Land leveling is one of the most important steps in soil preparation and cultivation. Although land leveling with machines requires considerable amount of energy, it delivers a suitable surface slope with minimal soil deterioration as well as damage to plants and other organisms in the soil. Notwithstanding, in recent years researchers have tried to reduce fossil fuel consumption and its deleterious side effects, using new techniques such as Artificial Neural Networks (ANNs) and Adaptive Neuron-Fuzzy Inference System (Fuzzy shell-clustering algorithm) models that will lead to a noticeable improvement in the environment. The present research investigates the effects of various soil properties such as Embankment Volume, Soil Compressibility Factor, Specific Gravity, Moisture Content, Slope, Sand Percent, and Soil Swelling Index in energy consumption. The study consists of 90 samples, collected from three different regions. The grid size has been set on 20 m * 20 m from a farmland in Karaj Province, Iran. The aim is to determine the best linear model, using ANNs and ANFIS model to predict environmental indicatorsand find the best model for land leveling in terms of its output (i.e. Labor Energy, Fuel energy, Total Machinery Cost, and Total Machinery Energy). Results show that ANFIS can successfully predict labor energy, fuel energy, total machinery cost, and total machinery energy. All ANFIS-based models have R2 values above 0.995 and MSE values below 0.002 with higher accuracy in prediction, given their higher R2 value and lower RMSE value.

The first future challenge facing human beings is to supply the world's energy needs. However, energy consumption and resource depletion in industrial processes are significantly increasing. Therefore, life cycle assessment can be an excellent tool to quantify resources and energy consumption in different parts of industrial processes. The combination of process simulation and assessment of process life cycle can be resources & energy consumption in different parts is quantified and can be significantly reduced by optimizing the process, energy wastage. The process stimulation is done by HYSIS software, then by collecting output data, energy and materials flow, life cycle assessment is conducted using SIMAPRO software. According to output of the release list, 1709 items are released into the environment, of which 396, 407, 340 items are released into the air, water, soil, respectively and 556 items are extracted from sources. The most appropriate procedure to assess the life cycle of crude oil processing is Cumulative Energy Demand and Cumulative Exergy Demand energy approach. Based on the first-order analysis, the highest consumption of resources and energy is in the crude oil transmission sector; (Road construction with 44.95 petajoules and transmission pipelines with 19.85 petajoules). Also, regarding the second-order analysis, the highest consumption of resources and energy is related to crude oil production processes with 1.65 petajoules per operation and desalination unit, medium voltage electricity consumption with 0.002194 petajoules and exergy of power lines with 0.00087 petajoules.

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.

Recently, making use of emerging fuels such as municipal waste has been proposed as an alternative for conventional fuels and also as a way for municipal waste disposal. This research, while modeling the thermal and electrical profiles of Ilam Industrial Town, examines the possibility of supplying the required fuel from municipal waste by the year 2041. For this purpose, different combined heat and power (CHP) scenarios were implemented in the LEAP software. According to the results, electricity generation will start gradually from the year of operation of the power plants in 2025 and reach more than 4.3 GWh in 2026. The production process will be incremental and is expected to reach 115.9, 119.1, 111.8, 118.4, 123.1, 118.9, 118.4, 118.4 GWh, respectively under the scenarios of gasifier CHP, CHP turbine incinerator, CHP steam incinerator, landfill CHP, syngas CHP, anaerobic digester CHP, combined gasifier and incinerator CHP, and ultimately improve to 118.9 GWh under the scenario of optimized gasifier and incinerator CHP. The required power plant capacity under the above-mentioned scenarios is expected to be approximately 21 MW by the year 2041and modify to 20.5 MW under the optimization scenario. The incinerator, combined-incinerator-and-gasifier, and optimization scenarios meet the supply and demand conditions of the generated waste, and in other scenarios, either the CHP supply share should be lower than 50% or the additional waste should be supplied from the nearby villages and towns.

