Identification Of Pollution Sources Research Articles

Heavy Metal Pollution and Its Prior Pollution Source Identification in Agricultural Soil: A Case Study in the Qianguo Irrigation District, Northeast China

Heavy metals are the primary pollutants in agricultural soil and have hindered the sustainable development of agriculture. To control heavy metal pollution, it is essential to identify the pollution sources, particularly the prior source, in agricultural soils. In the current study, Qianguo Irrigation District, a typical agricultural region in Northeast China, was selected to be investigated for the source apportionment of soil heavy metals and identify the prior pollution source. The results showed that the study area was at a moderate pollution level with considerable ecological risk, while Hg and Cd were the main pollutants. Human-health risk assessment indicated that the non-carcinogenic risk for all populations was acceptable (HI < 1), and the carcinogenic risk was not negligible (10−6 < TCR < 10−4). The main pollution sources were concluded to be of lithogenic origin (35.5%), livestock manure (25.4%), coal combustion (21.5%), and chemical fertilizers (17.7%). Coal combustion was identified as the prior pollution source, accounting for 47.69% of the RI contribution. This study can provide scientific support for environmental management and pollution control of soil heavy metals in agricultural regions.

Pollution Characterization, Source Identification, and Health Risks of Atmospheric Particle-Bound Heavy Metals in PM2.5 in Zhengzhou City: Based on High-resolution Data

In order to study the pollution characteristics and sources of heavy metals in urban atmospheric PM2.5, 21 elements in atmospheric PM2.5 in Zhengzhou City were detected using an online metal analyzer during July and October 2017 and January and April 2018, and the changes in heavy metal concentrations were analyzed. Heavy metals were traced by enrichment factors, principal component analysis, and potential source function. The US EPA risk assessment model was used to assess their health risks. The results showed that:the concentrations of K, Zn, Mn, Pb, Cu, As, Cr, and Se increased with the increase in pollution level. The results of enrichment factors and principal component analysis showed that the main sources of heavy metals were crust, mixed combustion, industry, and motor vehicles. The characteristic radar charts showed that the pollution dominated by crustal sources mainly occurred in spring and winter, whereas the pollution dominated by mixed combustion sources mainly occurred in winter. Pb, As, and Ni were greatly affected by the transport of a fen nutrient-laden plain, Beijing-Tianjin-Hebei, and southern Henan, whereas Cd was greatly affected by the northwest region of the sampling site. As presented a significant carcinogenic risk in both adults and children, whereas Pb and Sb presented a significant non-carcinogenic risk in children.

Accurate Identification of Pollution Sources in a Chemical Enterprise Based on a Distributed Multi-channel VOCs Online Monitoring Mass Spectrometry System

A monitoring and traceability management system for unorganized emissions of volatile organic compounds (VOCs) in industrial parks has been established. This system uses distributed multi-channel mass spectrometry to continuously monitor multiple online monitoring points within the enterprise and the factory boundary to initially identify the source of unorganized emissions of VOCs. Based on online monitoring data, the system combined a positive matrix factorization (PMF) model and conditional bivariate probability function (CBPF) methods to accurately identify pollution sources of different scales in the park. The system was successfully applied to a pharmaceutical chemical factory in Taizhou Chemical Industry Park, and VOCs online monitoring was carried out for more than three months at 10 monitoring sites in the factory area. The sources of VOCs were analyzed using the PMF model, and the geographical location information of each pollution source factor was identified by the CBPF method. During the monitoring period, the contribution of chlorobenzene emissions and the number of early warnings were much higher than those of other species. Compared with that of other species, the frequency of abnormal emissions of butene was higher, and the frequency of abnormal emissions of toluene was lower. Among the top ten species, only chlorobenzene had significant concentration changes in different monitoring sites. Ambient VOCs in the plant mainly came from six sources:butene emission, toluene emission, chlorobenzene emission, solvent use, sulfur-related processes, and industrial production. Based on the CBPF results of each pollution source factor relative to the ten monitoring stations, the local pollution source and external pollution source in the plant were distinguished, and the specific location of the local pollution source and the transmission direction of the external pollution source were identified.

