Role of silver nanoparticles (AgNPs) on the cardiovascular system.

PubMed

Gonzalez, Carmen; Rosas-Hernandez, Hector; Ramirez-Lee, Manuel Alejandro; Salazar-García, Samuel; Ali, Syed F

2016-03-01

With the advent of nanotechnology, the use and applications of silver nanoparticles (AgNPs) have increased, both in consumer products as well as in medical devices. However, little is known about the effects of these nanoparticles on human health, more specific in the cardiovascular system, since this system represents an important route of action in terms of distribution, bioaccumulation and bioavailability of the different circulating substances in the bloodstream. A collection of studies have addressed the effects and applications of different kinds of AgNPs (shaped, sized, coated and functionalized) in several components of the cardiovascular system, such as endothelial cells, isolated vessels and organs as well as integrative animal models, trying to identify the underlying mechanisms involved in their actions, to understand their implication in the field of biomedicine. The purpose of the present review is to summarize the most relevant studies to date of AgNPs effects in the cardiovascular system and provide a broader picture of the potential toxic effects and exposure risks, which in turn will allow pointing out the directions of further research as well as new applications of these versatile nanomaterials.

Assessment of runoff and sediment yields using the AnnAGNPS model in a Three-Gorge watershed of China.

PubMed

Hua, Lizhong; He, Xiubin; Yuan, Yongping; Nan, Hongwei

2012-05-01

Soil erosion has been recognized as one of the major threats to our environment and water quality worldwide, especially in China. To mitigate nonpoint source water quality problems caused by soil erosion, best management practices (BMPs) and/or conservation programs have been adopted. Watershed models, such as the Annualized Agricultural Non-Point Source Pollutant Loading model (AnnAGNPS), have been developed to aid in the evaluation of watershed response to watershed management practices. The model has been applied worldwide and proven to be a very effective tool in identifying the critical areas which had serious erosion, and in aiding in decision-making processes for adopting BMPs and/or conservation programs so that cost/benefit can be maximized and non-point source pollution control can be achieved in the most efficient way. The main goal of this study was to assess the characteristics of soil erosion, sediment and sediment delivery of a watershed so that effective conservation measures can be implemented. To achieve the overall objective of this study, all necessary data for the 4,184 km(2) Daning River watershed in the Three-Gorge region of the Yangtze River of China were assembled. The model was calibrated using observed monthly runoff from 1998 to 1999 (Nash-Sutcliffe coefficient of efficiency of 0.94 and R(2) of 0.94) and validated using the observed monthly runoff from 2003 to 2005 (Nash-Sutcliffe coefficient of efficiency of 0.93 and R(2) of 0.93). Additionally, the model was validated using annual average sediment of 2000-2002 (relative error of -0.34) and 2003-2004 (relative error of 0.18) at Wuxi station. Post validation simulation showed that approximately 48% of the watershed was under the soil loss tolerance released by the Ministry of Water Resources of China (500 t·km(-2)·y(-1)). However, 8% of the watershed had soil erosion of exceeding 5,000 t·km(-2)·y(-1). Sloping areas and low coverage areas are the main source of soil loss in the

Applications of AnnAGNPS model for soil loss estimation and nutrient loading for Malaysian conditions

NASA Astrophysics Data System (ADS)

Shamshad, A.; Leow, C. S.; Ramlah, A.; Wan Hussin, W. M. A.; Sanusi, S. A. Mohd.

2008-09-01

The study evaluated the performance and suitability of AnnAGNPS model in assessing runoff, sediment loading and nutrient loading under Malaysian conditions. The watershed of River Kuala Tasik in Malaysia, a combination of two sub-watersheds, was selected as the area of study. The data for the year 2004 was used to calibrate the model and the data for the year 2005 was used for validation purposes. Several input parameters were computed using methods suggested by other researchers and studies carried out in Malaysia. The study shows that runoff was predicted well with an overall R2 value of 0.90 and E value of 0.70. Sediment loading was able to produce a moderate result of R2 = 0.66 and E = 0.49, nitrogen loading predictions were slightly better with R2 = 0.68 and E = 0.53, and phosphorus loading performance was slightly poor with an R2 = 0.63 and E = 0.33. The erosion map developed was in agreement with the erosion risk map produced by the Department of Agriculture, Malaysia. Rubber estates and urban areas were found to be the main contributors to soil erosion. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for planning and management of watersheds under Malaysian conditions.

Antifungal Effects of Silver Nanoparticles (AgNPs) against Various Plant Pathogenic Fungi.

PubMed

Kim, Sang Woo; Jung, Jin Hee; Lamsal, Kabir; Kim, Yun Seok; Min, Ji Seon; Lee, Youn Su

2012-03-01

This research is concerned with the fungicidal properties of nano-size silver colloidal solution used as an agent for antifungal treatment of various plant pathogens. We used WA-CV-WA13B, WA-AT-WB13R, and WA-PR-WB13R silver nanoparticles (AgNPs) at concentrations of 10, 25, 50, and 100 ppm. Eighteen different plant pathogenic fungi were treated with these AgNPs on potato dextrose agar (PDA), malt extract agar, and corn meal agar plates. We calculated fungal inhibition in order to evaluate the antifungal efficacy of silver nanoparticles against pathogens. The results indicated that AgNPs possess antifungal properties against these plant pathogens at various levels. Treatment with WA-CV-WB13R AgNPs resulted in maximum inhibition of most fungi. Results also showed that the most significant inhibition of plant pathogenic fungi was observed on PDA and 100 ppm of AgNPs.

The effect of silver nanoparticles (AgNPs) on proliferation and apoptosis of in ovo cultured glioblastoma multiforme (GBM) cells.

PubMed

Urbańska, Kaja; Pająk, Beata; Orzechowski, Arkadiusz; Sokołowska, Justyna; Grodzik, Marta; Sawosz, Ewa; Szmidt, Maciej; Sysa, Paweł

2015-01-01

Recently, it has been shown that silver nanoparticles (AgNPs) provide a unique approach to the treatment of tumors, especially those of neuroepithelial origin. Thus, the aim of this study was to evaluate the impact of AgNPs on proliferation and activation of the intrinsic apoptotic pathway of glioblastoma multiforme (GBM) cells cultured in an in ovo model. Human GBM cells, line U-87, were placed on chicken embryo chorioallantoic membrane. After 8 days, the tumors were divided into three groups: control (non-treated), treated with colloidal AgNPs (40 μg/ml), and placebo (tumors supplemented with vehicle only). At the end of the experiment, all tumors were isolated. Assessment of cell proliferation and cell apoptosis was estimated by histological, immunohistochemical, and Western blot analyses. The results show that AgNPs can influence GBM growth. AgNPs inhibit proliferation of GBM cells and seem to have proapoptotic properties. Although there were statistically significant differences between control and AgNP groups in the AI and the levels of active caspase 9 and active caspase 3, the level of these proteins in GBM cells treated with AgNPs seems to be on the border between the spontaneous apoptosis and the induced. Our results indicate that the antiproliferative properties of silver nanoparticles overwhelm proapoptotic ones. Further research focused on the cytotoxic effect of AgNPs on tumor and normal cells should be conducted.

Assessment of Runoff and Sediment Yields Using the AnnAGNPS Model in a Three-Gorge Watershed of China

PubMed Central

Hua, Lizhong; He, Xiubin; Yuan, Yongping; Nan, Hongwei

2012-01-01

Soil erosion has been recognized as one of the major threats to our environment and water quality worldwide, especially in China. To mitigate nonpoint source water quality problems caused by soil erosion, best management practices (BMPs) and/or conservation programs have been adopted. Watershed models, such as the Annualized Agricultural Non-Point Source Pollutant Loading model (AnnAGNPS), have been developed to aid in the evaluation of watershed response to watershed management practices. The model has been applied worldwide and proven to be a very effective tool in identifying the critical areas which had serious erosion, and in aiding in decision-making processes for adopting BMPs and/or conservation programs so that cost/benefit can be maximized and non-point source pollution control can be achieved in the most efficient way. The main goal of this study was to assess the characteristics of soil erosion, sediment and sediment delivery of a watershed so that effective conservation measures can be implemented. To achieve the overall objective of this study, all necessary data for the 4,184 km2 Daning River watershed in the Three-Gorge region of the Yangtze River of China were assembled. The model was calibrated using observed monthly runoff from 1998 to 1999 (Nash-Sutcliffe coefficient of efficiency of 0.94 and R2 of 0.94) and validated using the observed monthly runoff from 2003 to 2005 (Nash-Sutcliffe coefficient of efficiency of 0.93 and R2 of 0.93). Additionally, the model was validated using annual average sediment of 2000–2002 (relative error of −0.34) and 2003–2004 (relative error of 0.18) at Wuxi station. Post validation simulation showed that approximately 48% of the watershed was under the soil loss tolerance released by the Ministry of Water Resources of China (500 t·km−2·y−1). However, 8% of the watershed had soil erosion of exceeding 5,000 t·km−2·y−1. Sloping areas and low coverage areas are the main source of soil loss in the

Silver nanoparticles (AgNPs) as a contrast agent for imaging of animal tissue using swept-source optical coherence tomography (SSOCT)

NASA Astrophysics Data System (ADS)

Mondal, Indranil; Raj, Shipra; Roy, Poulomi; Poddar, Raju

2018-01-01

We present noninvasive three-dimensional depth-resolved imaging of animal tissue with a swept-source optical coherence tomography system at 1064 nm center wavelength and silver nanoparticles (AgNPs) as a potential contrast agent. A swept-source laser light source is used to enable an imaging rate of 100 kHz (100 000 A-scans s-1). Swept-source optical coherence tomography is a new variant of the optical coherence tomography (OCT) technique, offering unique advantages in terms of sensitivity, reduction of motion artifacts, etc. To enhance the contrast of an OCT image, AgNPs are utilized as an exogeneous contrast agent. AgNPs are synthesized using a modified Tollens method and characterization is done by UV-vis spectroscopy, dynamic light scattering, scanning electron microscopy and energy dispersive x-ray spectroscopy. In vitro imaging of chicken breast tissue, with and without the application of AgNPs, is performed. The effect of AgNPs is studied with different exposure times. A mathematical model is also built to calculate changes in the local scattering coefficient of tissue from OCT images. A quantitative estimation of scattering coefficient and contrast is performed for tissues with and without application of AgNPs. Significant improvement in contrast and increase in scattering coefficient with time is observed.

Green Synthesis of AgNPs Stabilized with biowaste and their antimicrobial activities

PubMed Central

Jasuja, Nakuleshwar Dut; Gupta, Deepak Kumar; Reza, Mohtashim; Joshi, Suresh C.

2014-01-01

In the present study, rapid reduction and stabilization of Ag+ ions with different NaOH molar concentration (0.5 mM, 1.0 mM and 1.5 mM) has been carried out in the aqueous solution of silver nitrate by the bio waste peel extract of P.granatum. Generally, chemical methods used for the synthesis of AgNPs are quite toxic, flammable and have adverse effect in medical application but green synthesis is a better option due to eco-friendliness, non-toxicity and safe for human. Stable AgNPs were synthesized by treating 90 mL aqueous solution of 2 mM AgNO3 with the 5 mL plant peels extract (0.4% w/v) at different NaOH concentration (5 mL). The synthesized AgNPs were characterized by UV-Vis spectroscopy, TEM and SEM. Further, antimicrobial activities of AgNPs were performed on Gram positive i.e. Staphylococcus aureus, Bacillus subtilius and Gram negative i.e. E. coli, Pseudomonas aeruginosa bacteria. The AgNPs synthesized at 1.5 mM NaOH concentration had shown maximum zone of inhibition (ZOI) i.e. 49 ± 0.64 in E. coli, whereas Pseudomonas aeruginosa, Staphylococcus aureus and Bacillus subtilius had shown 40 ± 0.29 mm, 28 ± 0.13 and 42 ± 0.49 mm ZOI respectively. The MIC value of 30 μg/mL observed for E. coli Whereas, Staphylococcus aureus, Bacillus subtilius and Pseudomonas aeruginosa had shown 45 μg/mL, 38 μg/mL, 35 μg/mL respectively. The study revealed that AgNPs had shown significant antimicrobial activity as compared to Streptomycin. PMID:25763037

Green Synthesis of AgNPs Stabilized with biowaste and their antimicrobial activities.

PubMed

Jasuja, Nakuleshwar Dut; Gupta, Deepak Kumar; Reza, Mohtashim; Joshi, Suresh C

2014-01-01

In the present study, rapid reduction and stabilization of Ag+ ions with different NaOH molar concentration (0.5 mM, 1.0 mM and 1.5 mM) has been carried out in the aqueous solution of silver nitrate by the bio waste peel extract of P.granatum. Generally, chemical methods used for the synthesis of AgNPs are quite toxic, flammable and have adverse effect in medical application but green synthesis is a better option due to eco-friendliness, non-toxicity and safe for human. Stable AgNPs were synthesized by treating 90 mL aqueous solution of 2 mM AgNO₃ with the 5 mL plant peels extract (0.4% w/v) at different NaOH concentration (5 mL). The synthesized AgNPs were characterized by UV-Vis spectroscopy, TEM and SEM. Further, antimicrobial activities of AgNPs were performed on Gram positive i.e. Staphylococcus aureus, Bacillus subtilius and Gram negative i.e. E. coli, Pseudomonas aeruginosa bacteria. The AgNPs synthesized at 1.5 mM NaOH concentration had shown maximum zone of inhibition (ZOI) i.e. 49 ± 0.64 in E. coli, whereas Pseudomonas aeruginosa, Staphylococcus aureus and Bacillus subtilius had shown 40 ± 0.29 mm, 28 ± 0.13 and 42 ± 0.49 mm ZOI respectively. The MIC value of 30 μg/mL observed for E. coli Whereas, Staphylococcus aureus, Bacillus subtilius and Pseudomonas aeruginosa had shown 45 μg/mL, 38 μg/mL, 35 μg/mL respectively. The study revealed that AgNPs had shown significant antimicrobial activity as compared to Streptomycin.

Runoff characteristics and non-point source pollution analysis in the Taihu Lake Basin: a case study of the town of Xueyan, China.

PubMed

Zhu, Q D; Sun, J H; Hua, G F; Wang, J H; Wang, H

2015-10-01

Non-point source pollution is a significant environmental issue in small watersheds in China. To study the effects of rainfall on pollutants transported by runoff, rainfall was monitored in Xueyan town in the Taihu Lake Basin (TLB) for over 12 consecutive months. The concentrations of different forms of nitrogen (N) and phosphorus (P), and chemical oxygen demand, were monitored in runoff and river water across different land use types. The results indicated that pollutant loads were highly variable. Most N losses due to runoff were found around industrial areas (printing factories), while residential areas exhibited the lowest nitrogen losses through runoff. Nitrate nitrogen (NO3-N) and ammonia nitrogen (NH4-N) were the dominant forms of soluble N around printing factories and hotels, respectively. The levels of N in river water were stable prior to the generation of runoff from a rainfall event, after which they were positively correlated to rainfall intensity. In addition, three sites with different areas were selected for a case study to analyze trends in pollutant levels during two rainfall events, using the AnnAGNPS model. The modeled results generally agreed with the observed data, which suggests that AnnAGNPS can be used successfully for modeling runoff nutrient loading in this region. The conclusions of this study provide important information on controlling non-point source pollution in TLB.

Rapid Biosynthesis of AgNPs Using Soil Bacterium Azotobacter vinelandii With Promising Antioxidant and Antibacterial Activities for Biomedical Applications

NASA Astrophysics Data System (ADS)

Karunakaran, Gopalu; Jagathambal, Matheswaran; Gusev, Alexander; Torres, Juan Antonio Lopez; Kolesnikov, Evgeny; Kuznetsov, Denis

2017-07-01

Silver nanoparticles (AgNPs) are applied in various fields from electronics to biomedical applications as a result of their high surface-to-volume ratio. Even though different approaches are available for synthesis of AgNPs, a nontoxic method for the synthesis has not yet been developed. Thus, this study focused on developing an easy and ecofriendly approach to synthesize AgNPs using Azotobacter vinelandii culture extracts. The biosynthesized nanoparticles were further characterized by ultraviolet-visible (UV-Vis) spectroscopy, x-ray diffraction (XRD), Fourier transform infrared (FTIR), energy-dispersive spectrum, particle size distribution (PSD), and transmission electron microscopy (TEM). UV absorption noticed at 435 nm showed formation of AgNPs. The XRD pattern showed a face-centered cubic structure with broad peaks of 28.2°, 32.6°, 46.6°, 55.2°, 57.9°, and 67.8°. The FTIR confirmed the involvement of various functional groups in the biosynthesis of AgNPs. The PSD and TEM analyses showed spherical, well-distributed nanoparticles with an average size of 20-70 nm. The elemental studies confirmed the existence of pure AgNPs. The bacterial extract containing extracellular enzyme nitrate reductase converted silver nitrate into AgNPs. AgNPs significantly inhibited the growth of pathogenic bacteria such as Streptomyces fradiae (National Collection of Industrial Microorganisms (NCIM) 2419), Staphylococcus aureus (NCIM 2127), Escherichia coli (NCIM 2065), and Serratia marcescens (NCIM 2919). In addition, biosynthesized AgNPs were found to possess strong antioxidant activity. Thus, the results of this study revealed that biosynthesized AgNPs could serve as a lead in the development of nanomedicine.

Silver nanoparticles (AgNPs) biosynthesized using pod extract of Cola nitida enhances antioxidant activity and phytochemical composition of Amaranthus caudatus Linn

NASA Astrophysics Data System (ADS)

Azeez, Luqmon; Lateef, Agbaje; Adebisi, Segun A.