The consequence of the lockdowns implemented to address the COVID-19 pandemic on human health damage due to air pollution and other environmental issues must be better understood. This paper analyses the effect of reducing energy demand on the evolution of environmental impacts during the occurrence of 2020-lockdown periods in Italy, with a specific focus on life expectancy. An energy metabolism analysis is conducted based on the life cycle assessment (LCA) of all monthly energy consumptions, by sector, category and province area in Italy between January 2015 to December 2020. Results show a general decrease (by ∼5% on average) of the LCA midpoint impact categories (global warming, stratospheric ozone depletion, fine particulate matter formation, etc.) over the entire year 2020 when compared to past years. These avoided impacts, mainly due to reductions in fossil energy consumptions, are meaningful during the first lockdown phase between March and May 2020 (by ∼21% on average). Regarding the LCA endpoint damage on human health, ∼66 Disability Adjusted Life Years (DALYs) per 100,000 inhabitants are estimated to be saved. The analysis shows that the magnitude of the officially recorded casualties is substantially larger than the estimated gains in human lives due to the environmental impact reductions. Future research could therefore investigate the complex cause-effect relationships between the deaths occurred in 2020 imputed to COVID-19 disease and co-factors other than the SARS-CoV-2 virus.

Reconstructing the long-term Hg history in major emission countries is important for understanding the global Hg cycle and controlling Hg pollution. In this study, the atmospheric Hg history was reconstructed over the last three centuries based on three lacustrine sediment records from southeastern Inner Mongolia in North China, and its relationship with global and regional Hg emissions was revealed. These records show little Hg pollution in the 18th and 19th centuries. This implies a limited influence of Hg emitted from Europe and North America in this region, which is confirmed by their different Hg trends during the two World Wars and the post-1970s. Atmospheric Hg in the region had increased gradually since the 1900s, primarily contributed by emissions from the former Soviet Union in Lake Dalihu (DLH) and Lake Zhagesitai (ZGST) and from the Beijing-Tianjin-Hebei region in Lake Kulunnao (KLN). In the last century, two decreases in Hg fluxes occurred in the KLN core due to the economic recession in the 1960s–1970s and reduced energy consumption and industrial production in the 1990s. In the DLH and ZGST cores, only one decrease occurred, corresponded with the dissolution of the Soviet Union in the 1990s. Although atmospheric Hg emissions in China had stabilized or even decreased in the last decade, atmospheric Hg continued to increase, particularly in KLN, because of emissions from small cities in the region. This study can help understand Hg sources and control Hg pollution in North China and supplement the understanding of the global Hg cycling.

Purple Martins (Progne subis) are migratory birds that breed in North America and overwinter and complete their molt in South America. Many of the breeding populations are declining. The eastern North American subspecies of Purple Martin (P. subis subis) comprises >90% of all Purple Martins. This subspecies overwinters and molts in the Amazon Basin, a region that is high in mercury (Hg) contamination, which raises the possibility that observed declines in Purple Martins could be linked to Hg exposure. Exposure to Hg results in numerous and systemic negative health outcomes, including endocrine disruption. Corticosterone (CORT) is a primary modulator of the stress and metabolic axes of vertebrates; thus, it is important in meeting metabolic and other challenges of migration. Because feathers accumulate Hg and hormones while growing, quantification of Hg and CORT in feathers provides an opportunity to retrospectively assess Hg exposure and adrenal activity of birds using minimally invasive methods. We evaluated interrelationships among concentrations of total Hg (THg) and CORT in feathers that grew in the Amazon Basin and body condition (mass, fat score) of these birds in North America. Concentrations of THg in Purple Martin feathers ranged from 1.103 to 8.740 μg/g dw, levels associated with negative physiological impacts in other avian species. Concentrations of CORT did not correlate with THg concentration at the time of feather growth. However, we found evidence that THg concentration may negatively impact the ability of Purple Martins to accumulate fat, which could impair migratory performance and survivorship due to the high energy requirements of migration. This finding suggests potential carryover effects of Hg contamination at the wintering grounds in the Amazon to the summer breeding grounds in North America.