Seasonal changes of heavy metals and health risk assessment based on Monte Carlo simulation in alternate water sources of the Xinbian River in Suzhou City, Huaibei Plain, China

The urban alternate water source (AWS) is of great significance to the sustainable development of the city, the pollution degree, and source of heavy metals (HMs) in AWS, and whether it will adversely affect human health has received widespread attention. In this study, the urban AWS of Xinbian River in Suzhou City, Huaibei Plain, China, was used as the research object to study the seasonal changes of HMs (As, Cr, Cu, Cd, Pb, and Zn), quantitative identification of pollution sources, and human health risks (HHR). Research results show that the contents of those HMs, except As, are less than the drinking standards limit set by the World Health Organization (WHO), and the contents of As, Cr, and Zn are the largest in summer. The multivariate statistical analysis combined with positive matrix factorization (PMF) model analysis revealed that industrial sources accounted for 44.83%, and agricultural sources accounted for 55.17%. HHR assessment based on Monte Carlo simulation shows that the noncarcinogenic risks of adults and children are in the acceptable range (hazardous ingestion (HI) < 1), and the probability of carcinogenic risk values of children and adults are 95.03% and 38.96%, respectively, which are exceed the acceptable range (1 × 10−4) recommended by the United States Environment Protection Agency (USEPA). Approximately 30.75% of the carcinogenic risk value of agricultural source HMs to children exceeds the acceptable range (1 × 10−4). The above research results indicate that the effect of agricultural non-point source pollution on AWS should be prevented.

Some Review for Identification of air pollution sources of Ulaanbaatar City using ED-XRF Analysis

The conventional XRF analysis is wide used and suitable analytical method for various fields, especially environmental studies. Air pollution associated with atmospheric particulate matter (PM) is a serious problem in Ulaanbaatar city, the capital of Mongolia. According to World Bank estimation Ulaanbaatar is one of most polluted city. In this paper, we have done XRF analysis on Air Particulate Matters for determining to identification sources and its contributions which was the first time in Mongolia. Main pollution sources for PM2.5 particles of Ulaanbaatar by the result of XRF analysis are soil, combustion and vehicles.Уламжлалт Рентген-флюоресценцийн шинжилгээ нь төрөл бүрийн салбарт ялангуяа хүрээлэн байгаа орчны судалгаанд өргөн хэрэглэгддэг, тохиромжтой аналитик арга юм. Атмосферийн тоосонцороос (PM) үүдэлтэй агаарын бохирдол бол Монгол улсын нийслэл Улаанбаатар хотын хувьд онцгой асуудал юм. Дэлхийн банкны үнэлгээгээр Улаанбаатар нь дэлхийн хамгийн их бохирдолтой хотын нэг болж байна. Агаарын тоосонцорт хийсэн Рентген-флюоресценцийн шинжилгээний дүнг бохирдлын үүсгүүрүүдийг тогтоож тэдний хувь хэмжээг тодорхойлох Монголд анх удаа хийгдэж буй ажлыг бидний энэхүү өгүүлэлд тусгав. Рентген-флюоресценцийн шинжилгээний дүнгээр хөрс, түлшний шаталт болон тээврийн хэрэгслэл нь Улаанбаатарын РМ2.5 тоосонцрын үндсэн үүсгүүрүүд болж байна.

Identification and Apportionment of Potential Pollution Sources Using Multivariate Statistical Techniques and APCS-MLR Model to Assess Surface Water Quality in Imjin River Watershed, South Korea

Reliable water quality monitoring data, identifying potential pollution sources, and quantifying the corresponding potential pollution source apportionment are essential for future water resource management and pollution control. Here, we collected water quality data from seven monitoring sites to identify spatiotemporal changes in surface water in the Imjin River Watershed (IRW), South Korea, distinguish potential pollution sources, and quantify the source apportionment from 2018–2020. An analysis was performed based on multivariate statistical techniques (MST) and the absolute principal component score-multiple linear regression (APCS-MLR) model. Statistically significant groups were created based on spatiotemporally similar physicochemical water quality characteristics and anthropogenic activities: low-pollution (LP) and high-pollution (HP) regions, and dry season (DS) and wet season (WS). There were statistically significant mean differences in water quality parameters between spatial clusters, rather than between temporal clusters. We identified four and three potential factors that could explain 80.75% and 71.99% in the LP and HP regions, respectively. Identification and quantitative evaluation of potential pollution sources using MST and the APCS-MLR model for the IRW may be useful for policymakers to improve the water quality of target watersheds and establish future management policies.

