Displaying publications 1 - 20 of 89 in total

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  1. Xia C, Lam SS, Sonne C
    Science, 2021 03 19;371(6535):1214.
    PMID: 33737479 DOI: 10.1126/science.abh3100
  2. Xia C, Lam SS, Sonne C
    Science, 2020 Oct 30;370(6516):539.
    PMID: 33122375 DOI: 10.1126/science.abf0461
  3. Peng W, Lam SS, Sonne C
    Science, 2020 01 17;367(6475):257-258.
    PMID: 31949072 DOI: 10.1126/science.aba5642
  4. Sonne C, Lam SS, Kanstrup N
    Eco Environ Health, 2023 Mar;2(1):16-17.
    PMID: 38074451 DOI: 10.1016/j.eehl.2023.02.001
    Image 1.
  5. Sonne C, Peng WX, Alstrup AKO, Lam SS
    Science, 2021 Jun 18;372(6548):1271.
    PMID: 34140374 DOI: 10.1126/science.abj3359
  6. Lam SS, Waugh C, Peng W, Sonne C
    Science, 2020 02 14;367(6479):750.
    PMID: 32054755 DOI: 10.1126/science.aba8372
  7. Lam SS, Ma NL, Peng W, Sonne C
    Science, 2020 May 29;368(6494):958.
    PMID: 32467384 DOI: 10.1126/science.abc2202
  8. Xia C, Lam SS, Zhong H, Fabbri E, Sonne C
    Science, 2022 Nov 25;378(6622):842.
    PMID: 36423283 DOI: 10.1126/science.ade9069
  9. Ravindiran G, Hayder G, Kanagarathinam K, Alagumalai A, Sonne C
    Chemosphere, 2023 Oct;338:139518.
    PMID: 37454985 DOI: 10.1016/j.chemosphere.2023.139518
    Clean air is critical component for health and survival of human and wildlife, as atmospheric pollution is associated with a number of significant diseases including cancer. However, due to rapid industrialization and population growth, activities such as transportation, household, agricultural, and industrial processes contribute to air pollution. As a result, air pollution has become a significant problem in many cities, especially in emerging countries like India. To maintain ambient air quality, regular monitoring and forecasting of air pollution is necessary. For that purpose, machine learning has emerged as a promising technique for predicting the Air Quality Index (AQI) compared to conventional methods. Here we apply the AQI to the city of Visakhapatnam, Andhra Pradesh, India, focusing on 12 contaminants and 10 meteorological parameters from July 2017 to September 2022. For this purpose, we employed several machine learning models, including LightGBM, Random Forest, Catboost, Adaboost, and XGBoost. The results show that the Catboost model outperformed other models with an R2 correlation coefficient of 0.9998, a mean absolute error (MAE) of 0.60, a mean square error (MSE) of 0.58, and a root mean square error (RMSE) of 0.76. The Adaboost model had the least effective prediction with an R2 correlation coefficient of 0.9753. In summary, machine learning is a promising technique for predicting AQI with Catboost being the best-performing model for AQI prediction. Moreover, by leveraging historical data and machine learning algorithms enables accurate predictions of future urban air quality levels on a global scale.
  10. Manoj D, Rajendran S, Murphy M, Jalil AA, Sonne C
    Chemosphere, 2023 Nov;340:139820.
    PMID: 37586499 DOI: 10.1016/j.chemosphere.2023.139820
    Over the past decades, increasing research in metal-organic frameworks (MOFs) being a large family of highly tunable porous materials with intrinsic physical properties, show propitious results for a wide range of applications in adsorption, separation, electrocatalysis, and electrochemical sensors. MOFs have received substantial attention in electrochemical sensors owing to their large surface area, active metal sites, high chemical and thermal stability, and tunable structure with adjustable pore diameters. Benefiting from the superior properties, MOFs and MOF-derived carbon materials act as promising electrode material for the detection of food contaminants. Although several reviews have been reported based on MOF and its nanocomposites for the detection of food contaminants using various analytical methods such as spectrometric, chromatographic, and capillary electrophoresis. But there no significant review has been devoted to MOF/and its derived carbon-based electrodes using electrochemical detection of food contaminants. Here we review and classify MOF-based electrodes over the period between 2017 and 2022, concerning synthetic procedures, electrode fabrication process, and the possible mechanism for detection of the food contaminants which include: heavy metals, antibiotics, mycotoxins, and pesticide residues. The merits and demerits of MOF as electrode material and the need for the fabrication of MOF and its composites/derivatives for the determination of food contaminants are discussed in detail. At last, the current opportunities, key challenges, and prospects in MOF for the development of smart sensing devices for future research in this field are envisioned.
