Using manure collected from swine fed with diet containing antibiotics and antibiotic-free swine manure spiked with antibiotics are the two common methods of studying the degradation behavior of veterinary antibiotic in manure in the environment. However, few studies had been conducted to co-compare these two different antibiotic addition methods. This study used oxytetracycline (OTC) as a model antibiotic to study antibiotic degradation behavior in manure under the above two OTC addition methods. In addition, the role of microorganisms present in the manure on degradation behavior was also examined. The results showed that degradation half-life of OTC in manure from swine fed OTC (9.04 days) was significantly shorter than that of the manure directly treated with OTC (9.65 days). Concentration of 4-epi-OTC in manure from swine fed OTC peaked earlier than that in manure spiked with OTC, and the degradation rates of 4-epi-OTC and α-apo-OTC in the manure from swine fed OTC were faster, but the peak concentrations were lower, than those in manure spiked with OTC. Bacterial diversity and relative abundance of Bacillus cereus data demonstrated that sterilization of the manure before experiment significantly decreased OTC degradation rate in both of the addition methods. Results of the present study demonstrated that the presence of the metabolites (especially 4-epi-OTC) and microorganisms had significant influence on OTC degradation.
The presented work analyzes the energy prices, climate shock, and health deprivation nexus in the BRICS economies for the period 1995-2020. Panel ARDL-PMG technique is used to reveal the underexplored linkages. The long-run estimates of energy prices are observed to be negatively significant to the health expenditure and life expectancy model, whereas, positively significant to the climate change model. These findings suggest that energy prices significantly reduce health expenditures and life expectancy and, thus, increase the death rate in the BRICS economies. The long-run country-wise estimate of energy prices is found negatively significant in case of Brazil, India, China, and South Africa. Alongside, the group-wise significance of CO2 emissions is discovered to be negatively, positively, and insignificant in the cases of life expectancy, death rate, and health expenditure models, respectively. Besides, country-wise long-run estimate of CO2 emissions witnesses negative significance for Russia, India, China, and South Africa.
Identification of contaminant sources in rivers is crucial for river protection and emergency response. This study presents an innovative approach for identifying river pollution sources by using Bayesian inference and cellular automata (CA) modeling. A general Bayesian framework is proposed that combines the CA model with observed data to identify unknown sources of river pollution. To reduce the computational burden of the Bayesian inference, a CA contaminant transport model is developed to efficiently simulate pollutant concentration values in the river. These simulated concentration values are then used to calculate the likelihood function of available measurements. The Markov chain Monte Carlo (MCMC) method is used to produce the posterior distribution of contaminant source parameters, which is a sampling-based method that enables the estimation of complex posterior distributions. The suggested methodology is applied to a real case study of the Fen River in Yuncheng City, Shanxi Province, Northern China, and it estimates the release time, release mass, and source location with relative errors below 19%. The research indicates that the proposed methodology is an effective and flexible way to identify the location and concentrations of river contaminant sources.
China's construction industry confronts with the dilemma of carbon emissions in adjusting the environmental regulations. Many studies are neglected on discovering the potential nexus amongst environmental regulations (ERs), technological innovation (TI) and CEI (CEI) and ignores the relationships amongst TI for reducing CEI. To mitigate this gap, this study bridges institutional theory to integrate the practices in the construction industry. This study applies a panel dataset on the construction industry from 30 provinces during 2004-2018 and uses it with a two-step system-generalised method of moments for analysis. The proposed method enables the prevention of the interference of the heteroscedasticity problem and improves certain analytical efficiency. The results are as a guideline for policymakers in rechecking the policies and regulations adequacy. The findings indicate that (1) the forced emission reduction effect is proven by command-and-control and market-based ERs, which can inhibit CEI; (2) voluntary ERs have an inverted U-shaped nexus with CEI; in other words, the green paradox effect shifts to the forced emission reduction effect once the intensity of voluntary ERs increases; and (3) market-based and voluntary ERs reduce CEI effectively by using TI as the mediator in construction industry.
