Improved Source Identification Research Articles

Real-time measurement of metals in submicron aerosols with particle-into-liquid sampler combined with micro-discharge optical emission spectroscopy.

The paper presents a novel technique for quantifying trace metals in aerosol samples in real time. Airborne metals were continuously collected for one week near the Baltic Sea in Finland using a particle-into-liquid sampler (PILS). The collected liquid samples were analyzed for metals using micro-discharge optical emission spectroscopy (µDOES). The micro-discharge analyzer is designed to perform real-time, on-site measurements of metal concentrations in aqueous solutions. Currently, µDOES can provide online measurements of 30 metals, with typical detection limits from 0.01µg/m3 to 0.06µg/m3 with a long-term repeatability less than 5%. The novelty of this analyzer lies in its compact design, rapid detection capabilities, and ease of operation and maintenance. Several metals, including potassium (K), calcium (Ca), sodium (Na), aluminum (Al), magnesium (Mg), and copper (Cu), were measured in the aerosol samples collected using PILS. The results indicate that this approach has significant potential for future automated online monitoring of airborne metal concentrations, facilitating investigations into their sources and daily variations. The development of real-time technologies for rapid, online, and accurate atmospheric aerosol measurements is essential for advancing climate change research. Such advancements allowing for continuous real-time data enhance our understanding of aerosol dynamics, improve source identification, and inform public health and environmental policies, ultimately contributing to more effective climate change monitoring and mitigation.

Constructing a resilient ecological network by considering source stability in the largest Chinese urban agglomeration

The dynamics of ecological sources and their impact on the resilience of ecological networks (ENs) have attracted increasing attention from both researchers and managers. Although a couple of studies have recognized the source-loss effects on network resilience, there is a knowledge gap in integrating spatiotemporal changes of the sources while constructing resilient ENs. Here, we propose the concept of dynamic stability (DS) to explore the sources’ changes over a certain period and improve source identification by grading the DS in the largest urban agglomeration located in the middle reaches of the Yangtze River in China. An investigation of the five selected ecosystem service (ES) indicators in 2000, 2010, and 2018 identified 49, 54, and 68 preliminary sources, respectively, from which 11, 14, and three sources were extracted, respectively, with high, moderate, and low levels of DS, respectively. A three-tier EN was constructed by considering both the ESs and DSs of the extracted sources. The constructed network was scale-free and featured in small world in topology analysis. Moreover, a carefully designed attack test found that this EN was of good resilience as the three critical nodes that might cause a marked decay of resilience were in high or moderate DSs and were preferentially protected by the Ecological Conservation Red Line policy in China. In conclusion, the improved approach of considering the DSs of sources may help to precisely identify and protect the critical nodes threatening network resilience, which is highly desired in constructing ENs facing various rapid changes, especially in large-scale urbanized areas.

The Animal Origin of Major Human Infectious Diseases: What Can Past Epidemics Teach Us About Preventing the Next Pandemic?

Emerging infectious diseases are one of the greatest public health challenges. Approximately three-quarters of these diseases are of animal origin. These diseases include classical zoonoses maintained in humans only via transmission from other vertebrates (e.g., rabies) and those initiated by a successful one-off zoonotic event (host-switch) in conjunction with efficient human-to-human transmission (e.g., H1N1 influenza). Here, we provide a systematic review, in conjunction with a meta-analysis and spatial risk modeling, to identify the major characteristics of past epidemics of animal origin and predict areas with high future disease emergence risk. Countermeasures against future pandemics of animal origin must focus on several key mechanisms. First, the eco-epidemiological contexts favoring spillover events must be clearly establish. Second, pathogen surveillance must be scaled up, particularly in taxa and/or eco-geographic areas with high disease emergence risk. Third, successful spillover risk must be mitigated through proactive strategies to interrupt animal-to-human transmission chains. Fourth, to decrease epidemic potential and prevent epidemics from becoming pandemics, improved source identification and real-time spatial tracking of diseases are crucial. Finally, because pandemics do not respect international borders, enhancing international collaboration is critical to improving preparedness and response.

Steroid Biomarkers Revisited - Improved Source Identification of Faecal Remains in Archaeological Soil Material.

Steroids are used as faecal markers in environmental and in archaeological studies, because they provide insights into ancient agricultural practices and the former presence of animals. Up to now, steroid analyses could only identify and distinguish between herbivore, pig, and human faecal matter and their residues in soils and sediments. We hypothesized that a finer differentiation between faeces of different livestock animals could be achieved when the analyses of several steroids is combined (Δ5-sterols, 5α-stanols, 5β-stanols, epi-5β-stanols, stanones, and bile acids). We therefore reviewed the existing literature on various faecal steroids from livestock and humans and analysed faeces from old livestock breed (cattle, horse, donkey, sheep, goat, goose, and pig) and humans. Additionally, we performed steroid analyses on soil material of four different archaeological periods (sites located in the Lower Rhine Basin, Western Germany, dating to the Linearbandkeramik, Urnfield Period / Bronze Age, Iron Age, Roman Age) with known or supposed faecal inputs. By means of already established and newly applied steroid ratios of the analysed faeces together with results from the literature, all considered livestock faeces, except sheep and cattle, could be distinguished on the basis of their steroid signatures. Most remarkably was the identification of horse faeces (via the ratio: epi-5β-stigmastanol: 5β-stigmastanol + epicoprostanol: coprostanol; together with the presence of chenodeoxycholic acid) and a successful differentiation between goat (with chenodeoxycholic acid) and sheep/cattle faeces (without chenodeoxycholic acid). The steroid analysis of archaeological soil material confirmed the supposed faecal inputs, even if these inputs had occurred several thousand years ago.