2017-02-01

This study investigates the influence of different concentrations of AgNPs biologically synthesized using pod extract of Cola nitida on antioxidant activity, phenolic contents, flavonoid contents and compositions of Amaranthus caudatus L. AgNPs of 25, 50, 75, 100 and 150 ppm were utilized in growing A. caudatus while water was used as control. Delayed germination for two days was observed for A. caudatus grown with 150 ppm of AgNPs, while others showed no difference. There were 43.3, 38.7, 26.7 and 6.48% improvements in the 2,2-diphenyl-1-picrylhydrazyl (DPPH) antioxidant activity of A. caudatus grown with 25, 50, 75 and 100 ppm of AgNPs, respectively, compared to control. Antioxidant activity of A. caudatus grown with AgNPs reduced with increase in the concentrations of AgNPs. A. caudatus grown with 50 ppm of AgNPs was the most potent with the least IC50 of 0.67 mg/ml. Significant improvements obtained for phenolic and flavonoid contents grown with AgNPs were concentration dependent. Enhancements of 21.9, 68.19, and 1.98% in phenolic contents were achieved in treatments with 25, 50 and 75 ppm AgNPs, respectively, while 32.58, 35.80, and 7.20% improvement in flavonoids were obtained for 25, 50 and 100 ppm treatments, respectively. Kaempferol and quercetin were the most abundant flavonoids in A. caudatus treated with 50 ppm of AgNPs, showing the highest flavonoid composition. This further confirms A. caudatus grown with 50 ppm of AgNPs as the most potent. This study has shown that concentration-dependent AgNPs can be used to boost antioxidant activity and phytochemical contents of vegetables.

Water quality modeling using geographic information system (GIS) data

NASA Technical Reports Server (NTRS)

Engel, Bernard A

1992-01-01

Protection of the environment and natural resources at the Kennedy Space Center (KSC) is of great concern. The potential for surface and ground water quality problems resulting from non-point sources of pollution was examined using models. Since spatial variation of parameters required was important, geographic information systems (GIS) and their data were used. The potential for groundwater contamination was examined using the SEEPAGE (System for Early Evaluation of the Pollution Potential of Agricultural Groundwater Environments) model. A watershed near the VAB was selected to examine potential for surface water pollution and erosion using the AGNPS (Agricultural Non-Point Source Pollution) model.

Differential Phytotoxic Impact of Plant Mediated Silver Nanoparticles (AgNPs) and Silver Nitrate (AgNO3) on Brassica sp.

PubMed Central

Vishwakarma, Kanchan; Shweta; Upadhyay, Neha; Singh, Jaspreet; Liu, Shiliang; Singh, Vijay P.; Prasad, Sheo M.; Chauhan, Devendra K.; Tripathi, Durgesh K.; Sharma, Shivesh

2017-01-01

Continuous formation and utilization of nanoparticles (NPs) have resulted into significant discharge of nanosized particles into the environment. NPs find applications in numerous products and agriculture sector, and gaining importance in recent years. In the present study, silver nanoparticles (AgNPs) were biosynthesized from silver nitrate (AgNO3) by green synthesis approach using Aloe vera extract. Mustard (Brassica sp.) seedlings were grown hydroponically and toxicity of both AgNP and AgNO3 (as ionic Ag+) was assessed at various concentrations (1 and 3 mM) by analyzing shoot and root length, fresh mass, protein content, photosynthetic pigments and performance, cell viability, oxidative damage, DNA degradation and enzyme activities. The results revealed that both AgNPs and AgNO3 declined growth of Brassica seedlings due to enhanced accumulation of AgNPs and AgNO3 that subsequently caused severe inhibition in photosynthesis. Further, the results showed that both AgNPs and AgNO3 induced oxidative stress as indicated by histochemical staining of superoxide radical and hydrogen peroxide that was manifested in terms of DNA degradation and cell death. Activities of antioxidants, i.e., ascorbate peroxidase (APX) and catalase (CAT) were inhibited by AgNPs and AgNO3. Interestingly, damaging impact of AgNPs was lesser than AgNO3 on Brassica seedlings which was due to lesser accumulation of AgNPs and better activities of APX and CAT, which resulted in lesser oxidative stress, DNA degradation and cell death. The results of the present study showed differential impact of AgNPs and AgNO3 on Brassica seedlings, their mode of action, and reasons for their differential impact. The results of the present study could be implied in toxicological research for designing strategies to reduce adverse impact of AgNPs and AgNO3 on crop plants. PMID:29075270

Plumbago auriculata leaf extract-mediated AgNPs and its activities as antioxidant, anti-TB and dye degrading agents.

PubMed

Jaryal, Neeraj; Kaur, Harpreet

2017-11-01

In the present work, silver nanoparticles have been biosynthesized by utilizing the alcoholic extract of Plumbago auriculata. The optimization of reaction conditions was carried out by monitoring the reactions with the help of UV-Visible absorption spectroscopy. The characterization of AgNP was carried out by infrared spectroscopy, transmission electron microscopy and X-Ray diffraction (XRD) studies. The biogenic AgNPs were tested against Mycobacterium tuberculosis using Microplate Almar Blue assay (MABA) and their antioxidant activity was also evaluated. The silver nanoparticles were also assessed for their reducing activity against organic dyes. The AgNPs were spherical in shape with size ranging from 15 to 45 nm with face centered cubic geometry as revealed by XRD analysis. The AgNPs possessed good antitubercular activity with MIC value of 1.6 μg/ml and these also exhibited promising antioxidant activity with IC 50 value of 28.2. Furthermore, AgNPs also reduced congo red within 2 h and malachite green was degraded within 40 min. The present work demonstrated the utilization of P. auriculata for biosynthesis of AgNP which could be a potential candidate for antitubercular drug development and it could also be used as an antioxidant agent. The application of AgNP in reducing agent can be further extended and evaluated for purification of effluent water from textile industries.

Facile and eco-friendly fabrication of AgNPs coated silk for antibacterial and antioxidant textiles using honeysuckle extract.

PubMed

Zhou, Yuyang; Tang, Ren-Cheng

2018-01-01

Recently, there is a growing trend towards the functionalization of silk through nanotechnology for the prevention of fiber damage from microbial attack and the enhancement of hygienic aspects. Considering sustainable development and environmental protection, the eco-friendly fabrication of silver nanoparticles (AgNPs)-modified silk using natural extracts has currently become a hot research area. This study presents a facile strategy for the fabrication of colorful and multifunctional silk fabric using biogenic AgNPs prepared by honeysuckle extract as natural reductant and stabilizing agents. The influences of pH and reactant concentrations on the AgNPs synthesis were investigated. The color characteristics and functionalities of AgNPs treated silk were evaluated. The results revealed that the particle size of AgNPs decreased with increasing pH. The diameter of AgNPs decreased with increasing amount of honeysuckle extract and reducing amount of silver nitrate. The transmission electron microscopy image showed that the AgNPs were spherical in shape with a narrow size distribution. The treated silk showed excellent antibacterial activities against E. coli and S. aureus, and certain antioxidant activity. Both of the antibacterial and antioxidant activities were well maintained even after 30 washing cycles. This work provides a sustainable and eco-friendly approach to the fabrication of AgNPs coated silk for colorful and long-term multifunctional textiles using honeysuckle extract. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake.

PubMed

Luo, Chuan; Li, Zhaofu; Li, Hengpeng; Chen, Xiaomin

2015-09-02

The application of hydrological and water quality models is an efficient approach to better understand the processes of environmental deterioration. This study evaluated the ability of the Annualized Agricultural Non-Point Source (AnnAGNPS) model to predict runoff, total nitrogen (TN) and total phosphorus (TP) loading in a typical small watershed of a hilly region near Taihu Lake, China. Runoff was calibrated and validated at both an annual and monthly scale, and parameter sensitivity analysis was performed for TN and TP before the two water quality components were calibrated. The results showed that the model satisfactorily simulated runoff at annual and monthly scales, both during calibration and validation processes. Additionally, results of parameter sensitivity analysis showed that the parameters Fertilizer rate, Fertilizer organic, Canopy cover and Fertilizer inorganic were more sensitive to TN output. In terms of TP, the parameters Residue mass ratio, Fertilizer rate, Fertilizer inorganic and Canopy cover were the most sensitive. Based on these sensitive parameters, calibration was performed. TN loading produced satisfactory results for both the calibration and validation processes, whereas the performance of TP loading was slightly poor. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for the planning and management of watersheds.

Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake

PubMed Central

Luo, Chuan; Li, Zhaofu; Li, Hengpeng; Chen, Xiaomin

2015-01-01

The application of hydrological and water quality models is an efficient approach to better understand the processes of environmental deterioration. This study evaluated the ability of the Annualized Agricultural Non-Point Source (AnnAGNPS) model to predict runoff, total nitrogen (TN) and total phosphorus (TP) loading in a typical small watershed of a hilly region near Taihu Lake, China. Runoff was calibrated and validated at both an annual and monthly scale, and parameter sensitivity analysis was performed for TN and TP before the two water quality components were calibrated. The results showed that the model satisfactorily simulated runoff at annual and monthly scales, both during calibration and validation processes. Additionally, results of parameter sensitivity analysis showed that the parameters Fertilizer rate, Fertilizer organic, Canopy cover and Fertilizer inorganic were more sensitive to TN output. In terms of TP, the parameters Residue mass ratio, Fertilizer rate, Fertilizer inorganic and Canopy cover were the most sensitive. Based on these sensitive parameters, calibration was performed. TN loading produced satisfactory results for both the calibration and validation processes, whereas the performance of TP loading was slightly poor. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for the planning and management of watersheds. PMID:26364642

Inhibitory Effects of Silver Nanoparticles on Removal of Organic Pollutants and Sulfate in an Anaerobic Biological Wastewater Treatment Process.

PubMed

Rasool, Kashif; Lee, Dae Sung

2016-05-01

The increasing use of silver nanoparticles (AgNPs) in commercial products and industrial processes raises issues regarding the toxicity of sludge biomass in biological wastewater treatment plants, due to potential antimicrobial properties. This study investigated the effects of AgNPs on removal of organic pollutants and sulfate in an anaerobic biological sulfate reduction process. At AgNPs concentrations of up to 10 mg/L, no significant inhibition of sulfate and COD removal was observed. However, at higher concentrations (50-200 mg/L) sulfate and COD removal efficiencies were significantly decreased to 51.8% and 33.6%, respectively. Sulfate and COD reduction followed first-order kinetics at AgNPs concentrations of up to 10 mg/L and second-order kinetics at AgNPs concentrations of 50-200 mg/L. Lactate dehydrogenase release profiles showed increases in cytotoxicity at AgNPs concentrations greater than 50 mg/L suggesting cell membrane disruption. Analysis of extracellular polymeric substances (EPS) from sulfidogenic sludge biomass and of Fourier transform infrared (FT-IR) spectra showed a decrease in concentrations of carbohydrates, proteins, humic substances, and lipids in the presence of AgNPs. Moreover, the interaction of AgNPs with sludge biomass and the damage caused to cell walls were confirmed through scanning electron microscopy with energy dispersive X-ray spectroscopy.

Biochar alleviates the toxicity of imidacloprid and silver nanoparticles (AgNPs) to Enchytraeus albidus (Oligochaeta).

PubMed

Nyoka, Ngitheni Winnie-Kate; Kanyile, Sthandiwe Nomthandazo; Bredenhand, Emile; Prinsloo, Godfried Jacob; Voua Otomo, Patricks

2018-04-01

The present study investigated the use of biochar for the alleviation of the toxic effects of a nanosilver colloidal dispersion and a chloronicotinyl insecticide. The survival and reproduction of the potworm Enchytraeus albidus were assessed after exposure to imidacloprid and silver nanoparticles (AgNPs). E. albidus was exposed to 0, 25, 50, 100, 200, and 400 mg imidacloprid/kg and 0, 5, 25, 125, and 625 mg Ag/kg for 21 days in 10% biochar amended and non-biochar amended OECD artificial soil. In both exposure substrates, the effects of imidacloprid on survival were significant in the two highest treatments (p < 0.01). No biochar effect was observed as survival was statistically similar in both soils after exposure to imidacloprid. In the case of AgNPs, significant mortality was only observed in the highest AgNP treatments in both the amended and non-amended soils (p < 0.05). Nevertheless, statistically greater survival occurred in the biochar-amended treatment (p < 0.05). Reproduction results showed a more pronounced biochar effect with an EC 50  = 22.27 mg imidacloprid/kg in the non-amended soil and a higher EC 50  = 46.23 mg imidacloprid/kg in the biochar-amended soil. This indicated a 2-fold decrease in imidacloprid toxicity due to biochar amendment. A similar observation was made in the case of AgNPs where a reproduction EC 50  = 166.70 mg Ag/kg soil in the non-amended soil increased to an EC 50  > 625 mg Ag/kg soil (the highest AgNP treatment) in the amended soil. This indicated at least a 3.7-fold decrease in AgNPs toxicity due to biochar amendment. Although more studies may be needed to optimize the easing effects of biochar on the toxicity of these chemicals, the present results show that biochar could be useful for the alleviation of the toxic effects of imidacloprid and silver nanoparticles in the soil.

Synthesis of Ag-NPs impregnated cellulose composite material: its possible role in wound healing and photocatalysis.

PubMed

Ali, Attarad; Haq, Ihsan Ul; Akhtar, Javeed; Sher, Muhammad; Ahmed, Naveed; Zia, Muhammad

2017-06-01

Cellulose is the natural biopolymer normally used as supporting agent with enhanced applicability and properties. In present study, cellulose isolated from citrus waste is used for silver nanoparticles (Ag-NPs) impregnation by a simple and reproducible method. The Ag-NPs fabricated cellulose (Ag-Cel) was characterised by powder X-rays diffraction, Fortier transform infrared spectroscopy and scanning electron microscopy. The thermal stability was studied by thermo-gravimetric analysis. The antibacterial activity performed by disc diffusion assay reveals good zone of inhibition against Staphylococcus aureus and Escherichia coli by Ag-Cel as compared Ag-NPs. The discs also displayed more than 90% reduction of S. aureus culture in broth within 150 min. The Ag-Cel discs also demonstrated minor 2,2-diphenyl 1-picryl-hydrazyl radical scavenging activity and total reducing power ability while moderate total antioxidant potential was observed. Ag-Cel effectively degrades methylene-blue dye up to 63.16% under sunlight irradiation in limited exposure time of 60 min. The Ag-NPs impregnated cellulose can be effectively used in wound dressing to prevent bacterial attack and scavenger of free radicals at wound site, and also as filters for bioremediation and wastewater purification.

Reactive oxygen species acts as executor in radiation enhancement and autophagy inducing by AgNPs.

PubMed

Wu, Hao; Lin, Jun; Liu, Peidang; Huang, Zhihai; Zhao, Peng; Jin, Haizhen; Ma, Jun; Wen, Longping; Gu, Ning

2016-09-01

Malignant glioma is one of the most common intracranial tumor with a dismal prognosis. The radiosensitizing effect of silver nanoparticles (AgNPs) on glioma both in vitro and in vivo were demonstrated in the previous studies of our group. However, the underlying mechanism is still unclear. In this present study, the use of antioxidants is employed for the regulating of reactive oxygen species (ROS) in U251 cells treated with various agents, and the results shows that ROS played an essential role in the autophagy inducing and radiosensitization effect of AgNPs. Moreover, the inhibition of protective autophagy with 3-MA is another way to increase ROS, resulting in the increasing of cell death and apoptosis. Taken together, understanding the relationship between the elevated ROS and autophagy and the effect of ROS should be useful to the clinical applications of AgNPs. These findings could potentially be exploited for new therapeutic strategies in glioma radiotherapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Microglial Immune Response to Low Concentrations of Combustion-Generated Nanoparticles: An In Vitro Model of Brain Health

PubMed Central

Duffy, Cayla M.; Swanson, Jacob; Northrop, William; Nixon, Joshua P.; Butterick, Tammy A.

2018-01-01

The brain is the central regulator for integration and control of responses to environmental cues. Previous studies suggest that air pollution may directly impact brain health by triggering the onset of chronic neuroinflammation. We hypothesize that nanoparticle components of combustion-generated air pollution may underlie these effects. To test this association, a microglial in vitro biological sensor model was used for testing neuroinflammatory response caused by low-dose nanoparticle exposure. The model was first validated using 20 nm silver nanoparticles (AgNP). Next, neuroinflammatory response was tested after exposure to size-selected 20 nm combustion-generated nanoparticles (CGNP) collected from a modern diesel engine. We show that low concentrations of CGNPs promote low-grade inflammatory response indicated by increased pro-inflammatory cytokine release (tumor necrosis factor-α), similar to that observed after AgNP exposure. We also demonstrate increased production of reactive oxygen species and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) p65 phosphorylation in microglia after CGNP stimulation. Finally, we show conditioned media from CGNP-stimulated microglia significantly reduced hypothalamic neuronal survival in vitro. To our knowledge, this data show for the first time that exposure to AgNP and CGNP elicits microglial neuroinflammatory response through the activation of NF-κB. PMID:29522448

Influence of salinity on the toxicity of silver nanoparticles (AgNPs) and silver nitrate (AgNO3) in halophilic microalgae, Dunaliella salina.

PubMed

Johari, Seyed Ali; Sarkheil, Mehrdad; Behzadi Tayemeh, Mohammad; Veisi, Shakila

2018-06-13

This study aim to evaluate the potential toxic effects of citrate coated silver nanoparticles (AgNPs) and ionic silver (AgNO 3 ) on marine microalgae Dunaliella salina under three different salinities (35, 70, and 140 g/L). The toxicity was investigated according to modified OECD guideline (No. 201) by 72 h exposure of microalgae to various concentrations of each of the chemicals in Walne's saline media. According to the results, the growth inhibitory effects of AgNPs and AgNO 3 increased significantly coincidence with increasing time and concentration compared to control (P < 0.05). The values of median inhibitory concentrations (IC 50 ) of AgNPs and AgNO 3 based on average specific growth rate and yield for D. salina increased significantly with elevation of water salinity from 35 to 140 g/L (P < 0.05). Toxicity of AgNO 3 based on IC 50 to D. salina was significantly higher than AgNPs at all salinities (P < 0.05). In conclusion, both AgNPs and AgNO 3 inhibited the growth of D. salina at different saltwater medium. Copyright © 2018 Elsevier Ltd. All rights reserved.

