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Among these ESs hotspots, over 50 % fell within PAs. This suggested that although PAs delivered moderately well outcomes in preserving ESs and biodiversity in Xinjiang, conservation gaps needed to be addressed. Our study also revealed substantial differences in ESs supplied by different PAs, and serious deficiency existed in some PAs in protecting either biodiversity or key ESs outlined in their conservation objectives. Our study illustrated the priority areas for future conservation expansion and stressed the urgent shift toward broadening the goals of PAs from a dominant focus to ones that encompass multiple ESs for human well-being.Shelterbelts are rows of trees planted around farmyards and field for protection against soil erosion, promotion of biodiversity and wildlife habitat. Additionally, to carbon sequestration through growth in tree biomass and carbon sinks in agricultural soil. In recent years, removal of shelterbelts has become more common, as crop land is preferred under higher crop prices, resulting in increased GHG emissions and decreases in carbon sinks. It is likely that landowners are making decisions without the knowledge of carbon sequestered by these trees. In this study, the level of carbon sequestration for the six common shelterbelt tree species found in Saskatchewan (hybrid poplar, green ash, Manitoba maple, Scots pine, white spruce, and caragana) was estimated using a carbon - life cycle analysis method. Net amount of carbon sequestered was estimated for five sequestration/emission stages - 1) seedling production, 2) transportation of seedlings to farm, 3) planting, 4) maintenance, and 5) growth of shelterbelts on period in the Black soil zone. In comparison, in the Brown soil zone, Manitoba maple and white spruce sequestered 756 and 732 t CO2, respectively over the same period. If a landowner decides to remove a 60-year-old shelterbelt, 1205 t CO2 is lost within a short period after removal, whereas 718 t of remaining CO2 is retained as dead organic matter, which is slowly released over a period. Although field shelterbelts may emit greenhouse gases in the earlier stages of development, overall, they are net sinks of carbon and can therefore play a significant role in Canada's plan to reduce GHG emissions from agriculture.This study evaluates water quality, concentrations and health risks of heavy metals (HMs) in eight major lakes in Kenya namely Naivasha, Elementaita, Nakuru, Baringo, Bogoria, Turkana, Victoria and Magadi. Water quality was assessed using water quality index (WQI) and pollution evaluation index (PEI), while human health risk associated with ingestion and dermal contact of HMs was assessed using hazard quotients (HQ) and hazard index (HI). Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to deduce the probable sources of the HMs. 2,2,2-Tribromoethanol datasheet The average concentration of aluminium (Al), molybdenum (Mo), manganese (Mn), nickel (Ni), arsenic (As), zinc (Zn), selenium (Se), lead (Pb), chromium (Cr), mercury (Hg), cobalt (Co) and cadmium (Cd) in the eight lakes was 824.6, 66.1, 58.9, 16.2, 8.40, 7.84, 6.91, 4.65, 2.66, 0.86, 0.78 and 0.46, respectively, all in μg/L. Al, Mn, As, and Mo were relatively high in Rift Valley lakes and exceeded the maximum permissible levels for drinking water. Nong water from Lake Elementaita, Nakuru, Bogoria and Magadi due to non-carcinogenic risks associated with As, Zn and Mo. These results are important for formulating the necessary remediation policies to improve water quality in the eight lakes.Landfill leachate contains many complex components that have a negative impact on the environment when improperly discharged. This study is the first to treat landfill leachate (after continuous flow sequencing bed biofilm reactor (CF-SBBR) bio-digested) using electrocoagulation (EC) combined with persulfate (PS) on Al and Fe electrodes. The effect of some of the key parameters on the COD, Color, TOC and TN removal efficiencies as part of the EC-PS process were studied using the PS concentration, reaction time, initial pH, current density, and aeration rate. The results show that a PS concentration of 3 g/L improved the COD removal efficiency by 9.0 ± 1.3 % at the Al electrode and 16.0 ± 2.6 % at the Fe electrode. Aeration also improved the COD, TOC and color removal efficiencies by about 10.0 ± 2.3 %, 8.0 ± 1.7 % and 3.0 ± 0.5 % at an optimal aeration rate 3.3 L/min. The optimal operation conditions for the EC-PS process were a PS concentration of 3 g/L, a pH of 2.0 (Al electrode), a pH of 4.0 (Fe electrode), a reaction time of 70 min, a current density of 35 mA/cm2 and an aeration rate of 3.3 L/min. The highest COD, color, TOC and TN removal efficiencies were 46.5 ± 1.8 %, 95.8 ± 2.4 %, 83.5 ± 1.7 %, and 40.9 ± 1.6 % at Al electrode and 54.4 ± 2.3 %, 98.5 ± 2.1 %, 78.6 ± 1.5 % and 57.9 ± 1.1 % at the Fe electrode. The EC-PS working mechanisms involve co-precipitation, an advanced oxidation process (AOPs) using oxidation radicals (HO, SO4-) and flotation. EC-PS is a promising method to treat bio-digested landfill leachate.The depletion of fossil fuels has been a greater concern to the world due to the demand for energy that tremendously increasing with urbanization and population growth. For sustainable development, power industries are trying to find suitable substitute of petroleum fuel which is environment friendly and economically feasible. The biomass such as the production of bio-oil from chicken litter could be a possible alternative source of energy. The conversion of the feedstock was conducted through a catalytic pyrolysis process in an ex-situ fixed bed reactor heated at 500 °C with a heating rate of 50 °C/min. Proximate, ultimate, and