Agricultural carbon emission is an important cause of climate change, and the carbon transfer caused by agricultural trade is a key area related to carbon emissions of all countries. Based on the Eora database, this paper aims to constructs a multi-region input-output database of 185 countries or regions, analyzes a spatial correlation network of embodied net carbon transfer in global agricultural trade by using UCINET, selects multi-dimensional network measurement indicators, and comprehensively studies the global evolution characteristics and functional features of network plate role of embodied carbon transfer in the global agricultural trade. The result shows that the embodied net carbon transfer network of global agricultural trade is densely connected, the spatial correlation spillover effect is significant, and the edge of the network core structure is clear. On the one hand, the top four countries or regions in terms of embodied carbon outflow in agricultural trade are the USA, Australia, Vietnam, and China. On the other hand, the top four countries or regions of embodied carbon inflow are Malaysia, Central Africa, Singapore, and Serbia. From the perspective of outdegree, indegree, proximity centrality, and intermediary centrality, Cambodia, the Netherlands, Vietnam, Ghana, and South Africa, with the high frequency of the shortest path of the globally embodied net carbon transfer network, have a strong influence and linking facility in spatial correlation and have a strong control ability to the spatial correlation of other countries or regions. The embodied carbon emission network of global agricultural trade can be divided into four sectors: main spillover, two-way spillover, broker, and main benefit. The main spillover segment, constituted by the USA, India, Germany, and China, has significant embodied carbon spillover effects on the internal segment and other segments. It is the main embodied carbon spillover sector of embodied net carbon transfer of global agricultural trade. Countries should reasonably allocate the responsibility of carbon reduction according to the trading embodied carbon transfer and made efforts to optimize the export structure of agricultural products.
The construction of low-carbon cities is an essential component of sustainable urban development. However, there is a lack of a comprehensive low-carbon city design and evaluation system that incorporates "carbon sink accounting-remote sensing monitoring-numerical modelling-design and application" in an all-around linkage, multi-scale coupling, and localized effects. This paper utilizes the Citespace tool to evaluate low-carbon city design applications by analyzing literature in the Web of Science (WOS) core collection database. The results reveal that low-carbon cities undergo four stages: "measurement-implementation-regulation - management." The research themes are divided into three core clustering evolutionary pathways: "extension of carbon sink functions," "spatialisation of carbon sink systems," and "full-cycle, full-dimensional decarbonisation." Applications include "Utility studies of multi-scale carbon sink assessments," "Correlation analysis of carbon sink influencing factors," "Predictive characterisation of multiple planning scenarios," and "Spatial planning applications of urban sink enhancement." Future low-carbon city construction should incorporate intelligent algorithm technology in real-time to provide a strong design basis for multi-scale urban spatial design with the features of "high-precision accounting, full-cycle assessment and low-energy concept."
Under the new development model, the digital economy has become a new engine to promote the green development of the economy and achieve the goal of "double carbon." Based on panel data from 30 Chinese provinces and cities from 2011 to 2021, the impact of the digital economy on carbon emissions was empirically studied by constructing a panel model and a mediation model. The results show that firstly, the effect of the digital economy on carbon emissions is a non-linear inverted "U" shaped relationship, and this conclusion still holds after a series of robustness tests; secondly, the results of the benchmark regression show that economic agglomeration is an essential mechanism through which the digital economy affects carbon emissions and that the digital economy can indirectly suppress carbon emissions through economic agglomeration. Finally, the results of the heterogeneity analysis show that the impact of the digital economy on carbon emissions varies according to the level of regional development, and its effect on carbon emissions is mainly in the eastern region, while its impact on the central and western regions is weaker, indicating that the impact effect is primarily in developed regions. Therefore, the government should accelerate the construction of new digital infrastructure and implement the development strategy of the digital economy according to local conditions to promote a more significant carbon emission reduction effect of the digital economy.
