Stimulation of Indigenous Carbonate Precipitating Bacteria for Ground Improvement

Calcite minerals are precipitated in soil through biomineralisation which can be either organic or inorganic in nature. Biomineralisation can be employed to improve ground conditions in its natural state. Usually, studies of applied biomineralisation are highly interdisciplinary involving expertise from engineers, chemists and microbiologists. In this paper, we study the potential of biomineralisation from indigenous bacteria present in soil. The soil samples were collected from a high permeable zone and the bacteria that inhabit the soil were stimulated at a temperature of 15°C. A cementation solution consisting of 500mM calcium chloride, urea and nutrient broth at a pH of 7.5 was added to the soil samples. Inorganic precipitation was found to be dominant and was more efficient when compared to organic precipitation. Carbonate precipitation data indicated that inorganic precipitation were 1.37 times better at carbonate formation in comparison to organic precipitation. Scanning Electron Microscopy analysis identified cementation bonds formed between soil particles. It was deducted that organic precipitation is dependent on temperature, and may take an extended time at such low temperature. The preliminary data presented in this paper suggests that the implementation of biomineralisation with in-situ microbes is promising but requires further laboratory and field investigation before being considered for engineering application.XJTL

Next-generation sequencing showing potential leachate influence on bacterial communities around a landfill in China

The impact of contaminated leachate on groundwater from landfills is well known but specific effects on bacterial consortia are less well-studied. Bacterial communities in landfill and an urban site located in Suzhou, China were studied using Illumina high-throughput sequencing. A total number of 153944 good quality reads were produced and sequences assigned to 6388 operational taxonomic units (OTUs). Bacterial consortia consisted of up to 16 phyla including Proteobacteria (31.9 to 94.9% at landfill, 25.1 to 43.3% at urban sites), Actinobacteria (0 to 28.7% at landfill, 9.9 to 34.3% at urban sites), Bacteroidetes (1.4 to 25.6% at landfill, 5.6 to 7.8% at urban sites), Chloroflexi (0.4 to 26.5% at urban sites only) and unclassified bacteria. Pseudomonas was the dominant (67-93%) genus in landfill leachate. Arsenic concentrations in landfill raw leachate (RL) (1.11x103 µg/L) and fresh leachate (FL2) (1.78x103 µg/L), and mercury concentrations in RL (10.9 µg/L) and FL2 (7.37 µg/L) were higher than Chinese State Environmental Protection Administration (SEPA) standards for leachate in landfills. Shannon diversity index and Chao 1 richness estimate showed RL and FL2 lacked richness and diversity when compared with other samples. This is consistent with stresses imposed by elevated arsenic and mercury and has implications for ecological site remediation by bioremediation or natural attenuation

Biomineralisation performance of bacteria isolated from a landfill in China

We report an investigation of microbially-induced carbonate precipitation by seven indigenous bacteria isolated from a landfill in China. Bacterial strains were cultured in a medium supplemented with 25 mM calcium chloride and 333 mM urea. The experiments were carried out at 30 °C for 7 days with agitation by a shaking table at 130 rpm. Scanning Electron Microscopic (SEM) and X-ray diffraction (XRD) analyses showed variations in calcium carbonate polymorphs and mineral composition induced by all bacterial strains. The amount of carbonate precipitation was quantified by titration. The amount of carbonate precipitated in the medium varied among isolates with the lowest being Bacillus aerius rawirorabr15 (LC092833) precipitating around 1.5 times more carbonate per unit volume than the abiotic (blank) solution. Pseudomonas nitroreducens szh_asesj15 (LC090854) was found to be the most efficient, precipitating 3.2 times more carbonate than the abiotic solution. Our results indicate that bacterial carbonate precipitation occurred through ureolysis and suggest that variations in carbonate crystal polymorphs and rates of precipitation were driven by strain-specific differences in urease expression and response to the alkaline environment. These results and the method applied provide benchmarking/screening data for assessing the bioremediation potential of indigenous bacteria for containment of contaminants in landfills

Spatial distribution, risk index, and correlation of heavy metals in the Chuhe River (Yangtze Tributary): preliminary research analysis of surface water and sediment contamination