  11. Li X, Lam SS, Xia C, Zhong H, Sonne C
    Science, 2023 Dec;382(6674):1007.
    PMID: 38033061 DOI: 10.1126/science.adl6721
  12. Xia C, Cai L, Lam SS, Sonne C
    Eco Environ Health, 2023 Jun;2(2):41-42.
    PMID: 38075294 DOI: 10.1016/j.eehl.2023.04.001
    •Microplastic pollution threats environmental and human health.•The resolution of End Plastic Pollution promotes the global strategy against plastic pollution.•The governments should launch relevant policies to implement this resolution.
  13. Sonne C, Dietz R, Jenssen BM, Lam SS, Letcher RJ
    Trends Ecol Evol, 2021 05;36(5):421-429.
    PMID: 33602568 DOI: 10.1016/j.tree.2021.01.007
    Recent advances in environmental analytical chemistry have identified the presence of a large number of chemicals of emerging Arctic concern (CEACs) being transported long range to the region. There has been very limited temporal monitoring of CEACs and it is therefore unknown whether they are of increasing or decreasing concern. Likewise, information on potential biological adverse effects from CEACs on Arctic wildlife is lacking compared with legacy persistent organic pollutants (POPs) found at levels associated with health effects in marine mammals. Hence, there is a need to monitor CEACs along with POPs to support risk and regulatory CEAC assessments. We suggest pan-Arctic temporal trend studies of CEACs in wildlife including the establishment of toxicity thresholds to evaluate their potential effects on populations, biodiversity, and ecosystem services.
  14. Ma NL, Lam SD, Che Lah WA, Ahmad A, Rinklebe J, Sonne C, et al.
    Environ Pollut, 2021 Oct 01;286:117214.
    PMID: 33971466 DOI: 10.1016/j.envpol.2021.117214
    Salinisation of soil is associated with urban pollution, industrial development and rising sea level. Understanding how high salinity is managed at the plant cellular level is vital to increase sustainable farming output. Previous studies focus on plant stress responses under salinity tolerance. Yet, there is limited knowledge about the mechanisms involved from stress state until the recovery state; our research aims to close this gap. By using the most tolerance genotype (SS1-14) and the most susceptible genotype (SS2-18), comparative physiological, metabolome and post-harvest assessments were performed to identify the underlying mechanisms for salinity stress recovery in plant cells. The up-regulation of glutamine, asparagine and malonic acid were found in recovered-tolerant genotype, suggesting a role in the regulation of panicle branching and spikelet formation for survival. Rice could survive up to 150 mM NaCl (∼15 ds/m) with declined of production rate 5-20% ranged from tolerance to susceptible genotype. This show that rice farming may still be viable on the high saline affected area with the right selection of salt-tolerant species, including glycophytes. The salt recovery biomarkers identified in this study and the adaption underlined could be empowered to address salinity problem in rice field.
  15. Wei Z, Van Le Q, Peng W, Yang Y, Yang H, Gu H, et al.
    J Hazard Mater, 2021 02 05;403:123658.