Distribution, ecological risk assessment and source identification of pollutants in soils of different land-use types in degraded wetlands.

BackgroundUrbanization and global warming are generating ecological degradation and land pattern alteration problems in natural wetlands. These changes are greatly affecting the ecological services of wetlands. Therefore, there is an urgent need to explore the relationship between pollutants and land-use type for wetland restoration purposes. Zaozhadian Lake is a freshwater wetland in the North China Plain, which is facing degradation and land-use types changes. An experiment for analyzing soil pollutants was conducted in three land-use types of farmland, lake, and ditch in the Zaozhadian Lake. The aims of this study were to identify the distribution, pollution degree, and sources of pollutants in different land-use types, and to explore the influence of land-use type changes on contamination.MethodsIn this study, surface sediments (0–10 cm) of three land types (farmland, lake, and ditch) in Zaozhadian Lake were collected, and heavy metals (Cu, Ni, Zn, Pb, Cd, Cr, Hg), As, total nitrogen (TN), total phosphorus (TP) and organic matter (OM) were determined. Kriging interpolation was used to visualize the pollutants distribution. The pollution degree of TN and TP was evaluated by the Nemerow pollution index. The pollution of heavy metals and As was evaluated by the geological accumulation index (Igeo) and the potential ecological risk index (RI). Then, dual hierarchical clustering analysis and the principal component analysis were performed to further analyze the impact of land type changes on pollutants.ResultsThe heavy metal contents in the farmland were higher than other areas, while the TN (3.71 ± 1.03 g kg-1) and OM (57.17 ± 15.16 g kg−1) in lake sediments were higher than that in other regions. Farmland, lake, and ditches had low ecological risks, with RI values of 84.21, 71.34, and 50.78, respectively. The primary heavy metal pollutants are Pb, Cu, and Ni. Furthermore, Cu, As, Ni, Pb, and Zn were primarily derived from agriculture pollution, the source of Cd was the industrial pollution, and Cr mainly originated from natural sources. Nutrients primarily came from the decomposition of aquatic animals, plants, and human-related activities. When the lake area was converted into farmland, the heavy metal concentrations in the soils increased and the TN and OM decreased. Based on the results, this study put forward key strategies including the adjustment of the land-use type and restriction of the entry of pollutants into the wetland ecosystems in the Zaozhadian Lake. More attention should be paid to the impact of land-use type change on pollutants in wetlands.

Relationship between non-point source pollution and fluorescence fingerprint of riverine dissolved organic matter is season dependent

The source identification of water pollution and quantification of pollution sources are vital for water environment management. Dissolved organic matter (DOM) affects the form, solubility, and toxicity of pollutants, so the migration and transformation of DOM are crucial for water quality assessment. Therefore, the aim of this study was to identify pollution sources and quantify their contribution in water environments using fluorescence fingerprint of DOM. The Danjiangkou Reservoir and its main tributaries were selected as the study area. The DOM fluorescence components of pollution source samples were analyzed and the quantitative relationship between DOM spectral indices and nitrate isotopes (δ15N-NO3− and δ18O-NO3−) was established. It was found that humic-like substances were mainly derived from non-point source (NPS) pollution and protein-like substances were from point source (PS) pollution. The fluorescence index (FI) of DOM was positively correlated with PS pollution and negatively correlated with NPS pollution. The quantitative relationship between three-dimensional (3D) fluorescence spectra characteristics of DOM and water quality indicators or NPS pollution was established, which realized the convenient quantitative evaluation of pollution load and pollution source contribution using DOM fluorescence spectra characteristics. The strength of the correlation between DOM fluorescence spectra characteristics and water quality indicators (or NPS pollution) was affected by seasonal rainfall due to changes in the contribution of PS and NPS pollution. This study provides a new approach for source identification of water pollution and quantification of pollution sources using 3D fluorescence fingerprint of DOM.