This comprehensive study aimed to evaluate the water quality and sediment contamination in the Chuhe River in Nanjing. The spatial assessment of 10 samples collected in September highlighted that, in surface water, Copper (Cu) > Nickel (Ni) > Zinc (Zn) > Chromium (Cr) > Lead (Pb) > Arsenic (As) > Cadmium (Cd) > Mercury (Hg), whereas in sediments, Zn > Cr > Cu > Pb > Ni > As > Cd > Hg. The coefficient of variation (CV) for Ni and Zn in surface water was >15, whereas As, Cu, Pb, and Ni had a CV that was higher than 15 in sediments, indicating variability in contamination sources. The Pollution Load Index values ranged between 2.16 and 3.05, reflecting varying contamination levels across samples. The Geoaccumulation Index data also showed moderate-to-considerable contamination, especially for elements such as Cd and Cu. Correlation analyses in water and sediments unearthed significant relationships, with notable links between Cu and Pb in the water and strong correlations between As and Cu and between Cr and Ni in sediments. In sediments, Total Nitrogen and Phosphorus were significantly correlated with As, Cu, Pb, and Ni. The Potential Ecological Response Index for sediments indicated that they are at medium to high risk (307.47 ± 33.17) and could be potentially detrimental to aquatic life in the tributary. The tributary, influenced by agricultural runoff, residential areas, and other anthropogenic activities, showed that despite Nemerow pollution index values for water samples being below 1, sediment analysis indicated areas of concern. Principal Component Analysis (PCA) was conducted to identify the potential sources of heavy metal contamination. In surface water, shared negative loadings on PC 1 (60.11%) indicated a unified influence, likely from agricultural runoff, while PC 2 (14.26%) revealed additional complexities. Sediments exhibited a unique signature on PC 1 (67.05%), associated with cumulative agricultural impacts, with PC 2 (18.08%) providing insights into nuanced factors, such as sediment composition and dynamic interactions. These findings offer a complete insight into the Chuhe River tributary’s condition, underlining the urgency for ongoing monitoring and potential remediation measures

MICP and Advances towards Eco-Friendly and Economical Applications

Biomineralization is a natural process aided by living organisms. Due to its applicability in ground improvement and bioremediation, Microbially Induced Calcite Precipitation (MICP) is an interdisciplinary field of study combining engineering, chemistry and microbiology. Bioremediation has been applied widely for contamination containment or removal, in this case it will be containment. MICP can also be applied to improve the efficiency of insitu bioremediation. Urease is an enzyme which can facilitate increased calcite precipitation. However the production of urease by bacteria and thus the resulting carbonate precipitation are inhibited by environmental factors including calcium concentration, bacterial concentration, pH and temperature. Under good conditions MICP can be used for heavy metal and radionuclide immobilization. However technologies such as bioconsolidation and biocementation require improvement such as time and cost. This paper highlights the application of MICP in addition to suggested improvements to make it more eco-friendly and sustainable.XJTL

MICP as a potential sustainable technique to treat or entrap contaminants in the natural environment: A review

In the last two decades, developments in the area of biomineralization has yielded promising results making it a potentially environmentally friendly technique for a wide range of applications in engineering and wastewater/heavy metal remediation. Microbially Induced Carbonate Precipitation (MICP) has led to numerous patented applications ranging from novel strains and nutrient sources for the precipitation of biominerals. Studies are being constantly published to optimize the process to become a promising, cost effective, ecofriendly approach when compared with the existing traditional remediation technologies which are implemented to solve multiple contamination/pollution issues. Heavy metal pollution still poses a major threat towards compromising the ecosystem. The removal of heavy metals is of high importance due to their recalcitrance and persistence in the environment. In that perspective, this paper reviews the current and most significant discoveries and applications of MICP towards the conversion of heavy metals into heavy metal carbonates and removal of calcium from contaminated media such as polluted water. It is evident from the literature survey that although heavy metal carbonate research is very effective in removal, is still in its early stages but could serve as a solution if the microorganisms are stimulated directly in the heavy metal environment

Microbially induced calcite precipitation performance of multiple landfill indigenous bacteria compared to a commercially available bacteria in porous media

Microbially Induced Carbonate Precipitation (MICP) is currently viewed as one of the potential prominent processes for field applications towards the prevention of soil erosion, healing cracks in bricks, and groundwater contamination. Typically, the bacteria involved in MICP manipulate their environment leading to calcite precipitation with an enzyme such as urease, causing calcite crystals to form on the surface of grains forming cementation bonds between particles that help in reducing soil permeability and increase overall compressive strength. In this paper, the main focus is to study the MICP performance of three indigenous landfill bacteria against a well-known commercially bought MICP bacteria (Bacillus megaterium) using sand columns. In order to check the viability of the method for potential field conditions, the tests were carried out at slightly less favourable environmental conditions, i.e., at temperatures between 15-17°C and without the addition of urease enzymes. Furthermore, the sand was loose without any compaction to imitate real ground conditions. The results showed that the indigenous bacteria yielded similar permeability reduction (4.79 E-05 to 5.65 E-05) and calcium carbonate formation (14.4–14.7%) to the control bacteria (Bacillus megaterium), which had permeability reduction of 4.56 E-5 and CaCO(3) of 13.6%. Also, reasonably good unconfined compressive strengths (160–258 kPa) were noted for the indigenous bacteria samples (160 kPa). SEM and XRD showed the variation of biocrystals formation mainly detected as Calcite and Vaterite. Overall, all of the indigenous bacteria performed slightly better than the control bacteria in strength, permeability, and CaCO(3) precipitation. In retrospect, this study provides clear evidence that the indigenous bacteria in such environments can provide similar calcite precipitation potential as well-documented bacteria from cell culture banks. Hence, the idea of MICP field application through biostimulation of indigenous bacteria rather than bioaugmentation can become a reality in the near future