Slow nutrient turnover and destructed soil function were the main factors causing low efficiency in phytoremediation of heavy metal (HM)-contaminated soil. Soil ecoenzymatic stoichiometry can reflect the ability of soil microorganisms to acquire energy and nutrients, and drive nutrient cycling and carbon (C) decomposition in HM-contaminated soil. Therefore, for the first time, we used the enzymatic stoichiometry modeling to examine the microbial nutrient limitation in rhizospheric and bulk soil of different plants (Medicago sativa, Halogeton arachnoideus and Agropyron cristatum) near the Baiyin Copper Mine. Results showed that the main pollutants in this area were Cu, Zn, Cd, and Pb, while Cd and Zn have the greatest contribution according to the analysis of pollution load index (PLI). The activities of soil C-, nitrogen (N)-, and phosphorus (P)-acquiring enzymes in the rhizosphere of plants were significantly greater than that in bulk soil. Moreover, microbial C and P limitations were observed in all plant treatments, while the lower limitation was generally in the rhizosphere compared to bulk soil. The HM stress significantly increased microbial C limitation and decreased microbial P limitation, especially in the rhizospheric soil. The partial least squares path modeling (PLS-PM) further indicated that HM concentration has the greatest effects on microbial P limitation (−0.64). In addition, the highest enzyme activities and the lowest P limitation were observed in the rhizospheric and bulk soil of M. sativa, thereby implying that soil microbial communities under the remediation of M. sativa were steadier and more efficient in terms of their metabolism. These findings are important for the elucidation of the nutrient cycling and microbial metabolism of rhizosphere under phytoremediation, and provide guidance for the restoration of HM-contaminated soil.

As typical pollutants, petroleum hydrocarbons that are widely present in various environmental media such as soil, water, sediments, and air, seriously endanger living organisms and human health. In the meantime, as a green environmental technology that integrates pollutant removal and resource recovery, bioelectrochemical systems (BESs) have been extensively applied to the removal of petroleum hydrocarbons from the environment. This review introduces working principles of BESs, following which it discusses the different reactor structures, application progresses, and key optimization factors when treating water, sewage sludges, sediments, and soil. Furthermore, bibliometrics was first used in this field to analyze the evolution of knowledge structure and forecast future hot topics. The research focus has shifted from the early generation of bioelectric energy to exploring mechanisms of soil remediation and microbial metabolisms, which will be closely integrated in the future. Finally, the future prospects of this field are proposed. This review focuses on the research status of bioelectrochemical degradation of petroleum hydrocarbons and provides a scientific reference for subsequent research.

Titanium dioxide nanoparticles (TiO₂ NPs) easily combine with other pollutants such as heavy metals because of their excellent physiochemical properties. However, how such an interaction may affect the binding behavior of metals onto biofilms remains largely unclear. This study, examined the effects of TiO₂ NPs on Cd²⁺ accumulation and toxicity for natural periphytic biofilms were examined. The adsorption kinetics showed that adding 0.1 and 1 mg/L TiO₂–NPs increased the Cd²⁺ adsorption of biofilms at equilibrium by 23.5% and 35.8%, respectively. However, adding 10 mg/L TiO₂ NPs increased the Cd²⁺ adsorption of biofilms at equilibrium by only 1.9%. The adsorption isotherms indicate that the presence of TiO₂ NPs considerably increased the Cd²⁺ adsorption capacity of the biofilms; however, this effect became less prominent at high TiO₂ NP concentrations. The optimum pH for Cd²⁺ adsorption increased with increasing Cd²⁺ and TiO₂ NP contents. At low concentrations, the coexistence of Cd²⁺ and TiO₂ NPs may facilitate their respective accumulation by stimulating the secretion of extracellular polymeric substances and enhancing the microbial activity of the biofilm. The presence of TiO₂ NPs increases the surface binding energy between Cd²⁺ and functional groups such as carboxyl groups, enhancing the Cd²⁺ accumulation on the biofilm.