An eco-benign synthesis of AgNPs using aqueous extract of Longan fruit peel: Antiproliferative response against human breast cancer cell line MCF-7, antioxidant and photocatalytic deprivation of methylene blue.

PubMed

Khan, Arif Ullah; Yuan, Qipeng; Khan, Zia Ul Haq; Ahmad, Aftab; Khan, Faheem Ullah; Tahir, Kamran; Shakeel, Muhammad; Ullah, Sadeeq

2018-05-07

Plants mediated synthesis of noble metal nanoparticles is encountered as a clean, environment friendly, lucrative and benign loom. The current study consists of clean and green synthesis of Silver nanoparticles (AgNPs). Phytoconstituents from Longan (Euphorbia longana Lam.) fruit peel were used to reduce Ag + into AgNPs. Different analytical techniques i.e. UV-vis Spectroscopy, X-ray diffraction spectroscopy (XRD), electron dispersive X-ray (EDX), High-resolution transmission electron microscopy (HRTEM) and Fourier transform infrared spectroscopy (FTIR) were used to analyze the synthesized AgNPs. AgNPs have localized surface plasmon resonance (LSPR) peak at 445 nm which is confirmed by UV-vis spectroscopy. HRTEM showed that the prepared AgNPs are spheroid in shape and well dispersed while XRD results showed that the AgNPs are face centered cubic crystalline. EDX confirmed the elemental composition of AgNPs. The antiproliferative response of AgNPs was assayed by an exhaustive MTT assay. AgNPs showed potent anticancer activity (88%) against breast cancer cells MCF-7. Moreover, the green produced AgNPs effectively scavenged 91% of the stable and harmful 2, 2-diphenyl-1-picrylhydrazyl (DPPH) free radical which confirms its' efficient antioxidant nature. AgNPs have profound photocatalytic degradation (99%) of methylene blue in a short period of time (7 min). The noteworthy biological and photocatalytic responses of the green and cleanly produced AgNPs are encountered to their well dispersion, petite volume and round shaped structure. Copyright © 2018 Elsevier B.V. All rights reserved.

Hydrodynamic chromatography coupled to single-particle ICP-MS for the simultaneous characterization of AgNPs and determination of dissolved Ag in plasma and blood of burn patients.

PubMed

Roman, Marco; Rigo, Chiara; Castillo-Michel, Hiram; Munivrana, Ivan; Vindigni, Vincenzo; Mičetić, Ivan; Benetti, Federico; Manodori, Laura; Cairns, Warren R L

2016-07-01

Silver nanoparticles (AgNPs) are increasingly used in medical devices as innovative antibacterial agents, but no data are currently available on their chemical transformations and fate in vivo in the human body, particularly on their potential to reach the circulatory system. To study the processes involving AgNPs in human plasma and blood, we developed an analytical method based on hydrodynamic chromatography (HDC) coupled to inductively coupled plasma mass spectrometry (ICP-MS) in single-particle detection mode. An innovative algorithm was implemented to deconvolute the signals of dissolved Ag and AgNPs and to extrapolate a multiparametric characterization of the particles in the same chromatogram. From a single injection, the method provides the concentration of dissolved Ag and the distribution of AgNPs in terms of hydrodynamic diameter, mass-derived diameter, number and mass concentration. This analytical approach is robust and suitable to study quantitatively the dynamics and kinetics of AgNPs in complex biological fluids, including processes such as agglomeration, dissolution and formation of protein coronas. The method was applied to study the transformations of AgNP standards and an AgNP-coated dressing in human plasma, supported by micro X-ray fluorescence (μXRF) and micro X-ray absorption near-edge spectroscopy (μXANES) speciation analysis and imaging, and to investigate, for the first time, the possible presence of AgNPs in the blood of three burn patients treated with the same dressing. Together with our previous studies, the results strongly support the hypothesis that the systemic mobilization of the metal after topical administration of AgNPs is driven by their dissolution in situ. Graphical Abstract Simplified scheme of the combined analytical approach adopted for studying the chemical dynamics of AgNPs in human plasma/blood.

Synthesis, kinetics and photocatalytic study of "ultra-small" Ag-NPs obtained by a green chemistry method using an extract of Rosa 'Andeli' double delight petals.

PubMed

Suárez-Cerda, Javier; Alonso-Nuñez, Gabriel; Espinoza-Gómez, Heriberto; Flores-López, Lucía Z

2015-11-15

This paper reports the effect of different concentrations of Rosa 'Andeli' double delight petals aqueous extract (PERA) in the synthesis of silver nanoparticles (Ag-NPs), using an easy green chemistry method. Its kinetics study and photocatalytic activity were also evaluated. The Ag-NPs were obtained using an aqueous silver nitrate solution (AgNO3) with 9.66% w/v, 7.25% w/v, and 4.20% w/v PERA as both reducing-stabilizing agent. The formation of the Ag-NPs was demonstrated by analysis of UV-vis spectroscopy, scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS) and transmission electron microscopy (TEM). TEM analysis shows spherical nanoparticles in shape and size between ∼0.5 and 1.4nm. A comparative study was done to determine which concentration was the best reducing-stabilizing agent, and we found out that "ultra-small" nanoparticles (0.5-1.1nm) were obtained with 9.66% w/v of PERA. The size of the Ag-NPs depends on the concentration of PERA and Ag(I). The reaction of formation of "ultra-small" Ag-NPs, proved to be first order for metallic precursor (silver) and second order for reducing-stabilizing agent (PERA). The Ag-NPs showed photocatalytic activity, in degradation of commercial dye with an efficiency of 95%. Copyright © 2015 Elsevier Inc. All rights reserved.

Comparative Cytotoxicity Study of Silver Nanoparticles (AgNPs) in a Variety of Rainbow Trout Cell Lines (RTL-W1, RTH-149, RTG-2) and Primary Hepatocytes

PubMed Central

Connolly, Mona; Fernandez-Cruz, Maria-Luisa; Quesada-Garcia, Alba; Alte, Luis; Segner, Helmut; Navas, Jose M.

2015-01-01

Among all classes of nanomaterials, silver nanoparticles (AgNPs) have potentially an important ecotoxicological impact, especially in freshwater environments. Fish are particularly susceptible to the toxic effects of silver ions and, with knowledge gaps regarding the contribution of dissolution and unique particle effects to AgNP toxicity, they represent a group of vulnerable organisms. Using cell lines (RTL-W1, RTH-149, RTG-2) and primary hepatocytes of rainbow trout (Oncorhynchus mykiss) as in vitro test systems, we assessed the cytotoxicity of the representative AgNP, NM-300K, and AgNO3 as an Ag+ ion source. Lack of AgNP interference with the cytotoxicity assays (AlamarBlue, CFDA-AM, NRU assay) and their simultaneous application point to the compatibility and usefulness of such a battery of assays. The RTH-149 and RTL-W1 liver cell lines exhibited similar sensitivity as primary hepatocytes towards AgNP toxicity. Leibovitz’s L-15 culture medium composition (high amino acid content) had an important influence on the behaviour and toxicity of AgNPs towards the RTL-W1 cell line. The obtained results demonstrate that, with careful consideration, such an in vitro approach can provide valuable toxicological data to be used in an integrated testing strategy for NM-300K risk assessment. PMID:26006119

The effect of biologically and chemically synthesized silver nanoparticles (AgNPs) on biofilm formation

NASA Astrophysics Data System (ADS)

Chojniak, Joanna; Biedroń, Izabela; Mendrek, Barbara; Płaza, Grażyna

2017-11-01

Bionanotechnology has emerged up as integration between biotechnology and nanotechnology for developing biosynthetic and environmental-friendly technology for synthesis of nanomaterials. Different types of nanomaterials like copper, zinc, titanium, magnesium, gold, and silver have applied in the various industries but silver nanoparticles have proved to be most effective against bacteria, viruses and eukaryotic microorganisms. The antimicrobial property of silver nanoparticles are widely known. Due to strong antibacterial property silver nanoparticles are used, e.g. in clothing, food industry, sunscreens, cosmetics and many household and environmental appliances. The aim of the study was to compare the effect of silver nanoparticles (AgNPs) synthesized biologically and chemically on the biofilm formation. The biofilm was formed by the bacteria isolated from the water supply network. The commonly used crystal violet assay (CV) was applied for biofilm analysis. In this study effect of biologically synthesized Ag-NPs on the biofilm formation was evaluated.

Aggregation-based colorimetric sensor for determination of prothioconazole fungicide using colloidal silver nanoparticles (AgNPs)

NASA Astrophysics Data System (ADS)

Ivrigh, Zahra Jafar-Nezhad; Fahimi-Kashani, Nafiseh; Hormozi-Nezhad, M. Reza

2017-12-01

There is a growing interest in developing high-performance sensors monitoring fungicides, due to their broadly usage and their adverse effects on humans and wildlife. In the present study, a colorimetric probe has been proposed for detection of prothioconazole based on aggregation of unmodified silver nanoparticles (AgNPs). Under optimized condition, linear relationships between the concentration of prothioconazole and the absorbance ratio of A500/A395 were found over the range of 0.01 μg·mL- 1 to 0.4 μg·mL- 1 with quantification limit as low as 1.7 ng·mL- 1. Furthermore, AgNPs color change from yellow to pink-orange in presence of prothioconazole, indicates highly sensitive naked-eye colorimetric assay for quantifying prothioconazole in real applications. The proposed approach was successfully used for the determination of prothioconazole in wheat flour and paddy water sample.

A perspective of mitochondrial dysfunction in rats treated with silver and titanium nanoparticles (AgNPs and TiNPs).

PubMed

Pereira, Lilian Cristina; Pazin, Murilo; Franco-Bernardes, Mariana Furio; Martins, Airton da Cunha; Barcelos, Gustavo Rafael Mazzaron; Pereira, Márcio Cesar; Mesquita, João Paulo; Rodrigues, Jairo Lisboa; Barbosa, Fernando; Dorta, Daniel Junqueira

2018-05-01

Nanotechnology is a growing branch of science that deals with the development of structural features bearing at least one dimension in the nano range. More specifically, nanomaterials are defined as objects with dimensions that range from 1 to 100 nm, which give rise to interesting properties. In particular, silver and titanium nanoparticles (AgNPs and TiNPs, respectively) are known for their biological and biomedical properties and are often used in consumer products such as cosmetics, food additives, kitchen utensils, and toys. This situation has increased environmental and occupational exposure to AgNPs and TiNPs, which has placed demand for the risk assessment of NPs. Indeed, the same properties that make nanomaterials so attractive could also prove deleterious to biological systems. Of particular concern is the effect of NPs on mitochondria because these organelles play an essential role in cellular homeostasis. In this scenario, this work aimed to study how AgNPs and TiNPs interact with the mitochondrial respiration chain and to analyze how this interaction interferes in the bioenergetics and oxidative state of the organelles after sub-chronic exposure. Mitochondria were exposed to the NPs by gavage treatment for 21 days to check whether co-exposure of the organelles to the two types of NPs elicited any mitochondrion-NP interaction. More specifically, male Wistar rats were randomly assigned to four groups. Groups I, II, III, and IV received mineral oil, TiNPs (100 μg/kg/day), AgNPs (100 μg/kg/day), and TiNPs + AgNPs (100 μg/kg/day), respectively, by gavage. The liver was immediately removed, and the mitochondria were isolated and used within 3 h. Exposure of mitochondria to TiNPs + AgNPs lowered the respiratory control ratio, causing an uncoupling effect in the oxidative phosphorylation system. Moreover, both types of NPs induced mitochondrial swelling. Extended exposure of mitochondria to the NPs maintained increased ROS levels and

Comparative effects on rat primary astrocytes and C6 rat glioma cells cultures after 24-h exposure to silver nanoparticles (AgNPs)

NASA Astrophysics Data System (ADS)

Salazar-García, Samuel; Silva-Ramírez, Ana Sonia; Ramirez-Lee, Manuel A.; Rosas-Hernandez, Hector; Rangel-López, Edgar; Castillo, Claudia G.; Santamaría, Abel; Martinez-Castañon, Gabriel A.; Gonzalez, Carmen

2015-11-01

The aim of this work was to compare the effects of 24-h exposure of rat primary astrocytes and C6 rat glioma cells to 7.8 nm AgNPs. Glioblastoma multiforme (GBM) is the most aggressive primary brain tumor and current treatments lead to diverse side-effects; for this reason, it is imperative to investigate new approaches, including those alternatives provided by nanotechnology, like nanomaterials (NMs) such as silver nanoparticles. Herein, we found that C6 rat glioma cells, but no primary astrocytes, decreased cell viability after AgNPs treatment; however, both cell types diminished their proliferation. The decrease of glioma C6 cells proliferation was related with necrosis, while in primary astrocytes, the decreased proliferation was associated with the induction of apoptosis. The ionic control (AgNO3) exerted a different profile than AgNPs; the bulk form did not modify the basal effect in each determination, whereas cisplatin, a well-known antitumoral drug used as a comparative control, promoted cytotoxicity in both cell types at specific concentrations. Our findings prompt the need to determine the fine molecular and cellular mechanisms involved in the differential biological responses to AgNPs in order to develop new tools or alternatives based on nanotechnology that may contribute to the understanding, impact and use of NMs in specific targets, like glioblastoma cells.

A systematic approach of removal mechanisms, control and optimization of silver nanoparticle in wastewater treatment plants.

PubMed

Vilela, Paulina; Liu, Hongbin; Lee, SeungChul; Hwangbo, Soonho; Nam, KiJeon; Yoo, ChangKyoo

2018-08-15

The release of silver nanoparticles (AgNPs) to wastewater caused by over-generation and poor treatment of the remaining nanomaterial has raised the interest of researchers. AgNPs can have a negative impact on watersheds and generate degradation of the effluent quality of wastewater treatment plants (WWTPs). The aim of this research is to design and analyze an integrated model system for the removal of AgNPs with high effluent quality in WWTPs using a systematic approach of removal mechanisms modeling, optimization, and control of the removal of silver nanoparticles. The activated sludge model 1 was modified with the inclusion of AgNPs removal mechanisms, such as adsorption/desorption, dissolution, and inhibition of microbial organisms. Response surface methodology was performed to minimize the AgNPs and total nitrogen concentrations in the effluent by optimizing operating conditions of the system. Then, the optimal operating conditions were utilized for the implementation of control strategies into the system for further analysis of enhancement of AgNPs removal efficiency. Thus, the overall AgNP removal efficiency was found to be slightly higher than 80%, which was an improvement of almost 7% compared to the BSM1 reference value. This study provides a systematic approach to find an optimal solution for enhancing AgNP removal efficiency in WWTPs and thereby to prevent pollution in the environment. Copyright © 2018 Elsevier B.V. All rights reserved.

Chitosan nanocomposite films based on Ag-NP and Au-NP biosynthesis by Bacillus Subtilis as packaging materials.

PubMed

Youssef, Ahmed M; Abdel-Aziz, Mohamed S; El-Sayed, Samah M

2014-08-01

Chitosan-silver (CS-Ag) and Chitosan-gold (CS-Au) nanocomposites films were synthesized by a simple chemical method. A local bacterial isolate identified as Bacillus subtilis ss subtilis was found to be capable to synthesize both silver nanoparticles (Ag-NP) and gold nanoparticles (Au-NP) from silver nitrate (AgNO3) and chloroauric acid (AuCl(4-)) solutions, respectively. The biosynthesis of both Ag-NP and Au-NP characterize using UV/vis spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM) and X-ray diffraction (XRD), and then added to chitosan by different ratios (0.5, 1 and 2%). The prepared chitosan nanocomposites films were characterize using UV, XRD, SEM and TEM. Moreover, the antibacterial activity of the prepared films was evaluated against gram positive (Staphylococcus aureus) and gram negative bacteria (Pseudomonas aerugenosa), fungi (Aspergillus niger) and yeast (Candida albicans). Therefore, these materials can be potential used as antimicrobial agents in packaging applications. Copyright © 2014 Elsevier B.V. All rights reserved.

Vehicular pollution modeling using the operational street pollution model (OSPM) for Chembur, Mumbai (India).

PubMed

Kumar, Awkash; Ketzel, Matthias; Patil, Rashmi S; Dikshit, Anil Kumar; Hertel, Ole

2016-06-01

Megacities in India such as Mumbai and Delhi are among the most polluted places in the world. In the present study, the widely used operational street pollution model (OSPM) is applied for assessing pollutant loads in the street canyons of Chembur, a suburban area just outside Mumbai city. Chembur is both industrialized and highly congested with vehicles. There are six major street canyons in this area, for which modeling has been carried out for NOx and particulate matter (PM). The vehicle emission factors for Indian cities have been developed by Automotive Research Association of India (ARAI) for PM, not specifically for PM10 or PM2.5. The model has been applied for 4 days of winter season and for the whole year to see the difference of effect of meteorology. The urban background concentrations have been obtained from an air quality monitoring station. Results have been compared with measured concentrations from the routine monitoring performed in Mumbai. NOx emissions originate mainly from vehicles which are ground-level sources and are emitting close to where people live. Therefore, those emissions are highly relevant. The modeled NOx concentration compared satisfactorily with observed data. However, this was not the case for PM, most likely because the emission inventory did not contain emission terms due to resuspended particulate matter.

Rapid colorimetric sensing of gadolinium by EGCG-derived AgNPs: the development of a nanohybrid bioimaging probe.

PubMed

Singh, Rohit Kumar; Mishra, Sourav; Jena, Satyapriya; Panigrahi, Bijayananda; Das, Bhaskar; Jayabalan, Rasu; Parhi, Pankaj Kumar; Mandal, Dindyal

2018-04-17

Polyphenol functionalized silver nanoparticles (AgNPs) have been developed and demonstrated as colorimetric sensors for the selective detection of gadolinium. The newly obtained AgNP-Gd3+ conjugates exhibit high aqueous dispersibility and excitation dependent fluorescence emission. The conjugates offer multicolor bioimaging potential owing to their excellent luminescence properties.

