposes a model to estimate air quality in a congested urban area in Baghdad city using Artificial Neural Network (ANN) algorithm and Geospatial Information System (GIS) techniques. Carbon Monoxide (CO) gas is selected as the main air pollutant. The model parameters involve; CO samples, traffic flow, weather data, and land use information collected in the field. The proposed model is implemented in Matlab environment and the results are processed after entering ArcGIS software. Using its spatial analysis tools, the outputs are presented as a map. The final findings indicate the highest value of CO emissions that reached 34 ppm during the daytime. The most polluted areas are located near congested roads and industrial locations in comparison with residential areas. The proposed model is validated by using actual values that are collected from the field, where the model's accuracy is 79%. The proposed model showed feasibility and applicability in a congested urban area due to the integration between the machine learning algorithm and GIS modeling. Therefore, the proposed model in this research can be used as a supportive model for decision making of city managers.

Though, the attention of researchers on exploring the impact of economic policy uncertainty on carbon emissions is on increase, however, the impact of different types of economic policy uncertainty remains unexplored. Thus, this study investigates the impact of different types of economic policy uncertainty on carbon emissions in Japan. A monthly data from 1987M1 to 2019M12 was used, while the FMOLS, DOLS, CCR and ARDL estimators were employed for examining the cointegration among the variables, as well as the long- and short-run relationship between types of economic policy uncertainty and carbon emissions. The study findings revealed a long-run cointegration among energy consumption, per capita income, fiscal, exchange rate, monetary, and trade policy uncertainties and carbon emissions. Moreover, this study found energy consumption, exchange rate, monetary, and trade policy uncertainties to contribute significantly to the increase of carbon emissions in Japan. Finally, this study suggests that environmental policy makers in Japan should take into account the economic policy uncertainty so as to promote robust information for climate policy that will be targeted at ameliorating the carbon emissions in Japan.

Produced water is a large amount of water wasted throughout the crude oil extraction process, it's a mixture of the well's deposition water and the water of oil wells extraction water. Produced water contains oil, suspended solids and dissolves solid. This study tested produced water collected from Alahdab oilfield/middle oil company for oil content and suspended solid contamination using chemical precipitation and coagulation-flocculation for reinjection and environmental considerations. Coagulation/flocculation is a common method used as primary purification to oily wastewater treatment due to its usability, performance, and low cost. Coagulant experimental was completed by A jar test device, additives of ferric sulfate and aluminium sulfate were in a range about (10 ـ 40) ppm, as well as polyelectrolyte- (polyacrylamide) as an additional flocculent in the range (1.5-3) ppm. The results show that ferric sulfate was more efficient at removing turbidity than aluminium sulfate under the same conditions, with the best removal of turbidity at dose concentration 30 ppm of Ferric sulfate and a flocculent dose concentration of 2.5 ppm of polyacrylamide, also with oil content decreasing from 396.71 ppm to 53.56 ppm.

In this study, the adsorptive removal of two dyes (crystal violet (CV) and methylene blue (MB)) with HNO3 pre-treated water hyacinth powder (WHP) adsorbent was analysed. The experiments were designed using response surface methodology (RSM) with variable input parameter pH (2-12), adsorbent dose (0.5-3 g/L), initial dyes concentration (25-200 mg/L) and time (10-180 min). The optimization condition for dye removal were (pH = 7.22, adsorbent dose = 3.0 g/L, initial dye concentration = 195.28 mg/L and time of contact = 99.29 min) for CV with removal of 98.20% and (pH = 9.82, adsorbent dose = 2.96 g/L, initial dye concentration = 199.36 mg/L and contact time = 111.74 min) for MB with removal of 97.843%. The above findings observed that pre-treated water hyacinth powder can be utilised as a cost-effective and efficient adsorbent for dye effluent wastewater treatment.