Source apportionment of fine and coarse particles at a roadside and urban background site in London during the 2012 summer ClearfLo campaign

London, like many major cities, has a noted air pollution problem, and a better understanding of the sources of airborne particles in the different size fractions will facilitate the implementation and effectiveness of control strategies to reduce air pollution. Thus, the trace elemental composition of the fine and coarse fraction were analysed at hourly time resolution at urban background (North Kensington, NK) and roadside (Marylebone Road, MR) sites within central London. Unlike previous work, the current study focuses on measurements during the summer providing a snapshot of contributing sources, utilising the high time resolution to improve source identification. Roadside enrichment was observed for a large number of elements associated with traffic emissions (Al, S, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Rb and Zr), while those elements that are typically from more regional sources (e.g. Na, Cl, S and K) were not found to have an appreciable increment. Positive Matrix Factorization (PMF) was applied for the source apportionment of the particle mass at both sites with similar sources being identified, including sea salt, airborne soil, traffic emissions, secondary inorganic aerosols and a Zn-Pb source. In the fine fraction, traffic emissions was the largest contributing source at MR (31.9%), whereas it was incorporated within an “urban background” source at NK, which had contributions from wood smoke, vehicle emissions and secondary particles. Regional sources were the major contributors to the coarse fraction at both sites. Secondary inorganic aerosols (which contained influences from shipping emissions and coal combustion) source factors accounted for around 33% of the PM10 at NK and were found to have the highest contributions from regional sources, including from the European mainland. Exhaust and non-exhaust sources both contribute appreciably to PM10 levels at the MR site, highlighting the continuing importance of vehicle-related air pollutants at roadside.

A Monitoring Network Design Procedure for Three-Dimensional (3D) Groundwater Contaminant Source Identification

Finding the location and concentration of contaminant sources is an important step in groundwater remediation and management. This discovery typically requires the solution of an inverse problem. This inverse problem can be formulated as an optimization problem where the objective function is the sum of the square of the errors between the observed and predicted values of contaminant concentration at the observation wells. Studies show that the source identification accuracy is dependent on the observation locations (i.e., network geometry) and frequency of sampling; thus, finding a set of optimal monitoring well locations is very important for characterizing the source. The objective of this study is to propose a sensitivity-based method for optimal placement of monitoring wells by incorporating two uncertainties: the source location and hydraulic conductivity. An optimality metric called D-optimality in combination with a distance metric, which tends to make monitoring locations as far apart from each other as possible, is developed for finding optimal monitoring well locations for source identification. To address uncertainty in hydraulic conductivity, an integration method of multiple well designs is proposed based on multiple hydraulic conductivity realizations. Genetic algorithm is used as a search technique for this discrete combinatorial optimization problem. This procedure was applied to a hypothetical problem based on the well-known Borden Site data in Canada. The results show that the criterion-based selection proposed in this paper provides improved source identification performance when compared to uniformly distributed placement of wells.

An Optimization Method of Sensor Layout to Improve Source Identification Accuracy in the Indoor Environment

This study presents an optimization method of sensor layout to improve identification accuracy of indoor contaminant sources. The method integrates an index, the performance of sensor layout (PSL), with a two-step screening procedure to determine sensor layouts that have potential to achieve relatively high levels of accuracy in source identification. Using the PSL, the performance of each possible sensor layout can be predicted and evaluated, and therefore the optimization method can be performed without running a source identification model. The relationship between source identification accuracy and sensor layout was revealed through case studies in a three-dimensional office. The optimization method was demonstrated and validated by two cases in the same office, which includes optimization of sensor layouts with one and five sensors. The case studies indicate that the presented method can significantly improve source identification accuracy. The influencing factors of optimization results were discussed, and the methods to exclude unexpected optimization results were proposed.

Improvement of receptor model use in analytical aspect

In this study, four certified particle standards including NIST SRM 1648 urban particulate matter, BCR Reference Material No. 176 city waste incineration ash, NIST SRM 2709 San Joaquin soil, and NIST SRM 1633b coal fly ash were used to simulate ambient particulate matter. Twenty-five samples were prepared with the four certified particulate standards. A total of 23 elements were analyzed per sample, 19 by ICP-AES and ICP-MS, three by IC, and one element, Si, by spectrophotometer. Results showed that combining the three IC-analyzed ionic species with the 19 ICP-AES/MS analyzed elements into the CMB model did not improve the source identification significantly. In addition, when all 23 analyzed chemical species per sample were used in the CMB model, they were still not good enough to effectively make the parameters of the CMB model fit the statistical criteria. Some of high variation and low recovery chemical species, i.e. Cd, V, Sb, etc., may have caused poor CMB model simulation. Omitting some poor quality analyzed species (such as relative analysis error >20%) could improve the CMB model simulation. Therefore, high quality chemical species data are important for the CMB model. In addition, co-linearity of source profiles also affects the CMB model; combining the co-linear sources could enhance the solubility of the CMB model. In this study, a two-step procedure was developed for CMB model simulation to improve source identification.

The production, use and quality of sewage sludge in Denmark

In Denmark, the production of municipal sewage sludge decreased from approximately 170,000 ton d.m. in 1994 to 140,000 ton d.m. in 2002. The sludge is handled and treated in a number of ways. The quality of Danish sludge has steadily improved since the middle of the 1980s, when the first set of quality criteria for heavy metals was introduced. In 1997, cut-off criteria for the organic pollutants, LAS, DEHP, nonylphenol and PAHs were introduced. Effective control from authorities, voluntary phasing out agreements with industry, improved source identification tools, better handling and after-care methods have in combination with higher waste duties led to a significant reduction in the sludge level of especially cadmium, mercury, chromium, LAS and nonylphenol. The increased quality demand has, nevertheless, also led to a minor reduction in the use of sewage sludge as organic fertiliser on agricultural land.