POLUTE. Forest Air Pollutant Uptake Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murphy, C.E. Jr.; Sinclair, T.R.

1992-02-13

POLUTE is a computer model designed to estimate the uptake of air pollutants by forests. The model utilizes submodels to describe atmospheric diffusion immediately above and within the canopy, and into the sink areas within or on the trees. The program implementing the model is general and can be used, with only minor changes, for any gaseous pollutant. The model provides an estimate describing the response of the vegetarian-atmosphere system to the environment as related to three types of processes: atmospheric diffusion, diffusion near and inside the absorbing plant, and the physical and chemical processes at the sink on ormore » within the plant.« less

Hydrology and sediment budget of Los Laureles Canyon, Tijuana, MX: Modelling channel, gully, and rill erosion with 3D photo-reconstruction, CONCEPTS, and AnnAGNPS

NASA Astrophysics Data System (ADS)

Taniguchi, Kristine; Gudiño, Napoleon; Biggs, Trent; Castillo, Carlos; Langendoen, Eddy; Bingner, Ron; Taguas, Encarnación; Liden, Douglas; Yuan, Yongping

2015-04-01

Several watersheds cross the US-Mexico boundary, resulting in trans-boundary environmental problems. Erosion in Tijuana, Mexico, increases the rate of sediment deposition in the Tijuana Estuary in the United States, altering the structure and function of the ecosystem. The well-being of residents in Tijuana is compromised by damage to infrastructure and homes built adjacent to stream channels, gully formation in dirt roads, and deposition of trash. We aim to understand the dominant source of sediment contributing to the sediment budget of the watershed (channel, gully, or rill erosion), where the hotspots of erosion are located, and what the impact of future planned and unplanned land use changes and Best Management Practices (BMPs) will be on sediment and storm flow. We will be using a mix of field methods, including 3D photo-reconstruction of stream channels, with two models, CONCEPTS and AnnAGNPS to constrain estimates of the sediment budget and impacts of land use change. Our research provides an example of how 3D photo-reconstruction and Structure from Motion (SfM) can be used to model channel evolution.

Highway Air Pollution Dispersion Modeling : Preliminary Evaluation of Thirteen Models

DOT National Transportation Integrated Search

1978-06-01

Thirteen highway air pollution dispersion models have been tested, using a portion of the Airedale air quality data base. The Transportation Air Pollution Studies (TAPS) System, a data base management system specifically designed for evaluating dispe...

Highway Air Pollution Dispersion Modeling : Preliminary Evaluation of Thirteen Models

DOT National Transportation Integrated Search

1977-01-01

Thirteen highway air pollution dispersion models have been tested, using a portion of the Airedale air quality data base. The Transportation Air Pollution Studies (TAPS) System, a data base management system specifically designed for evaluating dispe...

Low-dose AgNPs reduce lung mechanical function and innate immune defense in the absence of cellular toxicity.

PubMed

Botelho, Danielle J; Leo, Bey Fen; Massa, Christopher B; Sarkar, Srijata; Tetley, Terry D; Chung, Kian Fan; Chen, Shu; Ryan, Mary P; Porter, Alexandra E; Zhang, Junfeng; Schwander, Stephan K; Gow, Andrew J

2016-01-01

Multiple studies have examined the direct cellular toxicity of silver nanoparticles (AgNPs). However, the lung is a complex biological system with multiple cell types and a lipid-rich surface fluid; therefore, organ level responses may not depend on direct cellular toxicity. We hypothesized that interaction with the lung lining is a critical determinant of organ level responses. Here, we have examined the effects of low dose intratracheal instillation of AgNPs (0.05 μg/g body weight) 20 and 110 nm diameter in size, and functionalized with citrate or polyvinylpyrrolidone. Both size and functionalization were significant factors in particle aggregation and lipid interaction in vitro. One day post-intratracheal instillation lung function was assessed, and bronchoalveolar lavage (BAL) and lung tissue collected. There were no signs of overt inflammation. There was no change in surfactant protein-B content in the BAL but there was loss of surfactant protein-D with polyvinylpyrrolidone (PVP)-stabilized particles. Mechanical impedance data demonstrated a significant increase in pulmonary elastance as compared to control, greatest with 110 nm PVP-stabilized particles. Seven days post-instillation of PVP-stabilized particles increased BAL cell counts, and reduced lung function was observed. These changes resolved by 21 days. Hence, AgNP-mediated alterations in the lung lining and mechanical function resolve by 21 days. Larger particles and PVP stabilization produce the largest disruptions. These studies demonstrate that low dose AgNPs elicit deficits in both mechanical and innate immune defense function, suggesting that organ level toxicity should be considered.

An interprovincial cooperative game model for air pollution control in China.

PubMed

Xue, Jian; Zhao, Laijun; Fan, Longzhen; Qian, Ying

2015-07-01

The noncooperative air pollution reduction model (NCRM) that is currently adopted in China to manage air pollution reduction of each individual province has inherent drawbacks. In this paper, we propose a cooperative air pollution reduction game model (CRM) that consists of two parts: (1) an optimization model that calculates the optimal pollution reduction quantity for each participating province to meet the joint pollution reduction goal; and (2) a model that distribute the economic benefit of the cooperation (i.e., pollution reduction cost saving) among the provinces in the cooperation based on the Shapley value method. We applied the CRM to the case of SO2 reduction in the Beijing-Tianjin-Hebei region in China. The results, based on the data from 2003-2009, show that cooperation helps lower the overall SO2 pollution reduction cost from 4.58% to 11.29%. Distributed across the participating provinces, such a cost saving from interprovincial cooperation brings significant benefits to each local government and stimulates them for further cooperation in pollution reduction. Finally, sensitivity analysis is performed using the year 2009 data to test the parameters' effects on the pollution reduction cost savings. China is increasingly facing unprecedented pressure for immediate air pollution control. The current air pollution reduction policy does not allow cooperation and is less efficient. In this paper we developed a cooperative air pollution reduction game model that consists of two parts: (1) an optimization model that calculates the optimal pollution reduction quantity for each participating province to meet the joint pollution reduction goal; and (2) a model that distributes the cooperation gains (i.e., cost reduction) among the provinces in the cooperation based on the Shapley value method. The empirical case shows that such a model can help improve efficiency in air pollution reduction. The result of the model can serve as a reference for Chinese government

Antibacterial effect of silver nanoparticles and the modeling of bacterial growth kinetics using a modified Gompertz model.

PubMed

Chatterjee, Tanaya; Chatterjee, Barun K; Majumdar, Dipanwita; Chakrabarti, Pinak

2015-02-01

An alternative to conventional antibiotics is needed to fight against emerging multiple drug resistant pathogenic bacteria. In this endeavor, the effect of silver nanoparticle (Ag-NP) has been studied quantitatively on two common pathogenic bacteria Escherichia coli and Staphylococcus aureus, and the growth curves were modeled. The effect of Ag-NP on bacterial growth kinetics was studied by measuring the optical density, and was fitted by non-linear regression using the Logistic and modified Gompertz models. Scanning Electron Microscopy and fluorescence microscopy were used to study the morphological changes of the bacterial cells. Generation of reactive oxygen species for Ag-NP treated cells were measured by fluorescence emission spectra. The modified Gompertz model, incorporating cell death, fits the observed data better than the Logistic model. With increasing concentration of Ag-NP, the growth kinetics of both bacteria shows a decline in growth rate with simultaneous enhancement of death rate constants. The duration of the lag phase was found to increase with Ag-NP concentration. SEM showed morphological changes, while fluorescence microscopy using DAPI showed compaction of DNA for Ag-NP-treated bacterial cells. E. coli was found to be more susceptible to Ag-NP as compared to S. aureus. The modified Gompertz model, using a death term, was found to be useful in explaining the non-monotonic nature of the growth curve. The modified Gompertz model derived here is of general nature and can be used to study any microbial growth kinetics under the influence of antimicrobial agents. Copyright © 2014 Elsevier B.V. All rights reserved.

Synthesis of Silver nanoparticles (AgNPs) with Antibacterial Activity

NASA Astrophysics Data System (ADS)

Campillo Gloria, E.; Ederley, Vélez; Gladis, Morales; César, Hincapié; Jaime, Osorio; Oscar, Arnache; Uribe José, Ignacio; Franklin, Jaramillo

2017-06-01

The synthesis of nanomaterials is currently one of the most active in nanoscience branches; especially those help improve the human quality life. Silver nanoparticles (AgNPs) are an example of this as it is known to have inhibitory and bactericidal effects. In this work, we report the synthesis of silver nanoparticles by chemical reduction method of silver nitrate (AgNO3) from aqueous solution, using a mix of polivinyl pyrrolidone (PVP) - Aloe Vera as reducing agent and for stabilization and control of particle size. Silver nanoparticles obtained were characterized by Scanning Electron Microscopy (SEM), UV-visible spectroscopy and measurements using Zetasizer Nano ZS were applied to size estimation. The existence of surface plasmon resonance peak at λmax ~ 420 nm is evidence of silver nanoparticles formation. It was possible to standardize an appropriate protocol for the evaluation of bactericidal activity of the nanoparticles, for mesophilic microorganisms. Bactericidal activity above 90% against these kinds of bacteria was demonstrated.

Adsorption of silver nanoparticles from aqueous solution on copper-based metal organic frameworks (HKUST-1).

PubMed

Conde-González, J E; Peña-Méndez, E M; Rybáková, S; Pasán, J; Ruiz-Pérez, C; Havel, J

2016-05-01

Silver nanoparticles (AgNP) are emerging pollutants. The use of novel materials such as Cu-(benzene 1,3,5-tricarboxylate, BTC) Metal-Organic Framework (MOFs), for AgNP adsorption and their removal from aqueous solutions has been studied. The effect of different parameters was followed and isotherm model was suggested. MOFs adsorbed fast and efficiently AgNP in the range C0 < 10 mg L(-1), being Freundlich isotherm (R = 0.993) these data fitted to. Among studied parameters a remarkable effect of chloride on sorption was found, thus their possible interactions were considered. The high adsorption efficiency of AgNP was achieved and it was found to be very fast. The feasibility of adsorption on Cu-(BTC) was proved in spiked waters. The results showed the potential interest of new material as adsorbent for removing AgNP from environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Pollutant source identification model for water pollution incidents in small straight rivers based on genetic algorithm

NASA Astrophysics Data System (ADS)

Zhang, Shou-ping; Xin, Xiao-kang

2017-07-01

Identification of pollutant sources for river pollution incidents is an important and difficult task in the emergency rescue, and an intelligent optimization method can effectively compensate for the weakness of traditional methods. An intelligent model for pollutant source identification has been established using the basic genetic algorithm (BGA) as an optimization search tool and applying an analytic solution formula of one-dimensional unsteady water quality equation to construct the objective function. Experimental tests show that the identification model is effective and efficient: the model can accurately figure out the pollutant amounts or positions no matter single pollution source or multiple sources. Especially when the population size of BGA is set as 10, the computing results are sound agree with analytic results for a single source amount and position identification, the relative errors are no more than 5 %. For cases of multi-point sources and multi-variable, there are some errors in computing results for the reasons that there exist many possible combinations of the pollution sources. But, with the help of previous experience to narrow the search scope, the relative errors of the identification results are less than 5 %, which proves the established source identification model can be used to direct emergency responses.

Air Pollution Exposure Modeling for Health Studies | Science ...

EPA Pesticide Factsheets

Dr. Michael Breen is leading the development of air pollution exposure models, integrated with novel personal sensor technologies, to improve exposure and risk assessments for individuals in health studies. He is co-investigator for multiple health studies assessing the exposure and effects of air pollutants. These health studies include participants with asthma, diabetes, and coronary artery disease living in various U.S. cities. He has developed, evaluated, and applied novel exposure modeling and time-activity tools, which includes the Exposure Model for Individuals (EMI), GPS-based Microenvironment Tracker (MicroTrac) and Exposure Tracker models. At this seminar, Dr. Breen will present the development and application of these models to predict individual-level personal exposures to particulate matter (PM) for two health studies in central North Carolina. These health studies examine the association between PM and adverse health outcomes for susceptible individuals. During Dr. Breen’s visit, he will also have the opportunity to establish additional collaborations with researchers at Harvard University that may benefit from the use of exposure models for cohort health studies. These research projects that link air pollution exposure with adverse health outcomes benefit EPA by developing model-predicted exposure-dose metrics for individuals in health studies to improve the understanding of exposure-response behavior of air pollutants, and to reduce participant

Groundwater Pollution Source Identification using Linked ANN-Optimization Model

NASA Astrophysics Data System (ADS)

Ayaz, Md; Srivastava, Rajesh; Jain, Ashu

2014-05-01

Groundwater is the principal source of drinking water in several parts of the world. Contamination of groundwater has become a serious health and environmental problem today. Human activities including industrial and agricultural activities are generally responsible for this contamination. Identification of groundwater pollution source is a major step in groundwater pollution remediation. Complete knowledge of pollution source in terms of its source characteristics is essential to adopt an effective remediation strategy. Groundwater pollution source is said to be identified completely when the source characteristics - location, strength and release period - are known. Identification of unknown groundwater pollution source is an ill-posed inverse problem. It becomes more difficult for real field conditions, when the lag time between the first reading at observation well and the time at which the source becomes active is not known. We developed a linked ANN-Optimization model for complete identification of an unknown groundwater pollution source. The model comprises two parts- an optimization model and an ANN model. Decision variables of linked ANN-Optimization model contain source location and release period of pollution source. An objective function is formulated using the spatial and temporal data of observed and simulated concentrations, and then minimized to identify the pollution source parameters. In the formulation of the objective function, we require the lag time which is not known. An ANN model with one hidden layer is trained using Levenberg-Marquardt algorithm to find the lag time. Different combinations of source locations and release periods are used as inputs and lag time is obtained as the output. Performance of the proposed model is evaluated for two and three dimensional case with error-free and erroneous data. Erroneous data was generated by adding uniformly distributed random error (error level 0-10%) to the analytically computed concentration

Nitrogen component in nonpoint source pollution models

USDA-ARS?s Scientific Manuscript database

Pollutants entering a water body can be very destructive to the health of that system. Best Management Practices (BMPs) and/or conservation practices are used to reduce these pollutants, but understanding the most effective practices is very difficult. Watershed models are an effective tool to aid...

The impact of anticancer activity upon Beta vulgaris extract mediated biosynthesized silver nanoparticles (ag-NPs) against human breast (MCF-7), lung (A549) and pharynx (Hep-2) cancer cell lines.

PubMed

Venugopal, K; Ahmad, H; Manikandan, E; Thanigai Arul, K; Kavitha, K; Moodley, M K; Rajagopal, K; Balabhaskar, R; Bhaskar, M

2017-08-01

The present study tried for a phyto-synthetic method of producing silver nanoparticles (Ag-NPs) with size controlled as and eco-friendly route that can lead to their advanced production with decorative tranquil morphology. By inducing temperature fluctuation of the reaction mixture from 25 to 80°C the plasmon resonance band raised slowly which had an ultimate effect on size and shape of Ag-NPs as shown by UV-visible spectroscopy and TEM results. The biosynthesized nanoparticles showed good cytotoxic impact against MCF-7, A549 and Hep2 cells compared to normal cell lines. Compared to control plates, the percentage of cell growth inhibition was found to be high with as concentrations of Ag-NPs becomes more as determined by MTT assay. The AO/EtBr staining observations demonstrated that the mechanism of cell death induced by Ag-NPs was due to apoptosis in cancer cells. These present results propose that the silver nanoparticles (Ag-NPs) may be utilized as anticancer agents for the treatment of various cancer types. However, there is a need for study of in vivo examination of these nanoparticles to find their role and mechanism inside human body. Further, studies we plan to do biomarker fabrication from the green synthesized plant extract nanoparticles like silver, gold and copper nanoparticles with optimized shape and sizes and their enhancement of these noble nanoparticles. Copyright © 2017. Published by Elsevier B.V.

A model for interprovincial air pollution control based on futures prices.

PubMed

Zhao, Laijun; Xue, Jian; Gao, Huaizhu Oliver; Li, Changmin; Huang, Rongbing

2014-05-01

Based on the current status of research on tradable emission rights futures, this paper introduces basic market-related assumptions for China's interprovincial air pollution control problem. The authors construct an interprovincial air pollution control model based on futures prices: the model calculated the spot price of emission rights using a classic futures pricing formula, and determined the identities of buyers and sellers for various provinces according to a partitioning criterion, thereby revealing five trading markets. To ensure interprovincial cooperation, a rational allocation result for the benefits from this model was achieved using the Shapley value method to construct an optimal reduction program and to determine the optimal annual decisions for each province. Finally, the Beijing-Tianjin-Hebei region was used as a case study, as this region has recently experienced serious pollution. It was found that the model reduced the overall cost of reducing SO2 pollution. Moreover, each province can lower its cost for air pollution reduction, resulting in a win-win solution. Adopting the model would therefore enhance regional cooperation and promote the control of China's air pollution. The authors construct an interprovincial air pollution control model based on futures prices. The Shapley value method is used to rationally allocate the cooperation benefit. Interprovincial pollution control reduces the overall reduction cost of SO2. Each province can lower its cost for air pollution reduction by cooperation.

Development of a novel tridentate ligand for colorimetric detection of Mn2+ based on AgNPs.

