Emitted from vehicles, plant biomass combustion, and industries, particulate matter (PM) is an air pollutant widely studied by the scientific community due to its health effects (cardiorespiratory diseases, cancers, eye irritations, among others). The present study evaluates periods with high PM concentrations, defined as high-PM₁₀ episodes (daily concentrations above the 75th percentile), to define and assess the main possible sources of PM emission in the city of Limeira, São Paulo, Brazil. To determine the location of such sources, the trajectory regression analysis (TRA) statistical tool was used, based on trajectories obtained from the HYSPLIT model. The 75th percentile was calculated at 41.21 µg/m³, with a maximum concentration of 114.38 µg/m³. Results point to autumn, winter, and spring as the seasons with the highest number of episodes, accounting for 33, 91, and 49 episodes, respectively. April 2016 (20 episodes), July 2016 (25), and September 2017 (27), possibly due to the low precipitation rates, had the highest monthly totals. TRA showed that local sources (within a 500 km radius) were the ones contributing the most to PM concentration in the period studied, totaling 55%, which allows us to point to vehicle and industrial emissions near the city of Limeira as the main sources.

Studies indicate that the soil, water and consequently foodstuffs in Serbia are significantly poor in zinc (Zn), and thus, it is likely that there is a Zn deficiency in the Serbian population. This study examined the Zn status in multiple clinical samples, including body fluids (serum, cerebrospinal fluid), whole blood and Zn-rich solid tissues (thyroid and brain tissue). Differences between sex and age were also considered, and comparative analysis of Zn status with other world populations was performed. Serum samples from a large number of Serbian adults approximately had twofold lower Zn amounts when compared to other populations. A similar trend was obtained for whole blood. Males had significantly higher amounts of Zn in serum, whole blood and thyroid tissue samples than females. Higher amounts of Zn were observed in the group older than 50 years. Importantly, in thyroid and brain tissues, Zn was 10- and 20-fold lower, respectively, than reported in the literature. Our results indicate that the population in Serbia could be considered Zn deficient. Therefore, adequate oral Zn supplementation and/or foodstuff fortification should be considered to prevent the deleterious effects caused by Zn deficiency.

In this work, bioremediation was applied with sinusoidal alternating current (AC) electric fields to remove petroleum hydrocarbon (TPH) for soil remediation. Applying AC electric field with bioremediation (AC+BIO) could efficiently remove 31.6% of the TPH in 21 days, much faster than that in the BIO only system (13.7%) and AC only system (5.5%). When the operation time extended to 119 days, the AC+BIO system could remove 73.3% of the TPH. Applying AC electric field (20–200 V/m) could maintain the soil pH at neutral, superior to the direct current electric field. The maximum difference between soil temperature and the room temperature was 1.9 °C in the AC (50 V/m) +BIO system. The effects of AC voltage gradient (20–200 V/m) on the microorganisms and TPH degradation efficiency by AC+BIO were investigated, and the optimized AC voltage gradient was assessed as 50 V/m for lab-scale experiments. The microbial community structures in the BIO and AC+BIO systems were compared. Although Pseudomonas was the dominant species, Firmicutes became more abundant in the AC+BIO system than the BIO system, indicating their adaptive capacity to the stress of the AC electric field. Real petroleum-contaminated soil was used as a reaction matrix to evaluate the performance of AC+BIO in the field. The initial current density was about 0.2 mA/cm², voltage gradient was about 20 V/m, and the average TPH degradation rate was 8.1 μg/gdᵣy ₛₒᵢₗ per day. This study provided insights and fundamental supports for the applications of AC+BIO to treat petroleum-polluted soils.