One of the environmental challenges that modern poultry industry faced is odor pollution caused by ammonia emission. The objectives of the study were to determine the effect of sodium butyrate on the production of ammonia in the cecal contents of laying hens using in vitro gas production study and to elucidate the mechanism behind it. The study consisted of a control (without sodium butyrate), and three experimental groups added with 10, 15, and 20 mg of sodium butyrate, respectively. Results showed that ammonia production in headspace of the syringe decreased by 8.2, 23, and 23 %, respectively, while ammonium production from the fermentation broth decreased by 6.3, 14.4, and 13.7 %, respectively. Sodium butyrate had no significant effect on the contents of uric acid and urea, nitrate-N, or total N in all treatments. However, sodium butyrate decreased the urease and uricase activities (P
There has been increasing concern over the toxic effects of microplastics (MP), nanoplastics (NP), and copper (Cu) on microalgae. However, the combined toxicity of the metal in the presence of polystyrene (PS) MP/NP on microalgae has not been well studied, particularly after long-term exposure (i.e., longer than 4 days). The primary aim of the present study was to investigate the effect of PS MP and NP on Cu toxicity on two freshwater microalgae, namely Chlorella sp. TJ6-5 and Pseudokirchneriella subcapitata NIES-35 after acute exposure for 4 days and up to 16 days. The results showed that both microalgae were sensitive to Cu, but tolerant to MP/NP. However, MP/NP increased the toxicity of Cu at EC50 in both microalgae, which was only noticeable in chronic exposure. Single and combined treatment of MP/NP and Cu induced higher oxidative stress and caused morphological and ultrastructural changes in both microalgae. The adsorption of Cu to MP and NP was low (0.23-14.9%), with most of the Cu present in free ionic form (81.6-105.8%). The findings on different sensitivity of microalgae to Cu in the presence of MP/NP may have significant implication as microalgae are likely to be exposed to a mixture of both MP/NP and Cu in the environment. For example, in air-blasting technology, MP and NP are used as abrasive medium to remove Cu-containing antifouling paints on hulls of ship and submerged surfaces. Wastewater treatment plants receive household wastes containing MP and NP, as well as stormwater runoffs and industrial wastes contaminated with heavy metals.
Sago bark (SB) and empty fruit bunch (EFB) are available abundantly as agricultural waste in Sarawak. This study was conducted to investigate the physicochemical characteristics of SB and EFB as composting materials and used as a plant growth medium. The SB and EFB composts were prepared in a separate container by mixing chicken manure as compost accelerator and wood chips as a bulking agent in dry weight equivalent ratio (1:1:1). The maturity and stability of compost in 60-day composting periods were evaluated via physicochemical characterization of the composts in terms of pH, elemental content, total ash content, moisture content and nutrient analyses. The effect of the compost usage as growth medium was assessed towards water spinach and green mustard via seed germination and pot study. After 2 months, the colour of both composts was dark brown with an earthy smell. The acidic pH of the initial composting stage has changed into alkaline pH after 60 days of composting. Total NPK present in the SB and EFB composts were 0.96% and 1.21%, respectively. The germination index (GI) for the studied vegetables was above 100%, while the pot study showed that vegetables in compost media has higher growth compared to the control, after 14 days. SB and EFB are renewable waste which can be used as an excellent compost and able to improve the quality of the soil.
Pandemics leave their mark quickly. This is true for all pandemics, including COVID-19. Its multifarious presence has wreaked havoc on people's physical, economic, and social life since late 2019. Despite the need for social science to save lives, it is also critical to ensure future generations are protected. COVID-19 appeared as the world grappled with the epidemic of climate change. This study suggests policymakers and practitioners address climate change and COVID-19 together. This article offers a narrative review of both pandemics' impacts. Scopus and Web of Science were sought databases. The findings are reported analytically using important works of contemporary social theorists. The analysis focuses on three interconnected themes: technology advancements have harmed vulnerable people; pandemics have macro- and micro-dimensions; and structural disparities. To conclude, we believe that collaborative effort is the key to combating COVID-19 and climate change, while understanding the lessons learnt from the industrialised world. Finally, policymakers can decrease the impact of global catastrophes by addressing many socioeconomic concerns concurrently.