PubMed

Wei, Jianyu; Chen, Jinfan; Yue, Guozong; Hu, Liangsheng; Zhao, Danqing; Zhu, Jing; Yang, Luming; Huang, Deshun; Zhao, Pengxiang

2018-05-09

A novel tridentate ligand nitrilotris(methylene)tris(1,2,3-triazole)triacetate (NTTTA) has been synthesized by click reaction and followed with ester hydrolysis reaction. The silver nanoparticles (AgNPs) were then modified and stabilized by this ligand, and subsequently been employed for the highly selective and sensitive colorimetric detection of Mn 2+ in aqueous solution. The presence of Mn 2+ can cause the aggregation of AgNPs, which leads to the color change of the dispersion from yellow to brown, as well as the decrease and red-shift of the surface plasmon resonance absorption. The detection limit of Mn 2+ was as approximately 0.5 μM by the naked eyes. UV-vis spectroscopy analysis showed a good linear relationship between the logarithm of the ratios (A 550 /A 395 ) and the concentration of Mn 2+ over the range of 0.05 μM-10 μM, and the LOD was calculated to be 12.6 nM (S/N = 3). The present assay showed good simplicity without the need of adjusting the pH value. The feasibility of this technique was evaluated for successful detection of Mn 2+ in tap water and lake water samples, with good recoveries. Copyright © 2018 Elsevier B.V. All rights reserved.

Population-production-pollution nexus based air pollution management model for alleviating the atmospheric crisis in Beijing, China.

PubMed

Zeng, X T; Tong, Y F; Cui, L; Kong, X M; Sheng, Y N; Chen, L; Li, Y P

2017-07-15

In recent years, increscent emissions in the city of Beijing due to expanded population, accelerated industrialization and inter-regional pollutant transportation have led to hazardous atmospheric pollution issues. Although a number of anthropogenic control measures have been put into use, frequent/severe haze events have still challenged regional governments. In this study, a hybrid population-production-pollution nexus model (PPP) is proposed for air pollution management and air quality planning (AMP) with the aim to coordinate human activities and environmental protection. A fuzzy-stochastic mixed quadratic programming method (FSQ) is developed and introduced into a PPP for tackling atmospheric pollution issues with uncertainties. Based on the contribution of an index of population-production-pollution, a hybrid PPP-based AMP model that considers employment structure, industrial layout pattern, production mode, pollutant purification efficiency and a pollution mitigation scheme have been applied in Beijing. Results of the adjustment of employment structure, pollution mitigation scheme, and green gross domestic product under various environmental regulation scenarios are obtained and analyzed. This study can facilitate the identification of optimized policies for alleviating population-production-emission conflict in the study region, as well as ameliorating the hazardous air pollution crisis at an urban level. Copyright © 2017 Elsevier Ltd. All rights reserved.

A simulation of water pollution model parameter estimation

NASA Technical Reports Server (NTRS)

Kibler, J. F.

1976-01-01

A parameter estimation procedure for a water pollution transport model is elaborated. A two-dimensional instantaneous-release shear-diffusion model serves as representative of a simple transport process. Pollution concentration levels are arrived at via modeling of a remote-sensing system. The remote-sensed data are simulated by adding Gaussian noise to the concentration level values generated via the transport model. Model parameters are estimated from the simulated data using a least-squares batch processor. Resolution, sensor array size, and number and location of sensor readings can be found from the accuracies of the parameter estimates.

The model SIRANE for atmospheric urban pollutant dispersion; part I, presentation of the model

NASA Astrophysics Data System (ADS)

Soulhac, Lionel; Salizzoni, Pietro; Cierco, F.-X.; Perkins, Richard

2011-12-01

In order to control and manage urban air quality, public authorities require an integrated approach that incorporates direct measurements and modelling of mean pollutant concentrations. These have to be performed by means of operational modelling tools, that simulate the transport of pollutants within and above the urban canopy over a large number of streets. The operational models must be able to assess rapidly a large variety of situations and with limited computing resources. SIRANE is an operational urban dispersion model based on a simplified description of the urban geometry that adopts parametric relations for the pollutant transfer phenomena within and out of the urban canopy. The streets in a city district are modelled as a network of connected street segments. The flow within each street is driven by the component of the external wind parallel to the street, and the pollutant is assumed to be uniformly mixed within the street. The model contains three main mechanisms for transport in and out of a street: advection along the street axis, diffusion across the interface between the street and the overlying air flow and exchanges with other streets at street intersections. The dispersion of pollutants advected or diffused out of the streets is taken into account using a Gaussian plume model, with the standard deviations σ y and σ z parameterised by the similarity theory. The input data for the final model are the urban geometry, the meteorological parameters, the background concentration of pollutants advected into the model domain by the wind and the emissions within each street in the network.

Antimicrobial kinetics of Alstonia scholaris bark extract-mediated AgNPs

NASA Astrophysics Data System (ADS)

Supraja, N.; Prasad, T. N. V. K. V.; David, E.; Giridhara Krishna, T.

2016-06-01

Nanobiotechnology is considered as one of the important branches of nanotechnology, and research on synthesis of nanoscale materials, silver in particular, using plant and plant parts has been progressing rapidly. Herein, we used bark extract of Alstonia scholaris one of the most important medicinal plants to synthesize silver nanoparticles (AgNPs) which exhibited excellent antimicrobial properties against biofilm formed in drinking water PVC pipes. The biosynthesis of silver nanoparticles was done by treating 90 mL of 1 mM AgNO3 aqueous solution with 10 mL of 5 % bark extract. As-prepared silver nanoparticles were characterized using the biophysical techniques such as UV-Vis spectroscopy, Fourier transform infrared spectroscopy, X-ray diffraction, thermogravimetric analysis, transmission electron microscopy, and dynamic light scattering for the measurement of hydrodynamic diameter and zeta potential. The kinetics of the antimicrobial activity against PVC biofilm of prepared silver nanoparticles were done using comparative solution suspension time-killing assessments and which are evidenced in Epi-fluorescent microscopic observations.

Silver Nanoparticles in the Water Environment in Malaysia: Inspection, characterization, removal, modeling, and future perspective.

PubMed

Syafiuddin, Achmad; Salmiati, Salmiati; Hadibarata, Tony; Kueh, Ahmad Beng Hong; Salim, Mohd Razman; Zaini, Muhammad Abbas Ahmad

2018-01-17

The current status of silver nanoparticles (AgNPs) in the water environment in Malaysia was examined and reported. For inspection, two rivers and two sewage treatment plants (STPs) were selected. Two activated carbons derived from oil palm (ACfOPS) and coconut (ACfCS) shells were proposed as the adsorbent to remove AgNPs. It was found that the concentrations of AgNPs in the rivers and STPs are in the ranges of 0.13 to 10.16 mg L -1 and 0.13 to 20.02 mg L -1 , respectively, with the highest concentration measured in July. ACfOPS and ACfCS removed up to 99.6 and 99.9% of AgNPs, respectively, from the water. The interaction mechanism between AgNPs and the activated carbon surface employed in this work was mainly the electrostatic force interaction via binding Ag + with O - presented in the activated carbon to form AgO. Fifteen kinetic models were compared statistically to describe the removal of AgNPs. It was found that the experimental adsorption data can be best described using the mixed 1,2-order model. Therefore, this model has the potential to be a candidate for a general model to describe AgNPs adsorption using numerous materials, its validation of which has been confirmed with other material data from previous works.

A comparison of self reported air pollution problems and GIS-modeled levels of air pollution in people with and without chronic diseases

PubMed Central

Piro, Fredrik Niclas; Madsen, Christian; Næss, Øyvind; Nafstad, Per; Claussen, Bjørgulf

2008-01-01

Objective To explore various contributors to people's reporting of self reported air pollution problems in area of living, including GIS-modeled air pollution, and to investigate whether those with respiratory or other chronic diseases tend to over-report air pollution problems, compared to healthy people. Methods Cross-sectional data from the Oslo Health Study (2000–2001) were linked with GIS-modeled air pollution data from the Norwegian Institute of Air Research. Multivariate regression analyses were performed. 14 294 persons aged 30, 40, 45, 60 or 75 years old with complete information on modeled and self reported air pollution were included. Results People who reported air pollution problems were exposed to significantly higher GIS-modeled air pollution levels than those who did not report such problems. People with chronic disease, reported significantly more air pollution problems after adjustment for modeled levels of nitrogen dioxides, socio-demographic variables, smoking, depression, dwelling conditions and an area deprivation index, even if they had a non-respiratory disease. No diseases, however, were significantly associated with levels of nitrogen dioxides. Conclusion Self reported air pollution problems in area of living are strongly associated with increased levels of GIS-modeled air pollution. Over and above this, those who report to have a chronic disease tend to report more air pollution problems in area of living, despite no significant difference in air pollution exposure compared to healthy people, and no associations between these diseases and NO2. Studies on the association between self reported air pollution problems and health should be aware of the possibility that disease itself may influence the reporting of air pollution. PMID:18307757

InMAP: A model for air pollution interventions

DOE PAGES

Tessum, Christopher W.; Hill, Jason D.; Marshall, Julian D.; ...

2017-04-19

Mechanistic air pollution modeling is essential in air quality management, yet the extensive expertise and computational resources required to run most models prevent their use in many situations where their results would be useful. We present InMAP (Intervention Model for Air Pollution), which offers an alternative to comprehensive air quality models for estimating the air pollution health impacts of emission reductions and other potential interventions. InMAP estimates annual-average changes in primary and secondary fine particle (PM2.5) concentrations—the air pollution outcome generally causing the largest monetized health damages–attributable to annual changes in precursor emissions. InMAP leverages pre-processed physical and chemical informationmore » from the output of a state-of-the-science chemical transport model and a variable spatial resolution computational grid to perform simulations that are several orders of magnitude less computationally intensive than comprehensive model simulations. In comparisons we run, InMAP recreates comprehensive model predictions of changes in total PM2.5 concentrations with population-weighted mean fractional bias (MFB) of -17% and population-weighted R2 = 0.90. Although InMAP is not specifically designed to reproduce total observed concentrations, it is able to do so within published air quality model performance criteria for total PM2.5. Potential uses of InMAP include studying exposure, health, and environmental justice impacts of potential shifts in emissions for annual-average PM2.5. InMAP can be trained to run for any spatial and temporal domain given the availability of appropriate simulation output from a comprehensive model. The InMAP model source code and input data are freely available online under an open-source license.« less

InMAP: A model for air pollution interventions

PubMed Central

Hill, Jason D.; Marshall, Julian D.

2017-01-01

Mechanistic air pollution modeling is essential in air quality management, yet the extensive expertise and computational resources required to run most models prevent their use in many situations where their results would be useful. Here, we present InMAP (Intervention Model for Air Pollution), which offers an alternative to comprehensive air quality models for estimating the air pollution health impacts of emission reductions and other potential interventions. InMAP estimates annual-average changes in primary and secondary fine particle (PM2.5) concentrations—the air pollution outcome generally causing the largest monetized health damages–attributable to annual changes in precursor emissions. InMAP leverages pre-processed physical and chemical information from the output of a state-of-the-science chemical transport model and a variable spatial resolution computational grid to perform simulations that are several orders of magnitude less computationally intensive than comprehensive model simulations. In comparisons run here, InMAP recreates comprehensive model predictions of changes in total PM2.5 concentrations with population-weighted mean fractional bias (MFB) of −17% and population-weighted R2 = 0.90. Although InMAP is not specifically designed to reproduce total observed concentrations, it is able to do so within published air quality model performance criteria for total PM2.5. Potential uses of InMAP include studying exposure, health, and environmental justice impacts of potential shifts in emissions for annual-average PM2.5. InMAP can be trained to run for any spatial and temporal domain given the availability of appropriate simulation output from a comprehensive model. The InMAP model source code and input data are freely available online under an open-source license. PMID:28423049

InMAP: A model for air pollution interventions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tessum, Christopher W.; Hill, Jason D.; Marshall, Julian D.

Mechanistic air pollution modeling is essential in air quality management, yet the extensive expertise and computational resources required to run most models prevent their use in many situations where their results would be useful. We present InMAP (Intervention Model for Air Pollution), which offers an alternative to comprehensive air quality models for estimating the air pollution health impacts of emission reductions and other potential interventions. InMAP estimates annual-average changes in primary and secondary fine particle (PM2.5) concentrations—the air pollution outcome generally causing the largest monetized health damages–attributable to annual changes in precursor emissions. InMAP leverages pre-processed physical and chemical informationmore » from the output of a state-of-the-science chemical transport model and a variable spatial resolution computational grid to perform simulations that are several orders of magnitude less computationally intensive than comprehensive model simulations. In comparisons we run, InMAP recreates comprehensive model predictions of changes in total PM2.5 concentrations with population-weighted mean fractional bias (MFB) of -17% and population-weighted R2 = 0.90. Although InMAP is not specifically designed to reproduce total observed concentrations, it is able to do so within published air quality model performance criteria for total PM2.5. Potential uses of InMAP include studying exposure, health, and environmental justice impacts of potential shifts in emissions for annual-average PM2.5. InMAP can be trained to run for any spatial and temporal domain given the availability of appropriate simulation output from a comprehensive model. The InMAP model source code and input data are freely available online under an open-source license.« less

Modelling the effect of severe storms in coastal pollution

NASA Astrophysics Data System (ADS)

Grau, A.; Bolea, Y.; Guerra, E.

2009-09-01

Modelling and simulation of real events can be very useful to prevent environmental disasters, but these disasters can affect the health and life of human beings; then such tools become definitively necessary for governmental authorities to avoid population risk. In this wok we present a mathematical model that combines the effect of Mediterranean storms together with the effect of wastewater emissary dissolutions at the sea. The emissary model corresponds to a Catalan wastewater plant, the Besos plant in Barcelona. This plant throws the wastewater to the Mediterranean Sea with a 3-km pipe emissary, after a bacteriologically polluted secondary treatment. This polluted water is dissoluted in the salty water, provoking the death of all bacteria agents before they reach the coast. But in difficult conditions under violent storms, with strong East winds, the bacteriological polluted dissolution reaches the shore before the bacteria die and, therefore, a severe coastal pollution is produced. Its consequence can incur in a public health problem and the different governmental agencies activate great alarms to avoid population hazard. Storms modelling permits to evaluate the risk of coastal pollution predicting the wastewater dissolution path and velocity. Several simulations are presented under different storm conditions, making this tool very useful for the environmental protection agencies in the Catalan government.

Exposure to traffic pollution: comparison between measurements and a model.

PubMed

Alili, F; Momas, I; Callais, F; Le Moullec, Y; Sacre, C; Chiron, M; Flori, J P

2001-01-01

French researchers from the Building Scientific and Technical Center have produced a traffic-exposure index. To achieve this, they used an air pollution dispersion model that enabled them to calculate automobile pollutant concentrations in front of subjects' residences and places of work. Researchers used this model, which was tested at 27 Paris canyon street sites, and compared nitrogen oxides measurements obtained with passive samplers during a 6-wk period and calculations derived from the model. There was a highly significant correlation (r = .83) between the 2 series of values; their mean concentrations were not significantly different. The results suggested that the aforementioned model could be a useful epidemiological tool for the classification of city dwellers by present-or even cumulative exposure to automobile air pollution.

Mapping real-time air pollution health risk for environmental management: Combining mobile and stationary air pollution monitoring with neural network models.

PubMed

Adams, Matthew D; Kanaroglou, Pavlos S

2016-03-01

Air pollution poses health concerns at the global scale. The challenge of managing air pollution is significant because of the many air pollutants, insufficient funds for monitoring and abatement programs, and political and social challenges in defining policy to limit emissions. Some governments provide citizens with air pollution health risk information to allow them to limit their exposure. However, many regions still have insufficient air pollution monitoring networks to provide real-time mapping. Where available, these risk mapping systems either provide absolute concentration data or the concentrations are used to derive an Air Quality Index, which provides the air pollution risk for a mix of air pollutants with a single value. When risk information is presented as a single value for an entire region it does not inform on the spatial variation within the region. Without an understanding of the local variation residents can only make a partially informed decision when choosing daily activities. The single value is typically provided because of a limited number of active monitoring units in the area. In our work, we overcome this issue by leveraging mobile air pollution monitoring techniques, meteorological information and land use information to map real-time air pollution health risks. We propose an approach that can provide improved health risk information to the public by applying neural network models within a framework that is inspired by land use regression. Mobile air pollution monitoring campaigns were conducted across Hamilton from 2005 to 2013. These mobile air pollution data were modelled with a number of predictor variables that included information on the surrounding land use characteristics, the meteorological conditions, air pollution concentrations from fixed location monitors, and traffic information during the time of collection. Fine particulate matter and nitrogen dioxide were both modelled. During the model fitting process we reserved

Silver Nanoparticle-Mediated Cellular Responses in Various Cell Lines: An in Vitro Model

PubMed Central

Zhang, Xi-Feng; Shen, Wei; Gurunathan, Sangiliyandi

2016-01-01

Silver nanoparticles (AgNPs) have attracted increased interest and are currently used in various industries including medicine, cosmetics, textiles, electronics, and pharmaceuticals, owing to their unique physical and chemical properties, particularly as antimicrobial and anticancer agents. Recently, several studies have reported both beneficial and toxic effects of AgNPs on various prokaryotic and eukaryotic systems. To develop nanoparticles for mediated therapy, several laboratories have used a variety of cell lines under in vitro conditions to evaluate the properties, mode of action, differential responses, and mechanisms of action of AgNPs. In vitro models are simple, cost-effective, rapid, and can be used to easily assess efficacy and performance. The cytotoxicity, genotoxicity, and biocompatibility of AgNPs depend on many factors such as size, shape, surface charge, surface coating, solubility, concentration, surface functionalization, distribution of particles, mode of entry, mode of action, growth media, exposure time, and cell type. Cellular responses to AgNPs are different in each cell type and depend on the physical and chemical nature of AgNPs. This review evaluates significant contributions to the literature on biological applications of AgNPs. It begins with an introduction to AgNPs, with particular attention to their overall impact on cellular effects. The main objective of this review is to elucidate the reasons for different cell types exhibiting differential responses to nanoparticles even when they possess similar size, shape, and other parameters. Firstly, we discuss the cellular effects of AgNPs on a variety of cell lines; Secondly, we discuss the mechanisms of action of AgNPs in various cellular systems, and try to elucidate how AgNPs interact with different mammalian cell lines and produce significant effects; Finally, we discuss the cellular activation of various signaling molecules in response to AgNPs, and conclude with future perspectives

A cooperative reduction model for regional air pollution control in China that considers adverse health effects and pollutant reduction costs.