This article presents a systematic review of the literature using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method associated with a bibliometric analysis on global perspective of technological advances in waste-to-energy (WTE). OpenRefine and VOSviewer software supported the bibliometric analysis. It was possible to establish the scientific gap through the correlation among interactions observed on co-authored countries’ analyses, cited sources of co-citation, cited authors of co-citation, and keyword of the co-occurrence author. A total of 10 papers were included for meta-analysis and categorized into 8 fields: author(s), title, published year, research areas, energy conversion technologies, wastes used for energy production, WTE products, key findings. Considering the end use of the products, the systematic literature review confirmed a limitation of research focusing on the opportunities for a cleaner transport sector. When analysing the author’s keywords, the most cited were ‘municipal solid waste’, ‘incineration’, ‘waste management’, ‘gasification’, ‘anaerobic digestion’, ‘combustion’, ‘waste-to-energy’, ‘landfill gas’, and ‘sustainability’, noting that the studies were directed at economic and sustainable development, as well as circular economy, aiming to mitigate adverse environmental impacts. As can be seen from the systematic review associated with the bibliometric analysis presented, the waste to energy technology is an important innovation way or route that finds numerous applications in the transport and energetic sector. It was evidenced that the WTE research efforts are mainly focused on the conversion of waste for end use electricity generation. The main role of WTE technologies in the circular economy is the energy recovery from biomass and non-recyclable waste, and also it was presented as a viable alternative to the decarbonization of transport and energy sectors.

Ecological restoration projects have great impacts on ecosystem service values (ESVs) in China. However, it is still unclear how the temporal and spatial characteristics of ESVs in karst areas in southwestern China changed before and after the implementation of some ecological restoration projects. Land use data from five phases between 1980 and 2018 were used in combination with socioeconomic data of karst areas in southwestern China. The equivalent factor method and spatial, autocorrelation analysis method were used to study the temporal and spatial distributions of ESVs. The results show that (1) the conversion of land use types mainly consisted of the conversion of cultivated lands to woodlands, grasslands, and water areas, and from grasslands to woodlands, construction lands, and wetlands; (2) from 1980 to 2018, the overall trend of ESVs in the study area first decreased and then increased; the ESVs increased by 19.62 billion yuan, with a growth rate of 0.35%, and changes in water areas were the main reason for the ESVs increase, while changes in the areas of woodlands and wetlands were the second reason for the ESVs increase; (3) in terms of its spatial distribution, the ESVs was higher in the southwest direction, while in other areas, from west to east, the ESVs generally showed a spatial distribution pattern of “high-low-high-low”; and (4) the ESVs in the study area had significant, positive autocorrelations in its spatial distribution from 1980 to 2018. The spatial aggregation of ESVs among cities mainly included aggregations of spatially similar values. The results of this study provide reference data for ecological infrastructure construction and ecological-economic development in karst areas in southwestern China.

Condensates of vapor-gas streams were collected during field and laboratory experiments for the determination of the volatility of chemical elements in sulfide tailings under ambient conditions. The object of research was the Ursk waste heaps (Kemerovo region, Russia). Field experiments were performed on the top of the heap and in neighboring territories; the elements’ concentrations in condensates from the top exceed the background values in 2–3 orders of magnitude. To obtain condensates in the laboratory, the waste material was heated to 60 °С. Laboratory condensate–contended high concentrations Ca, Mg, but Fe, Cd, Mo, Sn, Zr, and W were lower by more than 2 orders of magnitude. Also, chemical elements such as Au, Zr, Cs, U, and Tl were determined in the laboratory condensates at elevated temperatures. Also, solid samples were leached with water at the laboratory. A high positive correlation of condensate compositions with compositions of water extracts obtained from parallel samples was established. The most mobile elements transferred in the steam-gas phase are alkaline (Li, Cs, Na, K), alkaline earth (Ca, Sr), chalcophile metals (Hg, Zn, Cu), and metalloids (As, Sb, Se). The numerical experiment of metal transfer forms using thermodynamic modeling methods has been performed, including those with organic ligands.

This study investigated the passivation of multiple heavy metals (Cd, Cr, Cu, Zn, and Pb) in river sediments by composting with rice straw. The correlation between the selected environmental factors and the distribution of heavy metal fractions was assessed by multivariate analysis. The results suggested that the composting could reduce the bioavailability of Cu, Cd, Cr, and Pb. The influences of composting on the passivation of these five heavy metals are different. The greatest passivation of heavy metals is for Cd, which its bioavailability decreased 17.72%. The bioavailability of Cu, Pb, and Cr also partly decreased. However, there was almost no effect on the bioavailability of Zn. The results of multivariate analysis revealed that the predominant parameters affecting the variation of the bioavailability of different heavy metals were different in a complex composting system with multiple heavy metal pollution. While the variation partitioning analysis indicated that water-soluble carbon (WSC) was the statistically main factor affecting the bioavailability of Cd, Cr, Cu, Zn, and Pb. It provides a theoretical reference for optimizing the co-composting process in remediation of different heavy metal contamination in sediments.