Extensive contamination of soils by highly recalcitrant contaminants such as polycyclic aromatic hydrocarbons (PAHs) is an environmental problem arising from rapid industrialisation. This work focusses on the remediation of soil contaminated with 3- and 4-aromatic ring PAHs (phenanthrene (PHE) and fluoranthene (FLUT)) through catalysed hydrogen peroxide propagation (CHP). In the present work, the operating parameters of the CHP treatment in packed soil column was optimised with central composite design (H2O2/soil 0.081, Fe(3+)/soil 0.024, sodium pyrophosphate (SP)/soil 0.024, pH of SP solution 7.73). The effect of contaminant aging on PAH removals was also investigated. Remarkable oxidative PAH removals were observed for the short aging and extended aging period (up to 86.73 and 70.61 % for PHE and FLUT, respectively). The impacts of CHP on soil biological, chemical and physical properties were studied for both spiked and aged soils. Overall, the soil functionality analyses after the proposed operating condition demonstrated that the values for soil respiration, electrical conductivity, pH and iron precipitation fell within acceptable limits, indicating the compatibility of the CHP process with land restoration.
The oil palm kernel shell biochar (OPKS-B) and oil palm kernel shell activated carbon (OPKS-AC) were used as a framework to entrap urea using adsorption method. Batch adsorption studies were performed to gauge the influence of contact time on the adsorption of urea onto both OPKS-B and OPKS-AC. To evaluate the physicochemical traits of the studied materials, energy dispersive X-ray spectrometer (EDS), N2-sorption, X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FESEM), elemental analysis, differential thermal gravity (TG/DTG) and thermal gravity were applied. Result shows OPKS-AC has a better sorption capacity for urea compared to OPKS-B. The Langmuir isotherm model better justified the sorption isotherms of urea. For the adsorption process for both OPKS-B and OPKS-AC, the pseudo-second-order kinetic model was picked as it best fitted the experimental sorption outcome with the superior R2 values of > 65.1% and > 74.5%, respectively. The outcome of the experiments showcased that the maximum monolayer adsorption capacity of the OPKS-AC towards urea was 239.68 mg/g. OPKS-AC has showed promising attributes to be picked as an organic framework in the production of controlled release urea fertiliser for a greener and environmentally friendly agricultural practices.
Hydrogeochemical understanding of groundwater is essential for the effective management of groundwater. This study has been carried out to have concrete data for the seasonal variations in hydrogeochemistry of groundwater in central Tamilnadu forming a complex geological terrain with a varied lithology. A total of 244 groundwater samples were collected during four different seasons, viz, southwest monsoon (SWM), summer (SUM), postmonsoon (POM), and northeast monsoon (NEM) from bore wells. The physical parameters such as pH, temperature, TDS, ORP, humidity, and electrical conductivity (EC) were measured insitu, whereas major ions were analyzed in the lab adopting standard procedures. Overall, higher EC and NO3 values were observed and exceeded the WHO permissible limit irrespective of seasons, except for NO3 in SWM. Na and HCO3 are the dominant cation and anion in the groundwater irrespective of seasons. The highest average values of Na (65.06 mg L-1) and HCO3 (350.75 mg L-1) were noted during SWM. Statistical analysis was carried out to elucidate the hydrogeochemistry of the region. Initially, to understand the ionic relationship, correlation matrix was used followed by factor analysis for determination of major geochemical control and later factor scores were derived to understand the regional representations. An attempt has also been made to identify the samples influenced by multiple geochemical processes and to understand their spatial variation in the study period. Correlation of geochemical parameters reveals a excellent positive correlation between Ca and NO3 in SUM, SWM, and NEM due to the dominant of anthropogenic sources and minor influence of weathering process. Strongly loaded factor scores are found to be mostly in the following order POM > NEM > SWM > SUM. Principal component analysis of different seasons indicates the interplay of natural weathering and anthropogenic factors. Overall, the predominant geochemical processes in this region, irrespective of seasons are weathering and, ion exchange and anthropogenic activities.
