Sulfites play imperative roles in food crops and food products, serving as sulfur nutrients for food crops and as food additives in various foods. It is necessary to develop an effective method for the on-site quantification of sulfites in food samples. Here, 7-(diethylamino) quinoline is used as a fluorescent group and electron donor, alongside the pyridinium salt group as an electron acceptor and the C=C bond as the sulfite-specific recognition group. We present a novel fluorescent sensor based on a mechanism that modulates the efficiency of intramolecular charge transfer (ICT), CY, for on-site quantitative measurement of sulfite in food. The fluorescent sensor itself exhibited fluorescence in the near-infrared light (NIR) region, effectively minimizing the interference of background fluorescence in food samples. Upon exposure to sulfite, the sensor CY displayed a ratiometric fluorescence response (I447/I692) with a high sensitivity (LOD = 0.061 μM), enabling accurate quantitative measurements in complex food environments. Moreover, sensor CY also displayed a colorimetric response to sulfite, making sensor CY measure sulfite in both fluorescence and colorimetric dual-signal modes. Sensor CY has been utilized for quantitatively measuring sulfite in red wine and sugar with recoveries between 99.65% and 101.90%, and the RSD was below 4.0%. The sulfite concentrations in live cells and zebrafish were also monitored via fluorescence imaging. Moreover, the sulfite assimilated by lettuce leaves was monitored, and the results demonstrated that excessive sulfite in leaf tissue could lead to leaf tissue damage. In addition, the sulfate-transformed sulfite in lettuce stem tissue was tracked, providing valuable insights for evaluating sulfur nutrients in food crops. More importantly, to accomplish the on-site quantitative measurement of sulfite in food samples, a portable sensing system was prepared. Sensor CY and the portable sensing system were successfully used for the on-site quantitative measurement of sulfite in food.

The new technologies used in the green transition towards carbon-free societies typically demand extensive use of metals. This leads to a heavily growing need for exploration and extraction of ore deposits. Exploration can be facilitated by measuring metal concentrations in ground and surface waters carrying trace concentrations of metals leached from nearby deposits. Currently, measuring metal concentrations in water is slow and expensive and it cannot be done on-site, which hinders the discovery of new ore deposits. To address this challenge, we have developed a method to collect and concentrate the dissolved metals in a solid filter and measure the metal concentrations directly from the filter with a portable X-ray fluorescence spectrometer. The permeable filter is made of mesoporous silicon modified with bisphosphonates. Two types of adsorbing materials for the filters were prepared based on scalable production methods: i) regenerative etching of metallurgical grade silicon powder, and ii) magnesiothermic reduction of silica from barley husks. Empirical calibrations were prepared in a concentration range of 10-200 μg/L for Mn, Co, Ni, Cu, Zn, and Pb using water samples prepared by spiking well water with standard metal solutions. Both filter types were tested for their ability to adsorb metals from the real water samples taken from drill holes. The developed system was able to detect metal concentrations down to 12 μg/L (ppb) showing its potential for on-site measurements of dissolved metals in water samples, which could be feasible in the discovery of new mineral deposits. This innovation enables smart sampling during exploration and provides real-time information on metal concentrations in water.

Reliable high-resolution data is essential for understanding the aquatic sulfur biogeochemical processes. However, the accurate quantification of total dissolved sulfide (TDS) remains challenging due to its low concentration and vulnerability to oxidation. Furthermore, the frequency and the spatial coverage of TDS measurements are constrained by the cost of the laboratory analysis. In this study, an automated portable system was developed for on-site real-time measurement of trace TDS in natural waters. This system was based on the classic methylene blue (MB) spectrophotometric assay combined with on-line solid phase extraction (SPE) and flow injection analysis (FIA). A commercially available weak-cation-exchange cartridge was used as the SPE sorbent. Experimental parameters affecting the performance of the proposed system were optimized. Under the optimized conditions, linear calibration range of 0.02-2.50 μmol L-1 was obtained with a sample loading volume of 5.0 mL and a sample throughput of 12 h-1. The limit of detection could be lowered to 0.003 μmol L-1 by pre-concentrating 10.0 mL sample. The precision, determined as the relative standard deviation (RSD), was <2.75 % (n = 11) and the recoveries from spiked samples ranged from 54.4 % to 97.5 % with RSDs of 1.1-2.3 % (n = 3). Furthermore, the FIA-SPE-MB system was successfully deployed in the Taihu Lake for continuous 48 h monitoring of variations in TDS, demonstrating the applicability of this system for on-site TDS measurement in natural waters.

