Development and validation of LC-MS/MS method for the determination of Ochratoxin A and its metabolite Ochratoxin α in poultry tissues and eggs

The objective of this study was to develop a liquid chromatography tandem mass spectrometry (LC-MS/MS) method for the determination of Ochratoxin A (OTA) and Ochratoxin α (OTα) in poultry tissues and eggs. The two toxins were extracted by a mixture of acetonitrile/water, purified with a reversed phase C18 solid phase extraction column (SPE) and determined by LC-MS/MS. The LC-MS/MS method performances were evaluated in terms of linearity in solvent and in matrix (ranged from 0.5 to 15.10 µg L^?1 for OTA and from 0.60 to 17.85 µg L^?1 for OTα), limit of detection (LOD), limit of quantitation (LOQ), specificity, accuracy and precision in repeatability conditions. Recovery experiments were performed by spiking poultry liver, kidney, muscle and eggs around 1 µg kg^?1 and 10 µg kg^?1. LODs were 0.27 and 0.26 µg kg^?1 while LOQs were fixed at 1.0 and 1.2 µg kg^?1 for OTA and OTα, respectively. Main recoveries for OTA ranged from 82 to 109% and for OTα ranged from 55 to 89%. The values of within-laboratory relative standard deviation (RSD_r) were equal to or below 20%. Considering the results obtained and that all analytical performance criteria were fulfilled, the new extraction and purification method developed for OTA and OTα determination in animal tissues and eggs was found appropriate for control laboratories and research activities designed to ensure food safety.     

Development of visibility forecasting modeling framework for the Lower Fraser Valley of British Columbia using Canada’s Regional Air Quality Deterministic Prediction System

Visibility degradation, one of the most noticeable indicators of poor air quality, can occur despite relatively low levels of particulate matter when the risk to human health is low. The availability of timely and reliable visibility forecasts can provide a more comprehensive understanding of the anticipated air quality conditions to better inform local jurisdictions and the public. This paper describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada’s operational Regional Air Quality Deterministic Prediction System (RAQDPS) for the Lower Fraser Valley of British Columbia. A baseline model (GM-IMPROVE) was constructed using the revised IMPROVE algorithm based on unprocessed forecasts from the RAQDPS. Three additional prototypes (UMOS-HYB, GM-MLR, GM-RF) were also developed and assessed for forecast performance of up to 48 hr lead time during various air quality and meteorological conditions. Forecast performance was assessed by examining their ability to provide both numerical and categorical forecasts in the form of 1-hr total extinction and Visual Air Quality Ratings (VAQR), respectively. While GM-IMPROVE generally overestimated extinction more than twofold, it had skill in forecasting the relative species contribution to visibility impairment, including ammonium sulfate and ammonium nitrate. Both statistical prototypes, GM-MLR and GM-RF, performed well in forecasting 1-hr extinction during daylight hours, with correlation coefficients (R) ranging from 0.59 to 0.77. UMOS-HYB, a prototype based on postprocessed air quality forecasts without additional statistical modeling, provided reasonable forecasts during most daylight hours. In terms of categorical forecasts, the best prototype was approximately 75 to 87% correct, when forecasting for a condensed three-category VAQR. A case study, focusing on a poor visual air quality yet low Air Quality Health Index episode, illustrated that the statistical prototypes were able to provide timely and skillful visibility forecasts with lead time up to 48 hr.

Implications: This study describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada’s operational Regional Air Quality Deterministic Prediction System. The main applications include tourism and recreation planning, input into air quality management programs, and educational outreach. Visibility forecasts, when supplemented with the existing air quality and health based forecasts, can assist jurisdictions to anticipate the visual air quality impacts as perceived by the public, which can potentially assist in formulating the appropriate air quality bulletins and recommendations.     