The occurrence and fate of antibiotic compounds in water can adversely affect human and animal health; hence, the removal of such substrates from soil and water is indispensable. Herein, we described the synthesis method of mesoporous carbon (MPC) via the pyrolysis route from a coordination polymer Fe-based MIL-53 (or MIL-53, shortly). The MPC structure was analyzed by several physical techniques such as SEM, TEM, BET, FT-IR, VSM, and XRD. The response surface methodology (RSM) was applied to find out the effects of initial concentration, MPC dosage, and pH on the removal efficiency of trimethoprim (TMP) and sulfamethoxazole (SMX) antibiotics in water. Under the optimized conditions, the removal efficiencies of TMP and SMX were found to be 87% and 99%, respectively. Moreover, the adsorption kinetic and isotherm studies showed that chemisorption and the monolayer adsorption controlled the adsorption process. The leaching test and recyclability studies indicated that the MPC structure was stable and can be reused for at least four times without any considerable change in the removal efficiency. Plausible adsorption mechanisms were also addressed in this study. Because of high maximum adsorption capacity (85.5 mg/g and 131.6 mg/g for TMP and SMX, respectively) and efficient reusability, MPC is recommended to be a potential adsorbent for TMP and SMX from water media.
The study tries to discover the impact of financial and social indicators' growth towards environmental considerations to understand the drivers of economic growth and carbon dioxide emissions change in G7 countries. The DEA-like composite index has been used to examine the tradeoff between financial and social indicator matters in environmental consideration by using a multi-objective goal programming approach. The data from 2008 to 2018 is collected from G-7 countries. The results from the DEA-like composite index reveals that there is a mixed condition of environmental sustainability in G-7 countries where the USA is performing better and Japan is performing worse among the set of other countries. The further result shows that the energy and fiscal indicators help to decrease the dangerous gas emissions. Divergent to that, the human and financial index positively contributes to greenhouse gas emissions. Fostering sustainable development is essential to successfully reduce emissions, meet established objectives, and ensure steady development. The study provides valuable information for policymakers.
A comprehensive study of the chemical composition of rainwater was carried out from October 2016 to September 2017 in the equatorial tropical rainforest region of northwestern Borneo. Monthly cumulative rainwater samples were collected from different locations in the Limbang River Basin (LRB) and were later categorized into seasonal samples representing northeast monsoon (NEM), southwest monsoon (SWM), and inter-monsoon (IM) periods. Physical parameters (pH, EC, TDS, DO, and turbidity), major ions (HCO3-, Cl-, Ca2+, Mg2+, Na+, and K+) and trace metals (Co, Ni, Cd, Fe, Mn, Pb, Zn, and Cu) were analyzed from collected rainwater samples. Rainwater is slightly alkaline with mean pH higher than 5.8. Chloride and bicarbonate are the most abundant ions, and the concentration of major ions in seasonal rainwater has shown slight variation which follows a descending order of HCO3-> Cl-> Na+ > Ca2+ > Mg2+ > K+ in NEM and Cl- > HCO3- > Na+ > Ca2+ > K+ > Mg2+ in SWM and Cl- > HCO3- > Na+ > Ca2+ > Mg2+ > K+ in IM period. Trace metals such as Fe and Ni have shown dominance in seasonal rainwater samples, and all the metals have shown variation in concentration in different seasons. Variation in chemical characteristic of seasonal rainwater samples identified through piper diagram indicates dominance of Ca2+-Mg2+-HCO3- and mixed Ca2+-Mg2+-Cl- facies during NEM, SWM, and IM periods. Statistical analysis of the results through two-way ANOVA and Pearson's correlation also indicates significant variation in physico-chemical characteristics. This suggests a variation in contributing sources during the monsoon seasons. Factor analysis confirmed the source variation by explaining the total variance of 79.80%, 90.72%, and 90.52% with three factor components in NEM, SWM, and IM rainwater samples with different loading of parameters. Enrichment factor analysis revealed a combined contribution of marine and crustal sources except K+ which was solely from crustal sources. Sample analysis of backward air mass trajectory supports all these findings by explaining seasonal variation in the source of pollutants reaching the study area. Overall, the results show that the chemical composition of seasonal rainwater samples in LRB was significantly influenced by natural as well as anthropogenic processes. These include (long-range and local) industrial activities, fossil fuel combustion, forest burning, transportation activities including road transport and shipping activities, and land-derived soil dust along with chemical constituents carried by seasonal wind.