Total dissolved sulfide (TDS) plays multiple important roles in the aquatic environments. However, the determination of trace levels of TDS in natural waters is challenging because TDS is vulnerable to oxidation and volatilization. In this study, a fully automated flow injection analysis spectrophotometric system, incorporating a hollow fiber membrane contactor (HFMC) and a long path length liquid waveguide capillary cell, was fabricated to facilitate the on-site measurement of trace TDS in natural waters. The HFMC was used for matrix separation and analyte preconcentration. The measurement was based on the reaction of sulfide and N,N-dimethyl-p-phenylenediamine in the presence of FeCl3 under acidic conditions to yield methylene blue (MB). The proposed method was highly sensitive, with detection and quantification limits of 0.57 and 1.90 nmol L-1, respectively. The linear working range was from 1.90 to 150 nmol L-1, with a correlation coefficient of 0.9995. The repeatability, expressed as the relative standard deviation, was less than 0.86% (n = 15) and the recoveries varied from 76.2 ± 0.1% to 103.9 ± 0.6% (n = 3) for spiked samples. This method was applied to conduct a field analysis of TDS in a reservoir, giving results aligned with those obtained using a standard MB method. This work demonstrates that the new method for determining TDS was effective for both laboratory analysis and on-site measurement.

Quality and safety monitoring in the dairy industry is required to ensure products meet a high-standard based on legislation and customer requirements. The need for non-destructive, low-cost and user-friendly process analytical technologies, targeted at operators (as the end-users) for routine product inspections is increasing. In recent years, the development and advances in sensing technologies have led to miniaturisation of near infrared (NIR) spectrometers to a new era. The new generation of miniaturised NIR analysers are designed as compact, small and lightweight devices with a low cost, providing a strong capability for on-site or on-farm product measurements. Applying portable and handheld NIR spectrometers in the dairy sector is increasing; however, little information is currently available on these applications and instrument performance. As a result, this review focuses on recent developments of handheld and portable NIR devices and its latest applications in the field of dairy, including chemical composition, on-site quality detection, and safety assurance (i.e., adulteration) in milk, cheese and dairy powders. Comparison of model performance between handheld and bench-top NIR spectrometers is also given. Lastly, challenges of current handheld/portable devices and future trends on implementing these devices in the dairy sector is discussed.

The characteristics of heat transfer load from the non-air-conditioned (NAC) area can help to understand the complex airflow movement and thermal physical mechanisms inside large space buildings. Based on building energy modeling, the indoor thermal environment and building energy consumption of a plant for computerized numerical control (CNC) machine tools are studied. Considering the form of the stratified air-conditioning system and the phenomenon of heat retention near the roof in the plant, the double zone and triple zone models are established. The vertical air temperature, the parameters of the terminal of the air-conditioning system and the heat/cool source system of the plant in summer and winter were measured on site, which verifies the accuracy of the established model. Based on the validated model, the proportion of heat transfer load from the NAC area is calculated, at the range of about 60%-85%. The positive influence of the roof heat transfer coefficient on the sensible heat load in the NAC area is revealed. The recommended value of the non-dimensional zone-mixing flow rate between the air-conditioned (AC) and NAC areas is given, with 30% (in summer). The results of this work can help understand the composition of the stratified air-conditioning load in large spaces and optimize the design of air distribution.

Estimation of construction waste generation (CWG) at the field scale is a crucial but challenging task for effective construction waste management (CWM). Extant field-scale CWG modeling approaches have faced difficulties in obtaining accurate results due to a lack of detailed CWG data, and most of them fail to consider the complex relationship among predictive variables. This study attempts to tackle this issue by proposing a novel CWG modeling approach that integrates improved on-site measurement (IOM) and a support vector machine (SVM)-based prediction model. To achieve this goal, 206 ongoing commercial construction sites were investigated to obtain the predictor values and waste generation rates (WGRs) of five types of waste (i.e., inorganic nonmetallic waste, organic waste, metal waste, composite waste, and hazardous waste) generated at three construction stages (i.e., the understructure stage, superstructure stage, and finishing stage). The data were introduced to the SVM to develop the relationships between predictive variables and WGRs. An actual commercial building under construction was used to demonstrate the applicability of the proposed approach. The results showed that the superiority of the IOM can be used as a basis to implement robust CWG data collection. In addition, the SVM-based WGR prediction model (SWPM) can obtain more accurate prediction results (R2 = 86.87%) than the back-propagation neural network (R2 = 75.14%) and multiple linear regression (R2 = 61.93%).

Recently, there has been a growing demand to develop portable devices for the fast detection of contaminants in food safety, healthcare, and environmental fields. Herein, two biosensing methods were designed by the use of nicotinamide adenine dinucleotide phosphate (NAD(P)H)-dependent TetX2 enzyme activity and thionine as an excellent electrochemical and colorimetric mediator/probe to monitor tetracycline (TC) in milk. The nanoporous glassy carbon electrode (NPGCE) modified with polythionine was first prepared by electrochemically and then TetX2 was immobilized onto the NPGCE using polyethyleneimine. The prepared biosensor provided a high electrocatalytic response toward NAD(P)H by significantly reducing its overpotential. The proposed biosensor exhibited a detection limit of 40 nM with a linear range of 0.1-0.8 μM for TC determination. Besides, the thionine probe was used to develop a novel colorimetric assay using a simple enzymatic color reaction within a few minutes. The limit of detection for TC was experimentally achieved as 60 nM, which was lower than the safety levels established by the World Health Organization (225 nM). The correlation between change in the color of the solution and the concentration of TC was used for quality control of milk samples, as confirmed by the standard high-performance liquid chromatography method. The results show the great potential of the proposed assays as portable instruments for on-site TC measurements.

