CH₄ flux measured by a portable chamber using an infrared analyzer was compared with the flux by static chamber measurement for CW at 13 different sites from May 2012 to May 2017 in the Living Water Garden (LWG) in Chengdu, Sichuan Province, China, over 4 timescales (daily, monthly, seasonal, and annual). During the measurement period, a total of 1443 data were collected. CH₄ fluxes were measured using the portable chamber method and the results showed that the annual mean and median CH₄ flux values in the LWG were 17.4 mg m⁻² h⁻¹ and 6.2 mg m⁻² h⁻¹, respectively, ranging from − 19.7 to 98.0 mg m⁻² h⁻¹. Cumulative CH₄ emissions for LWG ranged from − 0.17 to 0.86 kg m⁻² year⁻¹. Global warming potential (GWP, 25.7 kg CO₂ₑq m⁻² year⁻¹) was at a high level, which means that the LWG was a source of CH₄ emissions. Significant temporal variations on the 4 timescales were observed. And the asymmetry of measurement uncertainty of CH₄ flux increases with the timescale. Although the total mean CH₄ flux measured by the portable chamber method was 42.1% lower than that of the static chamber method, the temporal variation trends of CH₄ flux were similar. The uncertainty of CH₄ flux measured in portable chamber was more symmetrical than that in static chamber. These results suggest that the portable chamber method has considerable value as a long-term measurement method for CH₄ flux temporal variations.

Odor concentrations (OC) and emissions (OE) were measured for a commercial broiler barn and a cage-layer barn in a cold region (the Canadian Prairies). Seasonal OC and OE profiles were plotted by monthly measurements over the course of a year from March 2015 to February 2016, and diurnal profiles were generated by 2-day measurements in cold, mild, and warm seasons, respectively. Seasonal OC and OE varied for both barns; OC was higher in the cold season, but OE was higher in the mild and warm seasons. The broiler barn had higher annual average OC (718 OU m⁻³) but slightly lower annual average OE (127 OU s⁻¹ AU⁻¹; AU is per 500 kg of body mass) than the layer barn (574 OU m⁻³ and 140 OU s⁻¹ AU⁻¹). For the layer barn, OC and OE were reduced by 31% and 33% in the cold season and by 30% and 26% in the mild season after manure removal compared with before manure removal. Statistical results showed increased outdoor temperature and ventilation rate (VR) were associated with decreased OC but increased OE for both barns. Finally, both single linear and multi-linear regression models of OE were developed.

A dead-end ultrafiltration cup was continuously operated to investigate the underlying mechanisms of membrane fouling caused by gel layer in this paper. Anionic polyacrylamide was used as a model foulant for gel formation process in various ultrafiltration processes by two kinds of ultrafiltration membrane, e.g., polyvinylidene fluoride (PVDF) membrane (OM) and TiO₂/Al₂O₃-PVDF membrane (MM); then, a gel formation model was established and systematically assessed. The results show that the gel formation process in ultrafiltration can be divided into three stages: “slow-rapid-slow” flux decay curve. The R² value of the simulation curve was still higher than 0.90 for both OM and MM. Based on the current cognition, the proposed gel layer formation mechanism and mathematical model were feasible.

Particulate matter (PM) is a complex mixture of particles that changes over time and from place to place; however, most PM is caused by the fuel combustion of motor vehicles and industry. PM is associated with acute and chronic illnesses, such as pulmonary and cardiovascular diseases. Medellín is one of the most polluted cities in Latin America. Therefore, the physicochemical characterization of its PM is necessary to understand its composition and effect on human health. In this study, PM was characterized by scanning electron microscopy (SEM), energy dispersive x-ray spectroscopy (EDS) analysis, Fourier infrared spectroscopy (FTIR), inductivity-coupled plasma optical emission spectrometry (ICP-OES), and thermogravimetric analysis (TGA) in order to evaluate its morphology and chemical composition. The SEM of the PM exhibited primary particles and agglomerates. The size of the particles ranged between 0.056 and 4.5 μm. The EDS revealed elements such as carbon, silicon, calcium, lead, and iron. Furthermore, carbon monoxide, carbon dioxide, and carbonyl and aliphatic functional groups were observed by means of FTIR. Additionally, weight losses associated with volatile matter and elemental carbon were identified in the TGA analysis. The TGA and FTIR confirmed the presence of fuel and lubricant traces. Subsequently, lead was selected among the most common components in the PM in order to conduct an in silico study into its effect on ventricular activity. Lead showed a pro-arrhythmic effect by shortening the duration of the action potential under normal electrophysiological conditions, which could be associated with cardiovascular diseases.