The probabilistic tsunami hazard assessment along Karnataka Coast from Makran Subduction Zone,west coast of India

Coastal tsunami amplitudes were calculated to identify areas susceptible to tsunami hazard at selected locations of the coast of Karnataka, west of India, due to earthquakes in the Makran Subduction Zone. This is the first time that the probabilistic tsunami hazard assessment along this study area has been attempted. A series of earthquake source scenarios with magnitudes of Mw 8.0, Mw 8.5, and a mega thrust of Mw 9.1 were modeled by using the Community Model Interface for Tsunami interface with the MOST model of Titov and Synolakis (J. Waterway, Port, Coastal and Ocean Engineering, 121(6), 308–316, 1995). As per the previous occurrences, the two least magnitudes are probable, while Mw 9.1 is a worst-case scenario as described by Heidarzadeh et al. (Ocean Engineering, 36(5), 368–376, 2009) and the same is reported by Burbidge et al. (Geoscience Australia Professional Opinion No. 2009/11) as high magnitude. These are not at all historical earthquakes or specifically from historical catalogues. The results of modeling show that all the seven coastal locations are inundated barely in our worst-case scenario with maximum water levels in the range of 100–200 cm. The first tsunami wave strikes the coast within 4–5 h of earthquake occurrence.     

Real<Emphasis Type="Bold">-</Emphasis>time water quality monitoring using Internet of Things in SCADA

Water pollution is the root cause for many diseases in the world. It is necessary to measure water quality using sensors for prevention of water pollution. However, the related works remain the problems of communication, mobility, scalability, and accuracy. In this paper, we propose a new Supervisory Control and Data Acquisition (SCADA) system that integrates with the Internet of Things (IoT) technology for real-time water quality monitoring. It aims to determine the contamination of water, leakage in pipeline, and also automatic measure of parameters (such as temperature sensor, flow sensor, color sensor) in real time using Arduino Atmega 368 using Global System for Mobile Communication (GSM) module. The system is applied in the Tirunelveli Corporation (Metro city of Tamilnadu state, India) for automatic capturing of sensor data (pressure, pH, level, and energy sensors). SCADA system is fine-tuned with additional sensors and reduced cost. The results show that the proposed system outperforms the existing ones and produces better results. SCADA captures the real-time accurate sensor values of flow, temperature, and color and turbidity through the GSM communication.     

Use of water quality index and multivariate statistical techniques for the assessment of spatial variations in water quality of a small river

Rapid urban development has led to a critical negative impact on water bodies flowing in and around urban areas. In the present study, 25 physiochemical and biological parameters have been studied on water samples collected from the entire section of a small river originating and ending within an urban area. This study envisaged to assess the water quality status of river body and explore probable sources of pollution in the river. Weighted arithmetic water quality index (WQI) was employed to evaluate the water quality status of the river. Multivariate statistical techniques namely cluster analysis (CA) and principal component analysis (PCA) were applied to differentiate the sources of variation in water quality and to determine the cause of pollution in the river. WQI values indicated high pollution levels in the studied water body, rendering it unsuitable for any practical purpose. Cluster analysis results showed that the river samples can be divided into four groups. Use of PCA identified four important factors describing the types of pollution in the river, namely (1) mineral and nutrient pollution, (2) heavy metal pollution, (3) organic pollution, and (4) fecal contamination. The deteriorating water quality of the river was demonstrated to originate from wide sources of anthropogenic activities, especially municipal sewage discharge from unplanned housing areas, wastewater discharge from small industrial units, livestock activities, and indiscriminate dumping of solid wastes in the river. Thus, the present study effectively demonstrates the use of WQI and multivariate statistical techniques for gaining simpler and meaningful information about the water quality of a lotic water body as well as to identify of the pollution sources.     