The adsorption behaviors of methylene blue (MB) on microalga residue powder (MRP) and biochars derived from microalga residue (MRB) produced at different pyrolytic temperatures were compared. Six biochars were prepared from residual Chlorella sp. and Spirulina sp. at different pyrolytic temperatures in the range of 200–550 °C. The adsorption kinetics, isotherms, thermodynamics, and the effect of pH were studied, and chemical analyses of MB-loaded MRP and MRB were conducted using SEM, FTIR, and XPS techniques. The results found that the pseudo-second-order, Elovich, and Freundlich models could effectively describe the MB adsorption process on MRP and MRB. The thermodynamic results confirmed that the adsorption processes were spontaneous and endothermic. Further, MRP showed an excellent adsorption ability on MB through electrostatic interaction, complexation with oxygen/nitrogen-containing functional groups and π-π interaction. However, massive oxygen-containing functional groups after pyrolysis were lost, leading to a significant decrease in the adsorption capacity of MRB on MB. This phenomenon was further observed with increasing pyrolytic temperature. Overall, this study demonstrated that microalga residue performed better for MB removal compared with their pyrolyzed analogs. Graphical abstract

Warming of the earth is considered as the major adverse effect of climate change along with other abnormalities such as non-availability of water resources, decreased agriculture production, food security, rise in seawater level, glaciers melting, and loss of biodiversity. Over the years, decreased agriculture production and water quality degradation have been observed due to climatic abnormalities. Crop production is highly sensitive to climate. It gets affected by long-term trends in average rainfall and temperature, annual climate variations, shocks during different stages of growth, and extreme weather events. Globally, the areas sown for the major crops of barley, maize, rice, sorghum, soya bean, and wheat have all seen an increase in the percentage of area affected by drought as defined in terms of the Palmer Drought Severity Index since the 1960s, from approximately 5–10% to approximately 15–25%. Increase in temperature will be observed in terms of wheat yield losses − 5.5 ± 4.4% per degree Celsius for the United States, − 9.1 ± 5.4% per degree Celsius for India, and − 7.8 ± 6.3% per degree Celsius for Russia as these countries are more vulnerable to temperature increase. Water management through increasing storage capacity (or rainwater storage), fair policies for water supply and distribution, river health, and watershed management can reduce the negative effects of climate change on water resource availability. Similarly, climate change-resistant crop development, water management in irrigation, adapting climate-smart agriculture approach, and promoting indigenous knowledge can ensure the food security via increasing agricultural yield. Technical intervention can equip the farmers with the scientific analyses of the climatic parameters required for the sustainable agriculture management. These technologies may include application of software, nutrient management, water management practices, instruments for temperature measurement and soil health analysis etc. Holistic efforts of the stakeholders (farmers, local society, academia, scientists, policy makers, NGOs etc.) can provide better results to reduce the risks of climate change on agriculture and water resources as discussed in this paper. Graphical abstract

Evaluation of water quality is a priority work nowadays. In order to monitor and map, the water quality for a wide range on different scales (spatial, temporal), the geospatial technique has the potential to minimize the field and laboratory work. The review has emphasized the advance of remote sensing for the effectiveness of spectral analysis, bio-optical estimation, empirical method, and application of machine learning for water quality assessment. The water quality parameters (turbidity, suspended particles, chlorophyll, etc.) and their retrieval techniques are described in a scientific manner. Available satellite, bands, resolution, and spectrum ranges for specific parameters are critically described in this review with challenges in remote sensing for water quality analysis, considering non-optical active parameters. The application of statistical programmes like linear (multiple regression analysis) and non-linear approaches is discussed for better assessment of water quality. Emphasis is given on comparison between different models to increase the accuracy level of remote sensing of water quality assessment. A direction is suggested for future development in the field of estimation of water pollution assessment through geospatial techniques.