A major obstacle to biodiesel commercialization is supplying feedback which increases production costs. The potential of some oleaginous yeast for conversion of waste materials to biodiesel feedstock can overcome this problem. In this study, a potential oleaginous yeast strain was used for single-cell oil (SCO) production. Two sets of experiments were designed for the optimization process. According to the results obtained from the first experiment, lipid production and lipid content of this strain increased from 1.96 g/L and 22.6% to 3.85 g/L and 35.18% by optimization of grass hydrolysis, respectively. The results of the second experiment indicate an increase in SCO production and lipid content to 7.28 g/L and 56.39%, respectively. These results were obtained when HNO₃ was used for substrate pre-treatment. Lipid analysis by gas chromatography-mass spectrometry showed a suitable and high potential of fatty acid profile for biodiesel production, which was then confirmed by evaluating the physicochemical properties of the biodiesel obtained in compliance with the US and EU standards. Consumption of microbial oil and low-cost substrate can compensate the high costs of feedstock in biodiesel production.

Traceability offers significant information about the quality and safety of Chinese Angelica, a medicine and food homologous substance. In this study, a systematic four-step strategy, including sample collection, specific metal element fingerprinting, multivariate statistical analysis, and benefit-risk assessment, was developed for the first time to identify Chinese Angelica based on geographical origins. Fifteen metals in fifty-six Chinese Angelica samples originated from three provinces were analyzed. The multivariate statistical analysis model established, involving hierarchical cluster analysis (HCA), principal component analysis (PCA), and self-organizing map clustering analysis was able to identify the origins of samples. Furthermore, benefit-risk assessment models were created by combinational calculation of chemical daily intake (CDI), hazard index (HI), and cancer risk (CR) levels to evaluate the potential risks of Chinese Angelica using as traditional Chinese medicine (TCM) and food, respectively. Our systematic strategy was well convinced to accurately and effectively differentiate Chinese Angelica based on geographical origins.

Considering the importance of green economic growth and environmental sustainability in the discussion, it is crucial to understand its critical contributing factors and to draw results implications for the green policy. This research used the data of the South Asian Association for Regional Cooperation (SAARC) member countries for a period from 2005 to 2017. It adopted the panel autoregressive distributed lag technique to examine the hypotheses. The findings revealed that environmental sustainability is strongly and positively associated with national scale-level green practices, including renewable energy, regulatory pressure, and eco-friendly policies, and sustainable use of natural resources. Conversely, in our model, the “regulatory pressure” has an insignificant effect on economic growth. A necessary contribution of the present study is that a positive effect of green practices on national scale economic and environmental variables, particularly in the scenario of SAARC member states, can be noticed. At the end of the present study, we have provided policy implications for regulatory authorities and discussed potential areas for future research.