PubMed

Xie, Yujing; Zhao, Laijun; Xue, Jian; Hu, Qingmi; Xu, Xiang; Wang, Hongbo

2016-12-15

How to effectively control severe regional air pollution has become a focus of global concern recently. The non-cooperative reduction model (NCRM) is still the main air pollution control pattern in China, but it is both ineffective and costly, because each province must independently fight air pollution. Thus, we proposed a cooperative reduction model (CRM), with the goal of maximizing the reduction in adverse health effects (AHEs) at the lowest cost by encouraging neighboring areas to jointly control air pollution. CRM has two parts: a model of optimal pollutant removal rates using two optimization objectives (maximizing the reduction in AHEs and minimizing pollutant reduction cost) while meeting the regional pollution control targets set by the central government, and a model that allocates the cooperation benefits (i.e., health improvement and cost reduction) among the participants according to their contributions using the Shapley value method. We applied CRM to the case of sulfur dioxide (SO 2 ) reduction in Yangtze River Delta region. Based on data from 2003 to 2013, and using mortality due to respiratory and cardiovascular diseases as the health endpoints, CRM saves 437 more lives than NCRM, amounting to 12.1% of the reduction under NCRM. CRM also reduced costs by US $65.8×10 6 compared with NCRM, which is 5.2% of the total cost of NCRM. Thus, CRM performs significantly better than NCRM. Each province obtains significant benefits from cooperation, which can motivate them to actively cooperate in the long term. A sensitivity analysis was performed to quantify the effects of parameter values on the cooperation benefits. Results shown that the CRM is not sensitive to the changes in each province's pollutant carrying capacity and the minimum pollutant removal capacity, but sensitive to the maximum pollutant reduction capacity. Moreover, higher cooperation benefits will be generated when a province's maximum pollutant reduction capacity increases. Copyright �

Stochastic modeling for river pollution of Sungai Perlis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yunus, Nurul Izzaty Mohd.; Rahman, Haliza Abd.; Bahar, Arifah

2015-02-03

River pollution has been recognized as a contributor to a wide range of health problems and disorders in human. It can pose health dangers to humans who come into contact with it, either directly or indirectly. Therefore, it is most important to measure the concentration of Biochemical Oxygen Demand (BOD) as a water quality parameter since the parameter has long been the basic means for determining the degree of water pollution in rivers. In this study, BOD is used as a parameter to estimate the water quality at Sungai Perlis. It has been observed that Sungai Perlis is polluted duemore » to lack of management and improper use of resources. Therefore, it is of importance to model the Sungai Perlis water quality in order to describe and predict the water quality systems. The BOD concentration secondary data set is used which was extracted from the Drainage and Irrigation Department Perlis State website. The first order differential equation from Streeter – Phelps model was utilized as a deterministic model. Then, the model was developed into a stochastic model. Results from this study shows that the stochastic model is more adequate to describe and predict the BOD concentration and the water quality systems in Sungai Perlis by having smaller value of mean squared error (MSE)« less

Influence of pH on the transport of silver nanoparticles in saturated porous media: laboratory experiments and modeling

NASA Astrophysics Data System (ADS)

Flory, Jason; Kanel, Sushil R.; Racz, LeeAnn; Impellitteri, Christopher A.; Silva, Rendahandi G.; Goltz, Mark N.

2013-03-01

Given the ubiquity of silver nanoparticles (AgNPs) and their potential for toxic effects on both humans and the environment, it is important to understand their environmental fate and transport. The purpose of this study is to gain information on the transport properties of commercial AgNP suspensions in a glass bead-packed column under saturated flow conditions at different solution pH levels. Commercial AgNPs were characterized using high-resolution transmission electron microscopy, dynamic light scattering, X-ray photoelectron spectroscopy, ultraviolet visible spectroscopy, Fourier transform infrared spectroscopy, thermogravimetric analysis, and X-ray diffraction. Transport data were collected at different pH levels (4, 6.5, 9, and 11) at fixed ionic strength. Capture of AgNPs increased as the pH of the solution increased from 4 to 6.5. Further increase in pH to 9 and 11 decreased the attachment of AgNPs to the glass beads. AgNP concentration versus time breakthrough data were simulated using an advection-dispersion model incorporating both irreversible and reversible attachment. In particular, a reversible attachment model is required to simulate breakthrough curve tailing at near neutral pH, when attachment is most significant. The laboratory and modeling study reveals that for natural groundwaters, AgNP transport in porous media may be retarded due to capture; but ultimately, most of the mass may be slowly released over time.

Modeling the risk of water pollution by pesticides from imbalanced data.

PubMed

Trajanov, Aneta; Kuzmanovski, Vladimir; Real, Benoit; Perreau, Jonathan Marks; Džeroski, Sašo; Debeljak, Marko

2018-04-30

The pollution of ground and surface waters with pesticides is a serious ecological issue that requires adequate treatment. Most of the existing water pollution models are mechanistic mathematical models. While they have made a significant contribution to understanding the transfer processes, they face the problem of validation because of their complexity, the user subjectivity in their parameterization, and the lack of empirical data for validation. In addition, the data describing water pollution with pesticides are, in most cases, very imbalanced. This is due to strict regulations for pesticide applications, which lead to only a few pollution events. In this study, we propose the use of data mining to build models for assessing the risk of water pollution by pesticides in field-drained outflow water. Unlike the mechanistic models, the models generated by data mining are based on easily obtainable empirical data, while the parameterization of the models is not influenced by the subjectivity of ecological modelers. We used empirical data from field trials at the La Jaillière experimental site in France and applied the random forests algorithm to build predictive models that predict "risky" and "not-risky" pesticide application events. To address the problems of the imbalanced classes in the data, cost-sensitive learning and different measures of predictive performance were used. Despite the high imbalance between risky and not-risky application events, we managed to build predictive models that make reliable predictions. The proposed modeling approach can be easily applied to other ecological modeling problems where we encounter empirical data with highly imbalanced classes.

Modelling Pollutant Dispersion in a Street Network

NASA Astrophysics Data System (ADS)

Salem, N. Ben; Garbero, V.; Salizzoni, P.; Lamaison, G.; Soulhac, L.

2015-04-01

This study constitutes a further step in the analysis of the performances of a street network model to simulate atmospheric pollutant dispersion in urban areas. The model, named SIRANE, is based on the decomposition of the urban atmosphere into two sub-domains: the urban boundary layer, whose dynamics is assumed to be well established, and the urban canopy, represented as a series of interconnected boxes. Parametric laws govern the mass exchanges between the boxes under the assumption that the pollutant dispersion within the canopy can be fully simulated by modelling three main bulk transfer phenomena: channelling along street axes, transfers at street intersections, and vertical exchange between street canyons and the overlying atmosphere. Here, we aim to evaluate the reliability of the parametrizations adopted to simulate these phenomena, by focusing on their possible dependence on the external wind direction. To this end, we test the model against concentration measurements within an idealized urban district whose geometrical layout closely matches the street network represented in SIRANE. The analysis is performed for an urban array with a fixed geometry and a varying wind incidence angle. The results show that the model provides generally good results with the reference parametrizations adopted in SIRANE and that its performances are quite robust for a wide range of the model parameters. This proves the reliability of the street network approach in simulating pollutant dispersion in densely built city districts. The results also show that the model performances may be improved by considering a dependence of the wind fluctuations at street intersections and of the vertical exchange velocity on the direction of the incident wind. This opens the way for further investigations to clarify the dependence of these parameters on wind direction and street aspect ratios.

Health benefit modelling and optimization of vehicular pollution control strategies

NASA Astrophysics Data System (ADS)

Sonawane, Nayan V.; Patil, Rashmi S.; Sethi, Virendra

2012-12-01

This study asserts that the evaluation of pollution reduction strategies should be approached on the basis of health benefits. The framework presented could be used for decision making on the basis of cost effectiveness when the strategies are applied concurrently. Several vehicular pollution control strategies have been proposed in literature for effective management of urban air pollution. The effectiveness of these strategies has been mostly studied as a one at a time approach on the basis of change in pollution concentration. The adequacy and practicality of such an approach is studied in the present work. Also, the assessment of respective benefits of these strategies has been carried out when they are implemented simultaneously. An integrated model has been developed which can be used as a tool for optimal prioritization of various pollution management strategies. The model estimates health benefits associated with specific control strategies. ISC-AERMOD View has been used to provide the cause-effect relation between control options and change in ambient air quality. BenMAP, developed by U.S. EPA, has been applied for estimation of health and economic benefits associated with various management strategies. Valuation of health benefits has been done for impact indicators of premature mortality, hospital admissions and respiratory syndrome. An optimization model has been developed to maximize overall social benefits with determination of optimized percentage implementations for multiple strategies. The model has been applied for sub-urban region of Mumbai city for vehicular sector. Several control scenarios have been considered like revised emission standards, electric, CNG, LPG and hybrid vehicles. Reduction in concentration and resultant health benefits for the pollutants CO, NOx and particulate matter are estimated for different control scenarios. Finally, an optimization model has been applied to determine optimized percentage implementation of specific

Investigating Nitrogen Pollution: Activities and Models.

ERIC Educational Resources Information Center

Green Teacher, 2000

2000-01-01

Introduces activities on nitrogen, nitrogen pollution from school commuters, nitrogen response in native and introduced species, and nutrient loading models. These activities help students determine the nitrogen contribution from their parents' cars, test native plant responses to nitrogen, and experiment with the results of removing water from…

Uncertainty characterization and quantification in air pollution models. Application to the ADMS-Urban model.

NASA Astrophysics Data System (ADS)

Debry, E.; Malherbe, L.; Schillinger, C.; Bessagnet, B.; Rouil, L.

2009-04-01

Evaluation of human exposure to atmospheric pollution usually requires the knowledge of pollutants concentrations in ambient air. In the framework of PAISA project, which studies the influence of socio-economical status on relationships between air pollution and short term health effects, the concentrations of gas and particle pollutants are computed over Strasbourg with the ADMS-Urban model. As for any modeling result, simulated concentrations come with uncertainties which have to be characterized and quantified. There are several sources of uncertainties related to input data and parameters, i.e. fields used to execute the model like meteorological fields, boundary conditions and emissions, related to the model formulation because of incomplete or inaccurate treatment of dynamical and chemical processes, and inherent to the stochastic behavior of atmosphere and human activities [1]. Our aim is here to assess the uncertainties of the simulated concentrations with respect to input data and model parameters. In this scope the first step consisted in bringing out the input data and model parameters that contribute most effectively to space and time variability of predicted concentrations. Concentrations of several pollutants were simulated for two months in winter 2004 and two months in summer 2004 over five areas of Strasbourg. The sensitivity analysis shows the dominating influence of boundary conditions and emissions. Among model parameters, the roughness and Monin-Obukhov lengths appear to have non neglectable local effects. Dry deposition is also an important dynamic process. The second step of the characterization and quantification of uncertainties consists in attributing a probability distribution to each input data and model parameter and in propagating the joint distribution of all data and parameters into the model so as to associate a probability distribution to the modeled concentrations. Several analytical and numerical methods exist to perform an

Modeling Trace Pollutants in the North Atlantic Free Troposphere and Comparisons with Observed Pollutant Concentrations at Pico

NASA Astrophysics Data System (ADS)

Sanyal, S.; Wuebbles, D. J.; Olsen, S. C.; Mazzoleni, L. R.; Mazzoleni, C.; Helmig, D.; Fialho, P. J.

2016-12-01

This study focuses on modeling free tropospheric aerosol and co-pollutants after trans-Atlantic transport of North American air pollution to the Pico Mountain Observatory (PMO) using the 3D global chemistry climate model CAM-Chem (version 4) and analyzing the model simulations relative to in-situ summertime measurements of carbon monoxide (CO), ozone (O3) and black carbon (BC) at the Pico Mountain Observatory (PMO) located in the Azores, Portugal from 2009 - 2011. The elevation of PMO ( 2225m above mean sea level) and steep slope of the surrounding mountain put the station above the regional marine boundary layer, enabling frequent sampling of free tropospheric air. Because of its unique location, air sampled at the station is rarely affected by local emissions or the ocean, and represents air masses transported over long distances to the site. The study used the Community Atmosphere Model CAM4, which is a part of the Community Earth System model version 1 (CESM1). HYSPLIT backward trajectories ran using the web-based portal READY was used to study airflow trajectory at PMO and showed that more than 50% of the air mass originated from North America. The model simulations were compared with observational data (from April - September) at PMO for the years 2009 through 2011. The fire data for the USA and Canada was compiled from the reports of National Interagency Coordination Center and Canadian Wildland Fire Information System, respectively. Time series analyses and orthogonal regression were used to compare model simulations with observations. The comparison shows simulations give a good representation of the observations, e.g., the mean concentration of CO in 2009 is 91.76 ppb and 95.05 ppb respectively from the simulation and the observations. Observed elevated pollutant concentrations also coincide with the maxima captured by the simulations. To assess the impact of North American outflow on pollution at PMO, scatter technique was used to calculate enhancement

Silver release from nanocomposite Ag/alginate hydrogels in the presence of chloride ions: experimental results and mathematical modeling

NASA Astrophysics Data System (ADS)

Kostic, Danijela; Vidovic, Srđan; Obradovic, Bojana

2016-03-01

A stepwise experimental and mathematical modeling approach was used to assess silver release from nanocomposite Ag/alginate microbeads in wet and dried forms into water and into normal saline solution chosen as a simplified model for certain biological fluids (e.g., blood plasma, wound exudates, sweat, etc). Three phenomena were connected and mathematically described: diffusion of silver nanoparticles (AgNPs) within the alginate hydrogel, AgNP oxidation/dissolution and reaction with chloride ions, and diffusion of the resultant silver-chloride species. Mathematical modeling results agreed well with the experimental data with the AgNP diffusion coefficient estimated as 1.3 × 10-18 m2 s-1, while the first-order kinetic rate constant of AgNP oxidation/dissolution and diffusivity of silver-chloride species were shown to be inversely related. In specific, rapid rehydration and swelling of dry Ag/alginate microbeads induced fast AgNP oxidation/dissolution reaction with Cl- and AgCl precipitation within the microbeads with the lowest diffusivity of silver-chloride species compared to wet microbeads in normal saline. The proposed mathematical model provided an insight into the phenomena related to silver release from nanocomposite Ca-alginate hydrogels relevant for use of antimicrobial devices and established, at the same time, a basis for further in-depth studies of AgNP interactions in hydrogels in the presence of chloride ions.

Modeling urban air pollution in Budapest using WRF-Chem model

NASA Astrophysics Data System (ADS)

Kovács, Attila; Leelőssy, Ádám; Lagzi, István; Mészáros, Róbert

2017-04-01

Air pollution is a major problem for urban areas since the industrial revolution, including Budapest, the capital and largest city of Hungary. The main anthropogenic sources of air pollutants are industry, traffic and residential heating. In this study, we investigated the contribution of major industrial point sources to the urban air pollution in Budapest. We used the WRF (Weather Research and Forecasting) nonhydrostatic mesoscale numerical weather prediction system online coupled with chemistry (WRF-Chem, version 3.6).The model was configured with three nested domains with grid spacings of 15, 5 and 1 km, representing Central Europe, the Carpathian Basin and Budapest with its surrounding area. Emission data was obtained from the National Environmental Information System. The point source emissions were summed in their respective cells in the second nested domain according to latitude-longitude coordinates. The main examined air pollutants were carbon monoxide (CO) and nitrogen oxides (NOx), from which the secondary compound, ozone (O3) forms through chemical reactions. Simulations were performed under different weather conditions and compared to observations from the automatic monitoring site of the Hungarian Air Quality Network. Our results show that the industrial emissions have a relatively weak role in the urban background air pollution, confirming the effect of industrial developments and regulations in the recent decades. However, a few significant industrial sources and their impact area has been demonstrated.

Polluter identification with spaceborne radar imagery, AIS and forward drift modeling.

PubMed

Longépé, N; Mouche, A A; Goacolou, M; Granier, N; Carrere, L; Lebras, J Y; Lozach, P; Besnard, S

2015-12-30

This study defines and assesses a new operational concept to identify the origin of pollution at sea, based on Synthetic Aperture Radar, Automatic Identification System, and a forward drift model. As opposed to traditional methodologies where the SAR detected pollution is backtracked in the past, our approach assumes that all the vessels pollute all along their way. Based on all the AIS data flows, the forward-tracked simulated pollutions are then compared to the detected pollution, and the potential polluter can be finally identified. Case studies are presented to showcase its usefulness in a variety of maritime situations with a focus on orphan pollutions in a dense traffic area. Out of the identification of the suspected polluters, the age and eventually the type of the pollution can be retrieved. Copyright © 2015 Elsevier Ltd. All rights reserved.

An improved risk-explicit interval linear programming model for pollution load allocation for watershed management.

PubMed

Xia, Bisheng; Qian, Xin; Yao, Hong

2017-11-01

Although the risk-explicit interval linear programming (REILP) model has solved the problem of having interval solutions, it has an equity problem, which can lead to unbalanced allocation between different decision variables. Therefore, an improved REILP model is proposed. This model adds an equity objective function and three constraint conditions to overcome this equity problem. In this case, pollution reduction is in proportion to pollutant load, which supports balanced development between different regional economies. The model is used to solve the problem of pollution load allocation in a small transboundary watershed. Compared with the REILP original model result, our model achieves equity between the upstream and downstream pollutant loads; it also overcomes the problem of greatest pollution reduction, where sources are nearest to the control section. The model provides a better solution to the problem of pollution load allocation than previous versions.

Modeling of air pollution from the power plant ash dumps

NASA Astrophysics Data System (ADS)

Aleksic, Nenad M.; Balać, Nedeljko

A simple model of air pollution from power plant ash dumps is presented, with emission rates calculated from the Bagnold formula and transport simulated by the ATDL type model. Moisture effects are accounted for by assumption that there is no pollution on rain days. Annual mean daily sedimentation rates, calculated for the area around the 'Nikola Tesla' power plants near Belgrade for 1987, show reasonably good agreement with observations.