    PMID: 33264867 DOI: 10.1016/j.jhazmat.2020.123658
    There is a global need to use plants to restore the ecological environment. There is no systematic review of phytoremediation mechanisms and the parameters for environmental pollution. Here, we review this situation and describe the purification rate of different plants for different pollutants, as well as methods to improve the purification rate of plants. This is needed to promote the use of plants to restore the ecosystems and the environment. We found that plants mainly use their own metabolism including the interaction with microorganisms to repair their ecological environment. In the process of remediation, the purification factors of plants are affected by many conditions such as light intensity, stomatal conductance, temperature and microbial species. In addition the efficiency of phytoremediation is depending on the plants species-specific metabolism including air absorption and photosynthesis, diversity of soil microorganisms and heavy metal uptake. Although the use of nanomaterials and compost promote the restoration of plants to the environment, a high dose may have negative impacts on the plants. In order to improve the practicability of the phytoremediation on environmental restoration, further research is needed to study the effects of different kinds of catalysts on the efficiency of phytoremediation. Thus, the present review provides a recent update for development and applications of phytoremediation in different environments including air, water, and soil.
  16. Khoo SC, Peng WX, Yang Y, Ge SB, Soon CF, Ma NL, et al.
    J Hazard Mater, 2020 12 05;400:123296.
    PMID: 32947701 DOI: 10.1016/j.jhazmat.2020.123296
    Synthetic adhesives in the plywood industry are usually volatile compounds such as formaldehyde-based chemical which are costly and hazardous to health and the environment. This phenomenon promotes an interest in developing bio-boards without synthetic adhesives. This study proposed a novel application of natural mycelium produced during mushroom cultivation as natural bio-adhesive material that convert spent mushroom substrate (SMS) into high-performance bio-board material. Different types of spent mushroom substrates were compressed with specific designed mould with optimal temperature at 160 °C and 10 mPa for 20 min. The bio-board made from Ganoderma lucidum SMS had the highest internal bonding strength up to 2.51 mPa. This is far above the 0.4-0.8 range of China and US national standards. In addition, the material had high water and fire resistance, high bonding and densified structures despite free of any adhesive chemicals. These properties and the low cost one step procedure show the potential as a zero-waste economy chain for sustainable agricultural practice for waste and remediation.
  17. Wang Y, Van Le Q, Yang H, Lam SS, Yang Y, Gu H, et al.
    Chemosphere, 2021 Oct;281:130835.
    PMID: 33992848 DOI: 10.1016/j.chemosphere.2021.130835
    The increase in global population size over the past 100 decades has doubled the requirements for energy resources. To mitigate the limited fossil fuel available, new clean energy sources being environmental sustainable for replacement of traditional energy sources are explored to supplement the current scarcity. Biomass containing lignin and cellulose is the main raw material to replace fossil energy given its abundance and lower emission of greenhouse gases and NOx when transformed into energy. Bacteria, fungi and algae decompose lignocellulose leading to generation of hydrogen, methane, bioethanol and biodiesel being the clean energy used for heating, power generation and the automobile industry. Microbial Fuel Cell (MFC) uses microorganisms to decompose biomass in wastewater to generate electricity and remove heavy metals in wastewater. Biomass contains cellulose, hemicellulose, lignin and other biomacromolecules which need hydrolyzation for conversion into small molecules by corresponding enzymes in order to be utilized by microorganisms. This paper discusses microbial decomposition of biomass into clean energy and the five major ways of clean energy production, and its economic benefits for future renewable energy security.
  18. Sun Q, Chen WJ, Pang B, Sun Z, Lam SS, Sonne C, et al.
    Bioresour Technol, 2021 Dec;341:125807.
    PMID: 34474237 DOI: 10.1016/j.biortech.2021.125807
    In recent years, visualization and characterization of lignocellulose at different scales elucidate the modifications of its ultrastructural and chemical features during hydrothermal pretreatment which include degradation and dissolving of hemicelluloses, swelling and partial hydrolysis of cellulose, melting and redepositing a part of lignin in the surface. As a result, cell walls are swollen, deformed and de-laminated from the adjacent layer, lead to a range of revealed droplets that appear on and within cell walls. Moreover, the certain extent morphological changes significantly promote the downstream processing steps, especially for enzymatic hydrolysis and anaerobic fermentation to bioethanol by increasing the contact area with enzymes. However, the formation of pseudo-lignin hinders the accessibility of cellulase to cellulose, which decreases the efficiency of enzymatic hydrolysis. This review is intended to bridge the gap between the microstructure studies and value-added applications of lignocellulose while inspiring more research prospects to enhance the hydrothermal pretreatment process.
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