Airborne transmission is a main spread mode of respiratory infectious diseases, whose frequent epidemic has brought serious social burden. Identifying possible routes of the airborne transmission and predicting the potential infection risk are meaningful for infectious disease control. In the present study, an internal spread route between horizontal adjacent flats induced by air infiltration was investigated. On-site measurements were conducted, and tracer gas technique was employed. Two measurement scenarios, closed window mode and open window mode, were compared. Using the calculated air change rate and mass fraction, the cross-infection risk was estimated using the Wells-Riley model. It found that tracer gas concentrations in receptor rooms are one order lower than the source room, and the infection risks are also one order lower. Opening windows results in larger air change rate on the one hand, but higher mass fraction on the other hand. Higher mass fraction not necessarily results in higher infection risk as the pathogen concentration in the source room is reduced by the higher air change rate. In the present study, opening windows could significantly reduce the infection risk of the index room but slightly reduce the risks in receptor rooms. The mass fraction of air originated from the index room to the receptor units could be 0.28 and the relative cross-infection risk through the internal transmission route could be 9%, which are higher than the external spread through single-sided window flush. The study implicates that the horizontal transmission route induced by air infiltration should not be underestimated.

OBJECTIVE: To assess the accuracy and influential factors for hypertension prevalence based on questionnaire interview by on-site measurement.
METHODS: Data were from the baseline surveys for chronic diseases among residents ages ≥18 years old in 4 districts/counties of Changsha between 2013 and 2014. All surveys adopted multi-stage random sampling to select samples. The Bootstrap resampling method was used to randomly select 1 000 repeated samples with replacement to obtain robust estimate of subgroup prevalence rates. Hypertension prevalence was calculated by using the data from both questionnaire interview and on-site measurement. Using the results of on-site measurement as the golden standard, the accuracy of questionnaire interview and 95% uncertainty interval were estimated. Multivariate logistic regression was used to investigate the influential factors for the underestimated hypotension prevalence based on questionnaire interview.
RESULTS: The hypertension prevalence from on-site measurement among the residents in the 4 districts/counties of Changsha was significantly higher than that from questionnaire interview (prevalence ratio: 1.26-2.31). Taking the results of on-site measurement as the golden standard, the sensitivity of questionnaire interview on hypotension prevalence range from 41.76% to 74.83% among the 4 districts/counties, and the specificity fell between 98.51% and 99.46%. The underestimation in questionnaire interview was more likely to occur in the youngest age group (18-34 years old), males, and residents were at lower levels of education in all 4 districts/counties.
CONCLUSIONS: Compared with the on-site measurement, questionnaire interview significantly under-estimate the hypertension prevalence, suggesting that the on-site measurement method should be firstly considered in epidemiological surveys for hypertension prevalence. If only the questionnaire method can be used to collect data due to conditions, it is necessary to make corresponding corrections to the questionnaire results with reference to relevant research evidence.
目的: 采用现场检测评价问卷询问所得高血压患病率的准确性，并探讨其影响因素。方法: 资料来自2013至2014年长沙市4个区/县针对≥18岁常住居民的慢性病基线调查资料，4个区/县均采用多阶段随机抽样选择样本。为获取稳定的亚组患病率，利用Bootstrap再抽样方法对样本数据进行1 000次重复抽样，计算基于复杂抽样的问卷询问和现场实测两种方式所得高血压患病率。以现场实测结果为金标准，估算问卷询问结果的准确性及95%不确定区间。采用多因素logistic回归探讨问卷询问方法相对于现场实测低估高血压患病率的影响因素。结果: 长沙市4个区/县居民现场实测的高血压患病率均明显高于问卷询问的高血压患病率(患病率比值：1.26~2.31)。以现场实测结果作为金标准，4个区/县问卷询问所得高血压患病报告的灵敏度为41.76%~74.83%，特异度为98.51%~99.46%。4个区/县问卷询问方式所得的高血压患病率在18~34岁、男性居民和文化程度偏低者中出现低估的可能性更高。结论: 相对于现场实测，问卷询问所得的高血压患病率明显低估，提示流行病学调查应采用现场实测方式估计高血压患病率。若因条件限制仅能采用问卷询问方法收集数据，则需要参照相关研究证据对问卷询问结果进行相应校正。.