Sulfonamide and tetracycline resistance genes in nanjing lakes: effect of water quality and heavy metals

Due to high population density, anthropogenic activities and waste disposal have negatively affected artificial lakes in residential areas. These artificial lakes lack the capacity for auto-depuration to remove pollutants and contaminants; thus, they have the potential to act as reservoirs for antibiotic resistance genes (ARGs). In this study, we examined three urban artificial freshwater lakes in Nanjing to determine the abundance of sulfonamide and tetracycline resistance genes. Concerning water quality, the three lakes were found to be highly eutrophic, owing to their high levels of Total Nitrogen (TN), Phosphorous (TP), and Chlorophyll a (Chla). The average abundance of sulfonamide resistance genes detected in the three urban lakes was 42.446 log _10 gene copies/100 ml, which was lower than the average abundance of tetracycline resistance genes (68.207 log _10 gene copies/100 ml). Analysis by ANOVA revealed that all ARGs, except sul 3, showed significant differences, probably due to varied anthropogenic influences in lakes. Pearson correlation and principal component analyses were performed to explore the correlation between ARGs, water quality markers, and heavy metals to understand the co-selection and drivers of ARGs propagation. tet M showed no correlation with any water quality markers, whereas Chla showed a positive correlation with all ARGs except tet M. tetM was the only gene observed to be unaffected by TN, TP, and Chla. The tet genes also showed strong associations with each other except tet M, especially tet A, tet Q, and tet G. The co-selection results between heavy metals and ARGs were insignificant (p > 0.05), with tet M being the most sensitive to the effects of heavy metals and As having the strongest effect on sul 3 and tet genes. The results from this study provide basic but archival information on the effect of eutrophication and heavy metals such as Arsenic, showing the potential influence on the dissemination of certain sulfonamide and tetracycline ARGs in freshwater environments

Projection of Extreme Temperature Events over the Mediterranean and Sahara Using Bias-Corrected CMIP6 Models

Climate change continues to increase the intensity, frequency and impacts of weather and climate extremes. This work uses bias-adjusted Coupled Model Intercomparison Project Phase six (CMIP6) model datasets to investigate the future changes in temperature extremes over Mediterranean (MED) and Sahara (SAH) regions. The mid- (2041–2070) and far-future (2071–2100) are studied under two Shared Socioeconomic Pathways: SSP2-4.5 and SSP5-8.5 scenarios. Quantile mapping function greatly improved the performance of CMIP6 by reducing the notable biases to match the distribution of observation data, the Climate Prediction Center (CPC). Results show persistent significant warming throughout the 21st century, increasing with the increase in radiative forcing. The MED will record a higher increase in temperature extremes as compared to SAH. The warming is supported by the projected reduction in cold days (TX10p) and cold nights (TN10p), with the reduction in the number of cold nights exceeding cold days. Notably, warm spell duration index (WSDI) and summer days (SU) have a positive trend in both timelines over the entire study area. There is a need to simulate how climate sensitive sectors, such as water and agriculture, are likely to be affected by projected changes under different scenarios for informed decision making in the choice and implementation of adaptation and mitigation effective measures

Evaluation of the Performance of CMIP6 Models in Reproducing Rainfall Patterns over North Africa

This study assesses the performance of historical rainfall data from the Coupled Model Intercomparison Project phase 6 (CMIP6) in reproducing the spatial and temporal rainfall variability over North Africa. Datasets from Climatic Research Unit (CRU) and Global Precipitation Climatology Centre (GPCC) are used as proxy to observational datasets to examine the capability of 15 CMIP6 models’ and their ensemble in simulating rainfall during 1951–2014. In addition, robust statistical metrics, empirical cumulative distribution function (ECDF), Taylor diagram (TD), and Taylor skill score (TSS) are utilized to assess models’ performance in reproducing annual and seasonal and monthly rainfall over the study domain. Results show that CMIP6 models satisfactorily reproduce mean annual climatology of dry/wet months. However, some models show a slight over/under estimation across dry/wet months. The models’ overall top ranking from all the performance analyses ranging from mean cycle simulation, trend analysis, inter-annual variability, ECDFs, and statistical metrics are as follows: EC-Earth3-Veg, UKESM1-0-LL, GFDL-CM4, NorESM2-LM, IPSL-CM6A-LR, and GFDL-ESM4. The mean model ensemble outperformed the individual CMIP6 models resulting in a TSS ratio (0.79). For future impact studies over the study domain, it is advisable to employ the multi-model ensemble of the best performing models