Analysis and identification of pollution sources of comprehensive river water quality: Evidence from two river basins in China

• Industry is still the major source of China’s ambient water pollution. • Impact of pollution sources on water quality vary from basin to basin significantly. • Cultivation’s impact on water quality is seasonal. • Cultivation and livestock farming have a cumulative effect on water quality. The identification of the main sources and the impact of the current comprehensive water quality is important in improving the precision and pertinence of water quality management, which will have a significant bearing on the quality of the water environment and the ecological system. This paper focuses on the Yangtze River and Yellow River Basins, employs panel data from 2004–2019 from prefecture-level cities and water quality monitoring sections along the Yangtze and Yellow River main streams, and conducts an empirical study on the effects of pollution sources from cultivation, livestock farming, aquaculture, industry, and domestic activities on the overall water quality. It is found that: (1) Increased pollution from agriculture (cultivation, livestock farming and aquaculture), industry and domestic pollution all contribute to the deterioration of water quality. Industry is still the major source of China’s ambient water pollution. It is then followed by domestic source of pollution and agricultural source of pollution, with the latter having the least impact on water quality. (2) Impact of pollution sources on water quality vary from basin to basin significantly.The main sources of water pollution in the Yangtze and Yellow River Basins are industry and domestic life respectively. Cultivation and aquaculture are the main agricultural sources of water pollution in the two basins respectively. (3) Impact of cultivation pollution sources on water quality is subject to seasonal variations. It means that pollutants from cultivation enter the rivers through the carrying effect of precipitation, and this effect is more often reflected in the busy season. (4) In the long term, the negative impact of cultivation and livestock farming on water quality pollution form a cumulative effect. It grows as the number of lag periods increases. Therefore, in the subsequent environmental pollution control processes, priority should be given to industrial and urban pollution control with more targeted regional pollution management. It is also important to strengthen inter-basin and inter-regional synergistic control, taking top-level design of environmental policies and other conditions of the basin areas into full account to reduce the undesired environmental consequences caused by production.

A Multivariate Statistical Approach to Pollution Source Identification in Cauvery River, South India

A Multivariate Statistical Approach to Pollution Source Identification in Cauvery River, South India

Source identification, seasonal and spatial variations of airborne dust trace elements pollution in Tehran, the capital of Iran

One of the main challenges in highly populated cities such as Tehran is air pollution, which originates mainly from rapid and irregular urbanization and industrialization. This study was carried out to investigate trace elements contamination in airborne dust of Tehran, the capital of Iran. Dust samples were collected from 44 different sites on a monthly basis from March 2016 to March 2017. Results of trace elements pollution using three factors of enrichment factor, contamination factor and pollution load index, revealed that the pollution has spread in all seasons and its highest amount was observed in the cold seasons, the results of these indices also showed Pb, Zn, Cd and As play an important role in air pollution in Tehran. Three main groups were identified in the sources analysis study: (1) Co and Fe, (2) As, (3) Ni, Cr, Cd, Pb and Zn. The first group does not seem to be much influenced by human activities and originates mostly from geogenic sources; but the second and third groups are mostly from anthropogenic sources. Traffic, fossil fuel combustion and industrial activities are among the most important human factors that have a significant impact on the amount of Trace elements in the dust.

Hydrochemical characteristics and identification of groundwater pollution sources in tropical savanna.