calorific analysis of the feedstock was studied using TGA/DTG analysis, CHNS, and bomb calorimeter, respectively. GCMS and py-GCMS experiments on the bio-oil showed that the HHV of the feedstock was 16.01 MJ/kg. The addition of catalyst improved the quality of the bio-oil yield. The presence of dolomite and ZMS-5 catalyst enhances the phenols and aromatic content, respectively. Biomass to catalyst (B/C) ratio increased the oil production from 43.6g to 51.9g for dolomite and 43.6g-47.1g for ZMS-5 with the B/C ration of 20g3g. Elevating the B/C ratio increases the pyrolytic liquid yield with greater influence on the furanic compound.Complete autotrophic nitrogen removal over nitrite (CANON) is used in wastewater treatment. However, the performance of the CANON system significantly decreases at low temperatures; thus, a new strategy to improve the resistance of the CANON system is required. To investigate the impact of sludge ratio control (high-granule, equivalent, and high-floc systems) on the resistance of CANON to low temperatures, and their recovery after restoring to normal temperature, the nitrogen removal performance of hybrid systems with different ratios was evaluated. The equivalent system had the lowest nitrite accumulation rate and highest nitrogen removal rate. Anaerobic ammonia oxidation was the rate-limiting step of each system, and hzs was the rate-limiting gene. The higher anaerobic ammonium oxidizing bacteria (AAOB) abundance and hzs expression levels resulted in an equivalent system with better resistance and recovery to short-term low temperatures at the gene level.Assisting the natural recovery of coral reefs through local management actions is needed in response to increasing ecosystem disturbances in the Anthropocene. There is growing evidence that commonly used resilience-based passive management approaches may not be sufficient to maintain coral reef key functions. We synthesize and discuss advances in coral reef recovery research, and its application to coral reef conservation and restoration practices. We then present a framework to guide the decision-making of reef managers, scientists and other stakeholders, to best support reef recovery after a disturbance. The overall aim of this management framework is to catalyse reef recovery, to minimize recovery times, and to limit the need for ongoing management interventions into the future. Our framework includes two main stages first, a prioritization method for assessment following a large-scale disturbance, which is based on a reef's social-ecological values, and on a classification of the likelihood of recovery ortions to return to a functional state providing key ecosystem services.Regulatory agencies are beginning to recognize and regulate per-and polyfluoroalkyl substances (PFAS) as concerning environmental contaminants. In groundwater management, testing and mitigation strategies are desirable, but can be time and cost-intensive processes. As a result, only a fraction of all groundwater wells has been tested for PFAS levels, resulting in potentially extended drinking water exposure to PFAS in the meantime. In this study, we build a series of machine learning models (including linear and random forest regressors) to predict PFAS based on a groundwater dataset from California. These models are used to compare the relative predictive ability of co-contaminant fingerprints, hydrological properties, soil parameters, proximity of airports/military bases, and geospatial data. Additionally, a random forest machine learning model that combines all data types can quantitatively predict the maximum PFAS compound concentration in a well with a Spearman correlation of 0.64 and can discern wells containing concerningly high concentrations of PFAS with an accuracy of 91 % (AUC of 0.90). This approach may have widespread utility for other hazardous anthropogenic compounds in groundwater. Future investigations should evaluate the practicability of using machine learning to prospectively prioritize contaminant testing in groundwater wells.This review compiles recent advances and challenges on photocatalytic treatment of wastewater using nanoparticles, nanocomposites, and polymer nanocomposites as photocatalyst. The review provides an overview of the fundamental principles of photocatalytic treatment along the recent advances on photocatalytic treatment, especially on the modification strategies and operational conditions to enhance treatment efficiency and removal of recalcitrant organic contaminants. The different types of photocatalysts along the key factors influencing their performance are also critically discussed and recommendations for future research are provided.River biomonitoring uses biotic indices that assess human-induced degradation, including pollution, by comparison with type-specific static biological reference conditions. However, index scores that indicate pollution may reflect biological responses to natural hydrological variability associated with low flows and drying, leading biomonitoring schemes to misclassify sites as degraded. To address this, dynamic, site-specific adjustments of static biological reference conditions have been proposed, but current biomonitoring tools cannot facilitate implementation of these adjustments. We analyzed 329 samples from mediterranean-climate rivers in Greece, to evaluate the use of six stressor-specific macroinvertebrate-based indices of hydrological variability (CEFI, DEHLI, ELF, LIFE, LIFENZ, MIS-index) as tools to facilitate dynamic adjustments of static biological reference conditions. We examined macroinvertebrate assemblage responses to physicochemical and land use drivers in relation to each sample's hydrological conditions, as assessed by the six indices.