The introduction of bioactive glasses (BGs) precipitated a paradigm shift in the medical industry and opened the path for the development of contemporary regenerative medicine driven by biomaterials. This composition can bond to live bone and can induce osteogenesis by the release of physiologically active ions. 45S5 BG products have been transplanted effectively into millions of patients around the world, primarily to repair bone and dental defects. Over the years, many other BG compositions have been introduced as innovative biomaterials for repairing soft tissue and delivering drugs. When research first started, many of the accomplishments that have been made today were unimaginable. It appears that the true capacity of BGs has not yet been realized. Because of this, research involving BGs is extremely fascinating. However, to be successful, it requires interdisciplinary cooperation between physicians, glass chemists, and bioengineers. The present paper gives a picture of the existing clinical uses of BGs and illustrates key difficulties deserving to be faced in the future. The challenges range from the potential for BGs to be used in a wide variety of applications. We have high hopes that this paper will be of use to both novice researchers, who are just beginning their journey into the world of BGs, as well as seasoned scientists, in that it will promote conversation regarding potential additional investigation and lead to the discovery of innovative medical applications for BGs.
Air pollution has a serious and adverse effect on human health, and it has become a risk to human welfare and health throughout the globe. One of the major effects of air pollution on health is hospitalizations associated with air pollution. Recently, the estimation and prediction of air pollution-based hospitalization is carried out using artificial intelligence (AI) and machine learning (ML) techniques, i.e., deep learning and long short-term memory (LSTM). However, there is ample room for improvement in the available applied methodologies to estimate and predict air pollution-based hospital admissions. In this paper, we present the modeling and analysis of air pollution and cardiorespiratory hospitalization. This study aims to investigate the association between cardiorespiratory hospitalization and air pollution, and predict cardiorespiratory hospitalization based on air pollution using the artificial intelligence (AI) techniques. We propose the enhanced long short-term memory (ELSTM) model and provide a comparison with other AI techniques, i.e., LSTM, DL, and vector autoregressive (VAR). This study was conducted at seven study locations in Klang Valley, Malaysia. The utilized dataset contains the data from January 2006 to December 2016 for five study locations, i.e., Klang (KLN), Shah Alam (SA), Putrajaya (PUJ), Petaling Jaya (PJ), and Cheras, Kuala Lumpur (CKL). The dataset for Banting contains data from April 2010 to December 2016, and the data for Batu Muda, Kuala Lumpur, contains data from January 2009 to December 2016. The prediction results show that the ELSTM model performed significantly better than other models in all study locations, with the best RMSE scores in Klang study location (ELSTM: 0.002, LSTM: 0.013, DL: 0.006, VAR: 0.066). The results also indicated that the proposed ELSTM model was able to detect and predict the trends of monthly hospitalization significantly better than the LSTM and other models in the study. Hence, we can conclude that we can utilize AI techniques to accurately predict cardiorespiratory hospitalization based on air pollution in Klang Valley, Malaysia.
Terrestrial anionic surfactants (AS) enter the marine environment through coastal region. Despite that, in general limited knowledge is available on the coastal AS transfer pathway. This paper aims to assess the distributions and exchange of AS in the Peninsular Malaysia coastal environments, adjacent to the southern waters of South China Sea and Strait of Malacca. An assessment case study was conducted by a review on the available data from the workgroup that span between the year 2008 and 2019. The findings showed that AS dominated in the sea surface microlayer (SML, 57%) compared to subsurface water (SSW, 43 %). AS were also found to have dominated in fine mode (FM, 71 %) compared to coarse mode (CM, 29 %) atmospheric aerosols. SML AS correspond to the SSW AS (p < 0.01); however, highest enrichment factor (EF) of the SML AS was not consistent with highest SSW AS. Direct AS exchange between SML and FM and CM was not observed. Furthermore, the paper concludes AS mainly located in the SML and FM and could potentially be the main transfer pathway in the coastal environment.