Method optimization to measure polybrominated diphenyl ether (PBDE) concentrations in soils of Bratislava, Slovakia

We modified an analytical method to determine polybrominated diphenyl ethers (PBDEs) in urban soils of Bratislava (Slovakia). Gel permeation chromatography (GPC) introduced as a clean-up step for soil extracts substantially reduced matrix enhancements when PBDEs were measured with gas chromatography-negative chemical ionization-mass spectrometry (GC-NCI-MS). The resulting method proved to be accurate, precise, and showed low detection limits. The sum of 15 PBDE concentrations in surface horizons of Bratislava soils ranged from 87 to 627 pg g⁻¹. PBDE concentrations were mostly higher in surface than deeper horizons probably because of atmospheric deposition and lack of substantial vertical transport. Lower brominated PBDEs undergo more soil-atmosphere exchanges or are more scavenged and transferred with litter fall to the soil organic matter than higher brominated ones as suggested by the correlation between lower brominated PBDEs and soil organic C (C_org) concentrations.     

An assessment of ecosystem services of Corbett Tiger Reserve,India

This paper examines the economic value of selected ecosystem services of Corbett Tiger Reserve, India. The direct cost was derived from secondary sources, and indirect and opportunity costs through socioeconomic surveys. For recreational value the individual approach to travel cost method was used, and to assess carbon sequestration the replacement cost method was used. The maintenance cost of the reserve was estimated as US $2,153,174.3 year⁻¹. The indirect costs in terms of crop and livestock depredation by wild animals ranged from US $2,153,174.3 year⁻¹. The indirect costs in terms of crop and livestock depredation by wild animals ranged from US 2,408 to US $37,958 village⁻¹ over a period of 5 years. The dependence of local communities was for fuel wood (US $37,958 village⁻¹ over a period of 5 years. The dependence of local communities was for fuel wood (US 7,346 day⁻¹), fodder (US $5,290 day⁻¹), small timber, and other nontimber forest products. The recreational value of the reserve was estimated as US $5,290 day⁻¹), small timber, and other nontimber forest products. The recreational value of the reserve was estimated as US 167,619 year⁻¹. With the cost per visitor being US $2.5, the consumers’ surplus was large, showing the willingness of visitors to pay for wildlife recreation. The forests of the reserve mitigate carbon worth US $2.5, the consumers’ surplus was large, showing the willingness of visitors to pay for wildlife recreation. The forests of the reserve mitigate carbon worth US 63.6 million, with an annual flow of US $65.0 ha⁻¹ year⁻¹. The other benefits of the reserve include US $65.0 ha⁻¹ year⁻¹. The other benefits of the reserve include US 41 million through generation of electricity since 1972. The analysis reveals that, though the benefits outweigh costs, they need to be accrued to local communities so as to balance the distribution of benefits and costs.     

Informal e-waste recycling: environmental risk assessment of heavy metal contamination in Mandoli industrial area,Delhi, India

Nowadays, e-waste is a major source of environmental problems and opportunities due to presence of hazardous elements and precious metals. This study was aimed to evaluate the pollution risk of heavy metal contamination by informal recycling of e-waste. Environmental risk assessment was determined using multivariate statistical analysis, index of geoaccumulation, enrichment factor, contamination factor, degree of contamination and pollution load index by analysing heavy metals in surface soils, plants and groundwater samples collected from and around informal recycling workshops in Mandoli industrial area, Delhi, India. Concentrations of heavy metals like As (17.08 mg/kg), Cd (1.29 mg/kg), Cu (115.50 mg/kg), Pb (2,645.31 mg/kg), Se (12.67 mg/kg) and Zn (776.84 mg/kg) were higher in surface soils of e-waste recycling areas compared to those in reference site. Level exceeded the values suggested by the US Environmental Protection Agency (EPA). High accumulations of heavy metals were also observed in the native plant samples (Cynodon dactylon) of e-waste recycling areas. The groundwater samples collected form recycling area had high heavy metal concentrations as compared to permissible limit of Indian Standards and maximum allowable limit of WHO guidelines for drinking water. Multivariate analysis and risk assessment studies based on total metal content explains the clear-cut differences among sampling sites and a strong evidence of heavy metal pollution because of informal recycling of e-waste. This study put forward that prolonged informal recycling of e-waste may accumulate high concentration of heavy metals in surface soils, plants and groundwater, which will be a matter of concern for both environmental and occupational hazards. This warrants an immediate need of remedial measures to reduce the heavy metal contamination of e-waste recycling sites.