Groundwater pollution of the watershed is mainly influenced by the multifaceted interactions of natural and anthropogenic processes. In this study, classic chemical and multivariate statistical methods were utilized to assess the groundwater quality and ascertain the potential contamination sources affecting the groundwater quality of Galma sub-watershed in a tropical savanna. For this purpose, the data set of 18 groundwater quality variables covering 57 different sampling boreholes (BH) was used. The groundwater samples essentially contained the cations in the following order of dominance: Ca2+ > Na+ > Mg2+ > K+. However, the anions had HCO3- > Cl- > SO4-2 > NO3- respectively. The hydrochemical facies classified the groundwater types of the sub-watershed into mixed Ca-Mg-Cl type of water, which means no cations and anions exceeds 50%. The second dominant water type was Ca-Cl. The Mg-HCO3 water type was found in BH 9, and Na-Cl water type in BH 29 of the studied area. The weathering of the basement rocks was responsible for the concentrations of these ions in the groundwater chemistry of the sub-watershed. Hierarchical cluster analysis (HCA) grouped the groundwater samples (boreholes) into five clusters that are statistically significant regarding the similarities of groundwater quality characteristics. The principal component analysis (PCA) extracted two major principal components explained around 65% of the variance and suggested the natural and anthropogenic processes especially the agricultural pollutants including synthetic fertilizers, and leaching of agricultural waste as the main factors affecting the groundwater quality. The integrated method proved to be efficient and robust for groundwater quality evaluation, as it guaranteed the precise assessment of groundwater chemistry in the sub-watershed of the tropical savanna. The findings of this investigation could be useful to the policy makers for developing effective groundwater management plans for the groundwater resources and protection of the sub-watershed.

Evaluation of pollution indices, health hazards and source identification of heavy metal in dust particles and storm trajectory simulation using HYSPLIT model (Case study: Hendijan center dust, southwest of Iran)

Atmospheric dust is one of the most recent environmental pollutions in Iran. This study examines the concentration of heavy metals and the assessment of environmental and human health risk in the dust samples of Hendijan region as one of the most important centers of wind erosion in the southwestern of Iran. ICP-MSS analysis was performed on 18 samples of fine dust to specify the concentration of heavy metals. Studies showed that the highest concentrations of metals in these fine dust samples belong to Cr, Ni, Zn, Cu, As, Pb and Cd, respectively. Examining fine dust's pollution assessment showed that the highest enrichment and geo-accumulation index belong to As, Ni and Cr metals. Environmental risk assessment shows the low environmental risk of these fine dusts. The hazard quotient in children and adults belongs to Cr, As and Ni, respectively. Human health risk assessment also showed that the highest absorption of metals in both children and adults is through ingestion. The non-carcinogenic risk of heavy metals of dust samples in children is about 9 times more than adults. The highest risk of cancer in the adult group belongs to Ni metal and in the group of children belongs to As and Ni metal. PCA analysis showed that As, Cu, Cd, Cr and Ni are of anthropogenic origin and Zn and Pb are of geogenic origin. The source of the dust phenomenon with the HYSPLIT model and the backward method indicates the tracking of this dust mass through Iraq, and its probable origin was assessed in the centers of northern Iraq and southeastern Syria.

Pollution characteristics and source identification of PBDEs in public transport microenvironments

Public transport microenvironments easily accumulate pollutants due to high airtightness and poor circulation. To investigate and analyze the pollution levels and sources of polybrominated diphenyl ethers (PBDEs), air and dust samples were collected from hybrid buses, electric buses and subways in Hangzhou, China. The components of six priority control PBDE congeners (BDE-28, -47, -99, -100, -153, and -209) were analyzed. The average concentrations of Σ6PBDEs in the air and dust samples were 625.38 pg/m3 and 1200.58 ng/g from hybrid buses; 747.46 pg/m3 and 1160.07 ng/g from electric buses; and 407.57 pg/m3 and 925.93 ng/g from subways, respectively. Decabromodiphenyl ether (BDE-209) was the main proportion of Σ6PBDEs in the air and dust samples. Several types of materials were collected from the interior as samples to investigate pollutant sources. Using principal component analysis (PCA), it was found that seat cover, polyvinyl chloride (PVC) plastic, rubber, and wire shells were the primary sources. Compared with the reference dose of several PBDE congeners proposed by the U.S. Environmental Protection Agency (US EPA), the exposure level of the population in public transport microenvironments to PBDEs was estimated to be low; however, the potential danger cannot be ignored.

Atmospheric concentration, spatial variations, and source identification of persistent organic pollutants in urban and semi-urban areas using passive air samplers in Bursa, Turkey.