Robust geographically weighted regression of modeling the Air Polluter Standard Index (APSI)

NASA Astrophysics Data System (ADS)

Warsito, Budi; Yasin, Hasbi; Ispriyanti, Dwi; Hoyyi, Abdul

2018-05-01

The Geographically Weighted Regression (GWR) model has been widely applied to many practical fields for exploring spatial heterogenity of a regression model. However, this method is inherently not robust to outliers. Outliers commonly exist in data sets and may lead to a distorted estimate of the underlying regression model. One of solution to handle the outliers in the regression model is to use the robust models. So this model was called Robust Geographically Weighted Regression (RGWR). This research aims to aid the government in the policy making process related to air pollution mitigation by developing a standard index model for air polluter (Air Polluter Standard Index - APSI) based on the RGWR approach. In this research, we also consider seven variables that are directly related to the air pollution level, which are the traffic velocity, the population density, the business center aspect, the air humidity, the wind velocity, the air temperature, and the area size of the urban forest. The best model is determined by the smallest AIC value. There are significance differences between Regression and RGWR in this case, but Basic GWR using the Gaussian kernel is the best model to modeling APSI because it has smallest AIC.

[Construction and application of economy-pollution-environment three-dimensional evaluation model for district].

PubMed

Fan, Xin-Gang; Mi, Wen-Bao; Ma, Zhen-Ning

2015-02-01

For deep analysis on the regional environmental economic system, the paper analyzes the mutual relation of regional economy development, environmental quality, environmental pollution, and builds the theoretical basis. Then, the economy-pollution-environment quality three-dimensional coupling evaluation model for district is constructed. It includes economic development level index, environmental pollution index, and environmental quality index. The model is a cube, which has spatialization and visualization characteristics. The model includes 8 sub cubes, which expresses 8 types of state, e. g. low pollution-inferior quality-low level of economic development etc. The model can be used to evaluate the status of region, divide development phase, analyze evolution trend etc. It has two ways including relative meaning evaluation (RME) and absolute meaning evaluation (AME). Based on the model, Yinchuan City in the Ningxia Hui Autonomous Region is used as an example for the empirical study. Using RME, compared with Guangzhou city, The result shows that the Yinchuan City has been a high pollution-low quality-low level of economic development state for a long period during 1996-2010. After 2007, the state changed to a high pollution-high quality-low level of economic development. Now, the environmental quality of Yinchuan city gets better, but pollutant discharge pressure is high, and tends to be the break point of high environment quality and low environment. With AME, using national standard, the Yinchuan City remains a high pollution-low quality-low level of economic development state during 1996-2010. Empirical research verifies that different target reference areas and relevant national standards have different main parameters, the evaluating result has an flexible range. The dimensionless data enhances the coupling of index. The data position in model increases the visibility to the environmental management decisions. The model improves mismatches of calculated data

Inverse modeling methods for indoor airborne pollutant tracking: literature review and fundamentals.

PubMed

Liu, X; Zhai, Z

2007-12-01

Reduction in indoor environment quality calls for effective control and improvement measures. Accurate and prompt identification of contaminant sources ensures that they can be quickly removed and contaminated spaces isolated and cleaned. This paper discusses the use of inverse modeling to identify potential indoor pollutant sources with limited pollutant sensor data. The study reviews various inverse modeling methods for advection-dispersion problems and summarizes the methods into three major categories: forward, backward, and probability inverse modeling methods. The adjoint probability inverse modeling method is indicated as an appropriate model for indoor air pollutant tracking because it can quickly find source location, strength and release time without prior information. The paper introduces the principles of the adjoint probability method and establishes the corresponding adjoint equations for both multi-zone airflow models and computational fluid dynamics (CFD) models. The study proposes a two-stage inverse modeling approach integrating both multi-zone and CFD models, which can provide a rapid estimate of indoor pollution status and history for a whole building. Preliminary case study results indicate that the adjoint probability method is feasible for indoor pollutant inverse modeling. The proposed method can help identify contaminant source characteristics (location and release time) with limited sensor outputs. This will ensure an effective and prompt execution of building management strategies and thus achieve a healthy and safe indoor environment. The method can also help design optimal sensor networks.

Modeling urban air pollution with optimized hierarchical fuzzy inference system.

PubMed

Tashayo, Behnam; Alimohammadi, Abbas

2016-10-01

Environmental exposure assessments (EEA) and epidemiological studies require urban air pollution models with appropriate spatial and temporal resolutions. Uncertain available data and inflexible models can limit air pollution modeling techniques, particularly in under developing countries. This paper develops a hierarchical fuzzy inference system (HFIS) to model air pollution under different land use, transportation, and meteorological conditions. To improve performance, the system treats the issue as a large-scale and high-dimensional problem and develops the proposed model using a three-step approach. In the first step, a geospatial information system (GIS) and probabilistic methods are used to preprocess the data. In the second step, a hierarchical structure is generated based on the problem. In the third step, the accuracy and complexity of the model are simultaneously optimized with a multiple objective particle swarm optimization (MOPSO) algorithm. We examine the capabilities of the proposed model for predicting daily and annual mean PM2.5 and NO2 and compare the accuracy of the results with representative models from existing literature. The benefits provided by the model features, including probabilistic preprocessing, multi-objective optimization, and hierarchical structure, are precisely evaluated by comparing five different consecutive models in terms of accuracy and complexity criteria. Fivefold cross validation is used to assess the performance of the generated models. The respective average RMSEs and coefficients of determination (R (2)) for the test datasets using proposed model are as follows: daily PM2.5 = (8.13, 0.78), annual mean PM2.5 = (4.96, 0.80), daily NO2 = (5.63, 0.79), and annual mean NO2 = (2.89, 0.83). The obtained results demonstrate that the developed hierarchical fuzzy inference system can be utilized for modeling air pollution in EEA and epidemiological studies.

InMAP: a new model for air pollution interventions

NASA Astrophysics Data System (ADS)

Tessum, C. W.; Hill, J. D.; Marshall, J. D.

2015-10-01

Mechanistic air pollution models are essential tools in air quality management. Widespread use of such models is hindered, however, by the extensive expertise or computational resources needed to run most models. Here, we present InMAP (Intervention Model for Air Pollution), which offers an alternative to comprehensive air quality models for estimating the air pollution health impacts of emission reductions and other potential interventions. InMAP estimates annual-average changes in primary and secondary fine particle (PM2.5) concentrations - the air pollution outcome generally causing the largest monetized health damages - attributable to annual changes in precursor emissions. InMAP leverages pre-processed physical and chemical information from the output of a state-of-the-science chemical transport model (WRF-Chem) within an Eulerian modeling framework, to perform simulations that are several orders of magnitude less computationally intensive than comprehensive model simulations. InMAP uses a variable resolution grid that focuses on human exposures by employing higher spatial resolution in urban areas and lower spatial resolution in rural and remote locations and in the upper atmosphere; and by directly calculating steady-state, annual average concentrations. In comparisons run here, InMAP recreates WRF-Chem predictions of changes in total PM2.5 concentrations with population-weighted mean fractional error (MFE) and bias (MFB) < 10 % and population-weighted R2 ~ 0.99. Among individual PM2.5 species, the best predictive performance is for primary PM2.5 (MFE: 16 %; MFB: 13 %) and the worst predictive performance is for particulate nitrate (MFE: 119 %; MFB: 106 %). Potential uses of InMAP include studying exposure, health, and environmental justice impacts of potential shifts in emissions for annual-average PM2.5. Features planned for future model releases include a larger spatial domain, more temporal information, and the ability to predict ground-level ozone (O3

Influence of natural organic matter on fate and transport of silver nanoparticles in saturated porous media: laboratory experiments and modeling

NASA Astrophysics Data System (ADS)

Kanel, Sushil R.; Flory, Jason; Meyerhoefer, Allie; Fraley, Jessica L.; Sizemore, Ioana E.; Goltz, Mark N.

2015-03-01

Understanding the fate and transport of silver nanoparticles (AgNPs) is of importance due to their widespread use and potential harmful effects on humans and the environment. The present study investigates the fate and transport of widely used Creighton AgNPs in saturated porous media. Previous investigations of AgNP transport in the presence of natural organic matter (NOM) report contradictory results regarding how the presence of NOM affected the stability and mobility of AgNPs. In this work, a nonreactive tracer, AgNPs and a mixture of AgNPs and NOM were injected into a background solution (0.01 mM of NaNO3) flowing through laboratory columns packed with water-saturated glass beads to obtain concentration versus time breakthrough curves. Transport of AgNPs in the presence of NOM was simulated with a model that accounted for both reversible and irreversible attachment. Based upon an analysis of the AgNP breakthrough curves, it was found that addition of NOM at concentrations ranging from 1 to 40 mg L-1 resulted in significant decreases in both the zeroth and first moments of the breakthrough curves. These observations may be attributed to NOM promoting AgNP aggregation and irreversible attachment. Raman and surface-enhanced Raman scattering analysis of NOM-AgNP mixtures revealed that a possible interaction of NOM with AgNP occurred through the carboxylic moieties (-COO-) located in the immediate vicinity of the metallic surface. At higher concentrations of NOM, both the zeroth and first moments of the breakthrough curves increased. Based on modeling and the literature, we hypothesize that as the NOM concentration increases, it begins to coat both the AgNPs and the glass beads, leading to a situation where AgNP transport may be described in the same way that transport of a sorbing hydrophobic compound partitioning to an immobile organic phase is typically described, assuming reversible, rate-limited sorption.

Risk forewarning model for rice grain Cd pollution based on Bayes theory.

PubMed

Wu, Bo; Guo, Shuhai; Zhang, Lingyan; Li, Fengmei

2018-03-15

Cadmium (Cd) pollution of rice grain caused by Cd-contaminated soils is a common problem in southwest and central south China. In this study, utilizing the advantages of the Bayes classification statistical method, we established a risk forewarning model for rice grain Cd pollution, and put forward two parameters (the prior probability factor and data variability factor). The sensitivity analysis of the model parameters illustrated that sample size and standard deviation influenced the accuracy and applicable range of the model. The accuracy of the model was improved by the self-renewal of the model through adding the posterior data into the priori data. Furthermore, this method can be used to predict the risk probability of rice grain Cd pollution under similar soil environment, tillage and rice varietal conditions. The Bayes approach thus represents a feasible method for risk forewarning of heavy metals pollution of agricultural products caused by contaminated soils. Copyright © 2017 Elsevier B.V. All rights reserved.

Experimental and Modeling Study on Detachment of Silver Nanoparticles in Saturated Granular Media

NASA Astrophysics Data System (ADS)

Kim, I.; Jeon, C. H.; Lawler, D. F.

2017-12-01

The detachment of citrate-capped silver nanoparticles (AgNPs) previously captured in a column packed with 350-μm glass beads was investigated either by increasing the hydrodynamic force (filtration velocity) or by reducing electrosteric attraction. Overall, the physical enforcement showed negligible (0.4 0.7%) release of attached AgNPs while the chemically-driven force resulted in the noticeable release up to 25.5% of attached AgNPs. Among the chemical parameters tested in this study, Na ionic strength reduction clearly demonstrated the reversible deposition in the secondary energy minimum of classical DLVO theory, yielding the most significant release of the attached AgNPs. The immediate and transient AgNP release after the ionic strength reduction further corroborated the weak deposition. However, an insignificant release was observed with Ca ionic strength reduction due to the strong Ca-citrate complexation and the subsequent deposition in the primary energy minimum; calculations indicated that the depth of the secondary energy minimum was only 1/10 that of the Na ion case. The natural organic matter (NOM) coating on both AgNPs and granular media resulted in approximately 6.1% greater AgNP release compared to the case without NOM coating, indicating additional weak deposition due to the reduced steric attraction between AgNPs and granular media. A modified filtration model in agreement with the experimental data provided the estimated detachment coefficient as a transient AgNP releasing capacity independent of the amount of attached AgNPs. The marginal difference between the detachment coefficients from Na ionic strength reduction and NOM coating indicates the release potential by NOM coating was possibly underestimated in the experimental study due to a lesser amount of the initially attached AgNPs. The findings provide insights into chemical factors on possible reentrainment behavior of the engineered nanoparticles in soil and groundwater contamination.

SCIMAP: Modelling Diffuse Pollution in Large River Basins

NASA Astrophysics Data System (ADS)

Milledge, D.; Heathwaite, L.; Lane, S. N.; Reaney, S. M.

2009-12-01

Polluted rivers are a problem for the plants and animals that require clean water to survive. Watershed scale processes can influence instream aquatic ecosystems by delivering fine sediment, solutes and organic matter from diffuse sources. To improve our rivers we need to identify the pollution sources. Models can help us to do this but these rarely address the extent to which risky land uses are hydrologically-connected, and hence able to deliver, to the drainage network. Those that do tend to apply a full hydrological scheme, which is unfeasible for large watersheds. Here we develop a risk-based modelling framework, SCIMAP, for diffuse pollution from agriculture (Nitrate, Phosphate and Fine Sediment). In each case the basis of the analysis is the joint consideration of the probability of a unit of land (25 m2 cell) producing a particular environmental risk and then of that risk reaching the river. The components share a common treatment of hydrological connectivity but differ in their treatment of each pollution type. We test and apply SCIMAP using spatially-distributed instream water quality data for some of the UK’s largest catchments to infer the processes and the associated process parameters that matter in defining their concentrations. We use these to identify a series of risky field locations, where this land use is readily connected to the river system by overland flow.

Development of Laboratory Model Ecosystems as Early Warning Elements of Environmental Pollution

DTIC Science & Technology

1974-12-01

AD-AOll 851 DEVELOPMENT OF LABORATORY MODEL ECOSYSTEMS AS EARLY WARNING ELEMENTS OF ENVIRONMENTAL POLLUTION Robert L. Metcalf... ENVIRONMENTAL POLLUTION Robert L. Metcalf, Ph. D. University of Illinois Urbana-Champaign, Illinois INTRODUCTION Problems of environmental pollution with...house dust is unsafe to breathe (Ewing and Pearson, 1974). Most of the source of our concern about environmental pollution by trace substances relates

Parametric laws to model urban pollutant dispersion with a street network approach

NASA Astrophysics Data System (ADS)

Soulhac, L.; Salizzoni, P.; Mejean, P.; Perkins, R. J.

2013-03-01

This study discusses the reliability of the street network approach for pollutant dispersion modelling in urban areas. This is essentially based on a box model, with parametric relations that explicitly model the main phenomena that contribute to the street canyon ventilation: the mass exchanges between the street and the atmosphere, the pollutant advection along the street axes and the pollutant transfer at street intersections. In the first part of the paper the focus is on the development of a model for the bulk transfer street/atmosphere, which represents the main ventilation mechanisms for wind direction that are almost perpendicular to the axis of the street. We then discuss the role of the advective transfer along the street axis on its ventilation, depending on the length of the street and the direction of the external wind. Finally we evaluate the performances of a box model integrating parametric exchange laws for these transfer phenomena. To that purpose we compare the prediction of the model to wind tunnel experiments of pollutant dispersion within a street canyon placed in an idealised urban district.

A review of air exchange rate models for air pollution exposure assessments.

PubMed

Breen, Michael S; Schultz, Bradley D; Sohn, Michael D; Long, Thomas; Langstaff, John; Williams, Ronald; Isaacs, Kristin; Meng, Qing Yu; Stallings, Casson; Smith, Luther

2014-11-01

A critical aspect of air pollution exposure assessments is estimation of the air exchange rate (AER) for various buildings where people spend their time. The AER, which is the rate of exchange of indoor air with outdoor air, is an important determinant for entry of outdoor air pollutants and for removal of indoor-emitted air pollutants. This paper presents an overview and critical analysis of the scientific literature on empirical and physically based AER models for residential and commercial buildings; the models highlighted here are feasible for exposure assessments as extensive inputs are not required. Models are included for the three types of airflows that can occur across building envelopes: leakage, natural ventilation, and mechanical ventilation. Guidance is provided to select the preferable AER model based on available data, desired temporal resolution, types of airflows, and types of buildings included in the exposure assessment. For exposure assessments with some limited building leakage or AER measurements, strategies are described to reduce AER model uncertainty. This review will facilitate the selection of AER models in support of air pollution exposure assessments.

Application of the kinetic and isotherm models for better understanding of the behaviors of silver nanoparticles adsorption onto different adsorbents.

PubMed

Syafiuddin, Achmad; Salmiati, Salmiati; Jonbi, Jonbi; Fulazzaky, Mohamad Ali

2018-07-15

It is the first time to do investigation the reliability and validity of thirty kinetic and isotherm models for describing the behaviors of adsorption of silver nanoparticles (AgNPs) onto different adsorbents. The purpose of this study is therefore to assess the most reliable models for the adsorption of AgNPs onto feasibility of an adsorbent. The fifteen kinetic models and fifteen isotherm models were used to test secondary data of AgNPs adsorption collected from the various data sources. The rankings of arithmetic mean were estimated based on the six statistical analysis methods of using a dedicated software of the MATLAB Optimization Toolbox with a least square curve fitting function. The use of fractal-like mixed 1, 2-order model for describing the adsorption kinetics and that of Fritz-Schlunder and Baudu models for describing the adsorption isotherms can be recommended as the most reliable models for AgNPs adsorption onto the natural and synthetic adsorbent materials. The application of thirty models have been identified for the adsorption of AgNPs to clarify the usefulness of both groups of the kinetic and isotherm equations in the rank order of the levels of accuracy, and this significantly contributes to understandability and usability of the proper models and makes to knowledge beyond the existing literatures. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Flexible Spatio-Temporal Model for Air Pollution with Spatial and Spatio-Temporal Covariates.

PubMed

Lindström, Johan; Szpiro, Adam A; Sampson, Paul D; Oron, Assaf P; Richards, Mark; Larson, Tim V; Sheppard, Lianne

2014-09-01

The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system (GIS) covariates. The model presented in this paper has been implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of NO x in the Los Angeles area during a ten year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated R 2 of approximately 0.7 at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy.