TiO₂-based heterogeneous photocatalysis systems have been reported with remarkable efficiency to decontaminate and mineralize a range of pollutants present in air and water medium. In the present study, a series of visible light active metal oxide TiO₂ nanoparticle were synthesized and evaluated for their photodegradation efficiency against emerging textile pollutant (Reactive Yellow 145) and antibacterial applications. In the first phase, nanomaterial synthesis was carried out following various synthesis parameters like addition of metallic impurities (different types and concentration) and calcination temperature. In the second phase, synthesized nanomaterials were screened for their performance in terms of photocatalytic degradation of RY145 and the best one (Fe-1-T-3 with 100% RY145 removal within 80 min of irradiation) was further optimized against various reaction parameters. To get knowledge about the insights of nanomaterial performance for degradation of different environmental pollutants, the most important is to understand their physicochemical properties utilizing different characterization techniques. The physical morphology and elemental dispersion of metal-doped TiO₂ nanomaterials were analyzed and results indicated that added metallic impurities were well dispersed onto the substrate surface. The efficient nanomaterials selected from initial screening were further assessed for photocatalytic disinfection efficiency against human pathogenic bacterial strains. Antimicrobial activities of the metal oxide nanomaterial were tested against gram-positive and gram-negative pathogenic bacterial strains. Possible mode of interaction of nanomaterial with bacterial DNA for bacterial cell inactivation was predicted using molecular docking simulation. The research project has the potential to contribute to multiple disciplines like material synthesis, water disinfection, and as green solutions for the textile industry replacing traditional technologies.

The use of sewage water as an irrigation source can be beneficial in agricultural practices, however, it may result in human health risks due to the consumption of heavy metal(loid)–contaminated food. This study evaluated the suitability of using sewage water (SW), freshwater (FW), and groundwater (GW) for vegetable irrigation in District Vehari. Spinach (Spinacia oleracea) plants were grown in pots irrigated with FW, GW, and SW in different proportions and combinations. The results indicated the substantial lesser buildup of heavy metal(loid)s (As (− 0.8%), Cd (− 38%), Cr (− 6.2%), Cu (− 20%), Fe (− 9.2%), Mn (− 13%), Ni (− 16%), Pb (− 19%), and Zn (−15%)) in soil after S. oleracea cultivation compared to unirrigated soil possibly due to high metal(loid) uptake by S. oleracea. Irrigation with all types of waters resulted in metal(loid) accumulation in S. oleracea predominantly in roots. The combinations of FW, GW, and SW resulted in high metal(loid) accumulation (As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) in the edible S. oleracea leaves than their alone application. Owing to high metal(loid) buildup, plants showed a linear trend in physiological imbalance in terms of reduced pigment content, induction of peroxidation, and oxidation of lipids. The severe oxidative stress was observed in S. oleracea plants under FW and GW irrigation due to high metal(loid) accumulation. The risk indices showed possible carcinogenic risk (CR > 0.0001) and non-carcinogenic risk (HI > 1) from the consumption of metal(loid)-contaminated S. oleracea leaves. Results revealed unsuitability of all waters and their combinations for S. oleracea irrigation. Moreover, this study does not encourage the use of mixed water for vegetable irrigation in Vehari District. Therefore, it is of utmost importance to monitor the quality of irrigation waters to ensure food safety and prevent chronic health risks to the exposed population.

The industry sector is not only an important driving force for economic growth but also the largest sector of resource consumption and pollution emission. In this study, we first constructed a super-slack-based measure (Super-SBM) model including the resource consumption and undesirable outputs, and estimated the industrial environmental efficiency (IEE) in China from 2007 to 2016. Afterwards, based on the spatial autocorrelation test and the spatial Durbin model, the spatio-temporal evolution and the influencing factors of IEE were analyzed. The empirical results are obtained as follows: the average IEE from 2007 to 2016 was 0.5176. IEE in the east of China was the highest, whereas it was the lowest in the west. The spatial autocorrelation test showed that the regions with similar levels of IEE in China had significant spatial agglomeration, whereas the local spatial distribution of IEE was unbalanced. The high-high IEE agglomeration areas were located in Liaoning, Jilin, and Inner Mongolia. The low-low IEE agglomeration areas were concentrated in Gansu, Ningxia, and Sichuan. Finally, according to the spatial Durbin panel model and spillover effect decomposition, GDP, FDI, human capital, environmental governance investment, research and development investment, and urbanization have a positive impact on IEE. The industrial and energy consumption structures have a negative impact on IEE. Therefore, the central government should focus on balancing IEE of different provinces and regions, increasing investment in industrial pollution treatment, and encouraging FDI to improve IEE.