In this study, the concentration of ambient persistent organic pollutants (POPs) such as polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and organochlorine pesticides (OCPs) were measured for 12months in urban and semi-urban areas using a passive air sampler. During the sampling period, a total of 14 PAH (∑14PAH) concentrations measured in urban and semi-urban areas were found to be 54.4 ± 22.6ng/m3 and 51.7 ± 34.3ng/m3, respectively. Molecular diagnostic ratios (MDRs) were used to determine PAH sources. According to the MDR values, combustion sources were the most important PAH sources in both sampling areas. However, since the urban area is close to the industrial zone, the combustion sources occurred at high temperatures (> 800°C), while the sources in the semi-urban area generally consisted of petrogenic fuel combustion. ∑50PCB concentrations measured in the urban and semi-urban areas were found to be 522.5 ± 196.9pg/m3 and 439.5 ± 166.6pg/m3, respectively. Homologous group distributions were used to determine the source of PCBs. According to the homologous group distributions, tri-, tetra-, and penta-chlorinated PCBs were dominant in both sampling areas. ∑10OCP concentrations measured in urban and semi-urban areas were found as 242.5 ± 104.6pg/m3 and 275.9 ± 130.9pg/m3, respectively. Also, α-HCH/γ-HCH and β-/(α + γ)-HCH ratios were used to determine the source of OCPs. Lindane was the predominant OCP in both sampling areas.

Inversion method for multi-point source pollution identification: Sensitivity analysis and application to European Tracer Experiment data

Fast and accurate identification of unknown pollution sources plays a crucial role in the emergency response and source control of air pollution. In this work, the applicability of a previously proposed two-step inversion method is investigated with sensitivity experiments and real data from the first release of the European Tracer Experiment (ETEX-1). The two-step inversion method is based on the principle of least squares and carries out additional model correction through the residual iterative process. To evaluate its performance, its retrieval results are compared with those of two other existing algorithms. It is shown that for those cases with richer measurements, all three methods are less sensitive to errors, while for cases where measurements are sparse, their retrieval accuracy will rapidly decrease as errors increase. From the results of sensitivity experiments, the new method provides higher estimation accuracy and a more stable performance than the other two methods. The new method presents the smallest maximum location error of 18.20 km when the amplitude of the measurement error increases to 100%, and 22.67 km when errors in the wind fields increase to 200%. Moreover, when applied to ETEX-1 data, the new method also exhibits good performance, with a location error of 4.71 km, which is the best estimation with respect to source location.摘要快速并且准确地识别未知污染源, 在大气污染应急响应和源头控制过程中起着至关重要的作用. 本文利用敏感性试验及欧洲示踪物测场试验(ETEX-1)数据研究了新提出的两步反演算法的实用性, 并将其反演结果与现有的两种算法进行了对比分析. 敏感试验表明, 在观测数据较为丰富的情况下, 三种算法对观测误差和风场误差的敏感性均较低; 而当观测数据较为稀疏时, 所有算法的估计精度都将随着误差的增加而下降, 但与其他两种算法相比, 两步反演算法具有更高的估计精度以及更稳定的估计性能. 此外, 欧洲示踪物测场试验的源项估计结果也表明, 在三个算法中, 两步反演算法具有最小的位置估计误差.

Priority Pollutants Monitoring and Water Quality Assessment in the Siret River Basin, Romania

The Integrated Water Resources Management regulations aim to ensure a good status of surface water quality and its sustainable use. Water quality monitoring of various water users supports the identification of pollution sources and their environmental impacts. The priority pollutants generated by wastewater discharges from municipal, industrial wastewater treatment plants or agricultural areas are of great interest due to their eco-toxicological effects and bio-accumulative properties. The aim of this study was to monitor the priority organic and inorganic pollutants from the Siret River basin, in Romania, with the purpose of assessing the surface water quality status and evaluating it by the Water Quality Index (WAWQI) method. The monitoring of inorganic priority pollutants (e.g., As, Cd, Hg, Ni, Pb) and organic priority pollutants (e.g., Naphthalene, Anthracene, Phenanthrene, Fluoranthene, Benzo(a)anthracene, Benzo(b)fluoranthene, Benzo(k)fluoranthene, Benzo(a)pyrene, Benzo(ghi)perylene, Indeno(1,2,3-cd)pyrene, α, β, and γ-Hexachlorocyclohexane, and Di-2-ethyl-hexyl-phthalate) was conducted within the Siret River basin, during the period 2015–2020. With this purpose, 21 sampling points (18 river sections and 3 lakes) were considered to assess the water quality. The results of this study proved that the water quality within the Siret River basin is generally classified in the 2nd or 3rd class. The spatial distribution of the water quality index values, using ARCGIS, also highlighted the fact that the water quality is mostly unsuitable for drinking water supplies, being influenced by the quality of its main tributaries, as well as by the effluent of wastewater treatment plants.

Identification of airborne pollutant sources within a slot ventilated porous enclosure depending on backward model and downwind scheme

Identification of pollutant source, depending on the inverse computational fluid dynamics (CFD) methodology, within a slot-ventilated porous enclosure has been proposed in this paper. The whole fluid flow system is assumed to be two-dimensional, laminar and porous-saturated. As the inverse CFD modeling was ill-posed, a downwind scheme is employed to discretize the convection term to improve the accuracy and the corresponding time step range is derived to achieve numerical stability. Afterward, the downwind scheme simplifies the discretization process and its direct inversion algorithm. The effects of the Reynolds number (), the Darcy number (), the Schmidt number () and locations of pollutant source on the backward time CFD simulations are investigated, respectively. Results show that the temporal size/step is a critical factor of computational stability. In addition, the thickness of velocity or concentration boundary layer directly impacts the sensitivity of the inverse CFD simulation. The present research could aid in the safety of gas-supplying pipe network and relevant pollutant leakage accidents. Highlights Identification of prior-unknown sources was proposed regarding gas-supplying network. Original transport equations were maintained to enhance the accuracy and generality. The downwind convection scheme was implemented to enhance backward CFD procedures. Diverse influencing factors were numerically tested to recover pollutant sources. The proposed new algorithm was validated thoroughly by experiments and benchmark solutions.

Identification of pollution sources in the Narew River catchment using multivariate statistical methods

The aim of the statistical analyses carried out was to identify similarities and to point out differences between the various tributaries of the Narew River, to identify the factors and processes responsible for the transformations occurring in the aquatic environment and finally, to identify the main sources of pollution in the river catchment. For the purposes of statistical analysis, the results of studies conducted as part of diagnostic monitoring by the General Inspectorate for Environmental Protection in 2017–2018 were used. The studies included 8 measurement points located directly on the Narew River and 17 points located on its selected left and right tributaries. Analysis of the collected results indicates that the chemical condition of the water in the Narew catchment is assessed as being poor. This observation may be due to the fact that the Narew catchment is mainly used for agricultural purposes and, in addition, there is a relatively large number of potential anthropogenic sources. As part of the analysis, two potential sources of pollution affecting water quality in the Narew catchment were identified, which include surface run-off and treated wastewater inflow.

An improved selective/differential medium for culturing the Bacteroides fragilis group from wastewater.

The aim of this study was to develop an effective selective/differential medium for culturing environmental strains of the Bacteroides fragilis group (BFG). This goal was achieved by modifying standard commercial Bacteroides Bile Esculin Agar (BBE Agar). Bacteroides Bile Esculin Agar was combined with substances that inhibit the growth of non-BFG bacteria, mostly Klebsiella pneumoniae and Fusobacterium mortiferum. The strains isolated from standard and modified BBE Agar were identified as BFG strains by PCR and 16S rRNA gene sequencing. The supplementation of standard BBE Agar with colistin (40 mg L-1), kanamycin (400 mg L-1) and vancomycin (7.5 mg L-1) increases the effectiveness of BFG bacteria isolation from <10% to 35%, and additional Gram staining improves the effectiveness of bacterial isolation five-fold relative to standard BBE Agar. The results of the present study also suggest that the presence of the bfr gene is not a reliable indicator for the identification of BFG strains.