Air Pollution Exposure Modeling for Health Studies

EPA Science Inventory

Dr. Michael Breen is leading the development of air pollution exposure models, integrated with novel personal sensor technologies, to improve exposure and risk assessments for individuals in health studies. He is co-investigator for multiple health studies assessing the exposure ...

Biosynthesis of AgNPs using Carica Papaya peel extract and evaluation of its antioxidant and antimicrobial activities.

PubMed

Kokila, T; Ramesh, P S; Geetha, D

2016-12-01

Waste fruit peel mediated synthesis of silver nanoparticles (AgNPs) is a green chemistry approach that links nanotechnology and biotechnology. Using biological medium such as peel extract for the biosynthesis of nanoparticles is an ecofriendly and emerging scientific trend. With this back drop the present study focused on the biosynthesis of AgNPs using Carica Papaya peel extract (CPPE) and evaluation of its antimicrobial potentials of the nanoparticles against different human pathogens and to investigate the free radical scavenging activity. Water soluble antioxidant constituents present in Carica Papaya peel extract were mainly responsible for the reduction of silver ions to nanosized Ag particles. UV-vis spectral analysis shows surface plasmon resonance band at 430nm. The presence of active proteins and phenolic groups present in the biomass before and after reduction was identified by Fourier transform infrared spectroscopy. X-ray diffraction study shows the average size of the silver nanoparticles is in the range of 28nm, as well as revealed their face centered cubic structure. Atomic force microscope image gives the 3D topological characteristic of silver nanoparticles and the particle size ranges from 10 to 30nm. The average particle size distribution of silver nanoparticles is 161nm (Dynamic light scattering) and the corresponding average zeta potential value is -20.5mV, suggesting higher stability of silver nanoparticles. Biologically synthesized nanoparticles efficiently inhibited pathogenic organisms both gram-positive and gram-negative bacteria. The biosynthesized nanoparticles might serve as a potent antioxidant as revealed by DPPH and ABT S+ assay. Copyright © 2016 Elsevier Inc. All rights reserved.

Estimating near-road pollutant dispersion: a model inter-comparison

EPA Science Inventory

A model inter-comparison study to assess the abilities of steady-state Gaussian dispersion models to capture near-road pollutant dispersion has been carried out with four models (AERMOD, run with both the area-source and volume-source options to represent roadways, CALINE, versio...

E-beam deposited Ag-nanoparticles plasmonic organic solar cell and its absorption enhancement analysis using FDTD-based cylindrical nano-particle optical model.

PubMed

Kim, Richard S; Zhu, Jinfeng; Park, Jeung Hun; Li, Lu; Yu, Zhibin; Shen, Huajun; Xue, Mei; Wang, Kang L; Park, Gyechoon; Anderson, Timothy J; Pei, Qibing

2012-06-04

We report the plasmon-assisted photocurrent enhancement in Ag-nanoparticles (Ag-NPs) embedded PEDOT:PSS/P3HT:PCBM organic solar cells, and systematically investigate the causes of the improved optical absorption based on a cylindrical Ag-NPs optical model which is simulated with a 3-Dimensional finite difference time domain (FDTD) method. The proposed cylindrical Ag-NPs optical model is able to explain the optical absorption enhancement by the localized surface plasmon resonance (LSPR) modes, and to provide a further understanding of Ag-NPs shape parameters which play an important role to determine the broadband absorption phenomena in plasmonic organic solar cells. A significant increase in the power conversion efficiency (PCE) of the plasmonic solar cell was experimentally observed and compared with that of the solar cells without Ag-NPs. Finally, our conclusion was made after briefly discussing the electrical effects of the fabricated plasmonic organic solar cells.

How robust are the estimated effects of air pollution on health? Accounting for model uncertainty using Bayesian model averaging.

PubMed

Pannullo, Francesca; Lee, Duncan; Waclawski, Eugene; Leyland, Alastair H

2016-08-01

The long-term impact of air pollution on human health can be estimated from small-area ecological studies in which the health outcome is regressed against air pollution concentrations and other covariates, such as socio-economic deprivation. Socio-economic deprivation is multi-factorial and difficult to measure, and includes aspects of income, education, and housing as well as others. However, these variables are potentially highly correlated, meaning one can either create an overall deprivation index, or use the individual characteristics, which can result in a variety of pollution-health effects. Other aspects of model choice may affect the pollution-health estimate, such as the estimation of pollution, and spatial autocorrelation model. Therefore, we propose a Bayesian model averaging approach to combine the results from multiple statistical models to produce a more robust representation of the overall pollution-health effect. We investigate the relationship between nitrogen dioxide concentrations and cardio-respiratory mortality in West Central Scotland between 2006 and 2012. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

SIRANERISK: Modelling dispersion of steady and unsteady pollutant releases in the urban canopy

NASA Astrophysics Data System (ADS)

Soulhac, L.; Lamaison, G.; Cierco, F.-X.; Ben Salem, N.; Salizzoni, P.; Mejean, P.; Armand, P.; Patryl, L.

2016-09-01

SIRANERISK is an operational model for the simulation of the dispersion of unsteady atmospheric releases of pollutant within and above an urban area. SIRANERISK is built on the same principles as the SIRANE model, and couples a street network model for the pollutant transfers within the urban canopy with a Gaussian puff model for the transfers above it. The performance of the model are here analysed by a detailed comparisons with wind-tunnel experiments. These experiments concern the dispersion of steady and unsteady pollutant releases within and above obstacle arrays with varying geometrical configurations, representing different topologies of idealised urban districts. The overall good agreement between numerical and experimental data demonstrates the reliability of SIRANERISK as an operational tool for the assessment of risk analysis and for the management of crises due to the accidental release of harmful airborne pollutants within a built environment.

POLUTE; forest air pollutant uptake model. [IBM360,370; CSMP

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murphy, C.E.

POLUTE is a computer model designed to estimate the uptake of air pollutants by forests. The model utilizes submodels to describe atmospheric diffusion immediately above and within the canopy, and into the sink areas within or on the trees. The program implementing the model is general and can be used, with only minor changes, for any gaseous pollutant. The model provides an estimate describing the response of the vegetarian-atmosphere system to the environment as related to three types of processes: atmospheric diffusion, diffusion near and inside the absorbing plant, and the physical and chemical processes at the sink on ormore » within the plant.IBM360,370; CSMP; OS/370.« less

A Multivariate Dynamic Spatial Factor Model for Speciated Pollutants and Adverse Birth Outcomes

DOE PAGES

Kaufeld, Kimberly Ann; Fuentes, Montse; Reich, Brian J.; ...

2017-09-11

Evidence suggests that exposure to elevated concentrations of air pollution during pregnancy is associated with increased risks of birth defects and other adverse birth outcomes. While current regulations put limits on total PM2.5 concentrations, there are many speciated pollutants within this size class that likely have distinct effects on perinatal health. However, due to correlations between these speciated pollutants, it can be difficult to decipher their effects in a model for birth outcomes. To combat this difficulty, we develop a multivariate spatio-temporal Bayesian model for speciated particulate matter using dynamic spatial factors. These spatial factors can then be interpolated tomore » the pregnant women’s homes to be used to model birth defects. The birth defect model allows the impact of pollutants to vary across different weeks of the pregnancy in order to identify susceptible periods. Here, the proposed methodology is illustrated using pollutant monitoring data from the Environmental Protection Agency and birth records from the National Birth Defect Prevention Study.« less

A Multivariate Dynamic Spatial Factor Model for Speciated Pollutants and Adverse Birth Outcomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaufeld, Kimberly Ann; Fuentes, Montse; Reich, Brian J.

Evidence suggests that exposure to elevated concentrations of air pollution during pregnancy is associated with increased risks of birth defects and other adverse birth outcomes. While current regulations put limits on total PM2.5 concentrations, there are many speciated pollutants within this size class that likely have distinct effects on perinatal health. However, due to correlations between these speciated pollutants, it can be difficult to decipher their effects in a model for birth outcomes. To combat this difficulty, we develop a multivariate spatio-temporal Bayesian model for speciated particulate matter using dynamic spatial factors. These spatial factors can then be interpolated tomore » the pregnant women’s homes to be used to model birth defects. The birth defect model allows the impact of pollutants to vary across different weeks of the pregnancy in order to identify susceptible periods. Here, the proposed methodology is illustrated using pollutant monitoring data from the Environmental Protection Agency and birth records from the National Birth Defect Prevention Study.« less

Measuring the impact of pollution on property prices in Madrid: objective versus subjective pollution indicators in spatial models

NASA Astrophysics Data System (ADS)

Mínguez, Román; Montero, José-María; Fernández-Avilés, Gema

2013-04-01

Much work has been done in the context of the hedonic price theory to estimate the impact of air quality on housing prices. Research has employed objective measures of air quality, but only slightly confirms the hedonic theory in the best of cases: the implicit price function relating housing prices to air pollution will, ceteris paribus, be negatively sloped. This paper compares the performance of a spatial Durbin model when using both objective and subjective measures of pollution. On the one hand, we design an Air Pollution Indicator based on measured pollution as the objective measure of pollution. On the other hand, the subjective measure of pollution employed to characterize neighborhoods is the percentage of residents who declare that the neighborhood has serious pollution problems, the percentage being referred to as residents' perception of pollution. For comparison purposes, the empirical part of this research focuses on Madrid (Spain). The study employs a proprietary database containing information about the price and 27 characteristics of 11,796 owner-occupied single family homes. As far as the authors are aware, it is the largest database ever used to analyze the Madrid housing market. The results of the study clearly favor the use of subjective air quality measures.

Impact of silver nanoparticles on benthic prokaryotes in heavy metal-contaminated estuarine sediments in a tropical environment.

PubMed

Antizar-Ladislao, B; Bhattacharya, B D; Ray Chaudhuri, S; Sarkar, S K

2015-10-15

Little knowledge is available about the potential impact of commercial silver nanoparticles (Ag-NPs) on estuarine microbial communities. The Hugli river estuary, India, is susceptible to heavy metals pollution through boat traffic, and there is the potential for Ag-NP exposure via effluent discharged from ongoing municipal and industrial activities located in close proximity. This study investigated the effects of commercial Ag-NPs on native microbial communities in estuarine sediments collected from five stations, using terminal restriction fragment length polymorphism (T-RFLP) technique. An increase in the number of bacteria in consortium in sediments was observed following exposure to Ag-NPs. In general microbial communities may be resistant in estuarine systems to the antimicrobial effects of commercial Ag-NPs, but key microorganisms, such as Pelobacter propionicus, disappeared following exposure to Ag-NPs. In conclusion, the T-RFLP analysis indicated that Ag-NPs have the potential to shape estuarine sediment bacterial community structure. Copyright © 2015 Elsevier Ltd. All rights reserved.

Urban nonpoint source pollution buildup and washoff models for simulating storm runoff quality in the Los Angeles County.

PubMed

Wang, Long; Wei, Jiahua; Huang, Yuefei; Wang, Guangqian; Maqsood, Imran

2011-07-01

Many urban nonpoint source pollution models utilize pollutant buildup and washoff functions to simulate storm runoff quality of urban catchments. In this paper, two urban pollutant washoff load models are derived using pollutant buildup and washoff functions. The first model assumes that there is no residual pollutant after a storm event while the second one assumes that there is always residual pollutant after each storm event. The developed models are calibrated and verified with observed data from an urban catchment in the Los Angeles County. The application results show that the developed model with consideration of residual pollutant is more capable of simulating nonpoint source pollution from urban storm runoff than that without consideration of residual pollutant. For the study area, residual pollutant should be considered in pollutant buildup and washoff functions for simulating urban nonpoint source pollution when the total runoff volume is less than 30 mm. Copyright © 2011 Elsevier Ltd. All rights reserved.

Development of a distributed air pollutant dry deposition modeling framework

Treesearch

Satoshi Hirabayashi; Charles N. Kroll; David J. Nowak

2012-01-01

A distributed air pollutant dry deposition modeling systemwas developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry...

Laminarin based AgNPs using brown seaweed Turbinaria ornata and its induction of apoptosis in human retinoblastoma Y79 cancer cell lines

NASA Astrophysics Data System (ADS)

Remya, R. R.; Radhika Rajasree, S. R.; Suman, T. Y.; Aranganathan, L.; Gayathri, S.; Gobalakrishnan, M.; Karthih, M. G.

2018-03-01

Biosynthesis of nanoparticles using isolated compounds from various sources is accepting interest due to their broad array of biological activities and biocompatibility. This paper presents a simple; cost effective and green synthesis of silver nanoparticles (AgNPs) using the polysaccharide, laminarin a storage compound obtained from the brown algae Turbinaria ornata (T. ornata). Initially, the water soluble polysaccharide, laminarin was extracted, purified and analyzed using Matrix Assisted Laser Desorption Ionization Time-of-Flight Mass Spectroscopy (MALDI-TOF MS) and Proton Nuclear Magnetic Resonance (1H NMR). Further, the silver nanoparticles (AgNPs) were synthesized using the isolated laminarin and were characterized by Ultraviolet - visible (UV-vis) spectrophotometer, colour value analysis, Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD) and High Resolution Transmission Electron Microscopy (HR-TEM). The free radical scavenging activities were performed and the effect of cytotoxicity against retinoblastoma Y79 cell lines was also evaluated by in vitro studies. Induction of apoptosis was evident by the percentage of cells arrested in G2/M phase using flow cytometry analysis and was further confirmed by DNA fragmentation study which identified the presence of double strand break.

Structural equation modeling of the inflammatory response to traffic air pollution

PubMed Central

Baja, Emmanuel S.; Schwartz, Joel D.; Coull, Brent A.; Wellenius, Gregory A.; Vokonas, Pantel S.; Suh, Helen H.

2015-01-01

Several epidemiological studies have reported conflicting results on the effect of traffic-related pollutants on markers of inflammation. In a Bayesian framework, we examined the effect of traffic pollution on inflammation using structural equation models (SEMs). We studied measurements of C-reactive protein (CRP), soluble vascular cell adhesion molecule-1 (sVCAM-1), and soluble intracellular adhesion molecule-1 (sICAM-1) for 749 elderly men from the Normative Aging Study. Using repeated measures SEMs, we fit a latent variable for traffic pollution that is reflected by levels of black carbon, carbon monoxide, nitrogen monoxide and nitrogen dioxide to estimate its effect on a latent variable for inflammation that included sICAM-1, sVCAM-1 and CRP. Exposure periods were assessed using 1-, 2-, 3-, 7-, 14- and 30-day moving averages previsit. We compared our findings using SEMs with those obtained using linear mixed models. Traffic pollution was related to increased inflammation for 3-, 7-, 14- and 30-day exposure periods. An inter-quartile range increase in traffic pollution was associated with a 2.3% (95% posterior interval (PI): 0.0–4.7%) increase in inflammation for the 3-day moving average, with the most significant association observed for the 30-day moving average (23.9%; 95% PI: 13.9–36.7%). Traffic pollution adversely impacts inflammation in the elderly. SEMs in a Bayesian framework can comprehensively incorporate multiple pollutants and health outcomes simultaneously in air pollution–cardiovascular epidemiological studies. PMID:23232970

Modeling the Transport and Fate of Fecal Pollution and Nutrients of Miyun Reservoir

NASA Astrophysics Data System (ADS)

Liu, L.; Fu, X.; Wang, G.

2009-12-01

Miyun Reservoir, a mountain valley reservoir, is located 100 km northeast of Beijing City. Besides the functions of flood control, irrigation and fishery for Beijing area, Miyun Reservoir is the main drinking water storage for Beijing city. The water quality is therefore of great importance. Recently, the concentration of fecal pollution and nutrients in the reservoir are constantly rising to arrest the attention of Beijing municipality. Fecal pollution from sewage is a significant public health concern due to the known presence of human viruses and parasites in these discharges. To investigate the transport and fate of the fecal pollution and nutrients at Miyun reservoir and the health risks associated with drinking and fishery, the reservoir and two tributaries, Chaohe river and Baihe river discharging into it are being examined for bacterial, nutrients and other routine pollution. To understand the relative importance of different processes influencing pollution transport and inactivation, a finite-element model of surf-zone hydrodynamics (coupled with models for temperature, fecal pollution, nutrients and other routine contaminants) is used. The developed models are being verified by the observed water quality data including water temperature, conductivities and dissolved oxygen from the reservoir and its tributaries. Different factors impacting the inactivation of fecal pollution and the transport of nutrients such as water temperature, sedimentation, sunlight insolation are evaluated for Miyun reservoir by a sensitivity analysis analogized from the previous research of Lake Michigan (figure 1, indicating that solar insolation dominates the inactivation of E. Coli, an indicator of fecal pollution, Liu et al. 2006). The calibrated modeling system can be used to temporally and spatially simulate and predict the variation of the concentration of fecal pollution and nutrients of Miyun reservoir. Therefore this research can provide a forecasting tool for the

High-Resolution Modelling of Health Impacts from Air Pollution for Denmark using the Integrated Model System EVA

NASA Astrophysics Data System (ADS)

Brandt, Jørgen; Andersen, Mikael S.; Bønløkke, Jakob; Christensen, Jesper H.; Hansen, Kaj M.; Hertel, Ole; Im, Ulas; Jensen, Steen S.; Ketzel, Matthias; Nielsen, Ole-Kenneth; Plejdrup, Marlene S.; Sigsgaard, Torben; Geels, Camilla

2015-04-01

We have developed an integrated health impact assessment system EVA (Economic Valuation of Air pollution; Brandt et al., 2013a; 2013b), based on the impact-pathway chain, to assess the health impacts and health-related economic externalities of air pollution resulting from specific emission sources or sectors. The system is used to support policymaking with respect to emission control. The EVA system has previously been used to assess the health impacts based on results from a regional model DEHM (the Danish Eulerian Hemispheric Model; Brandt et al., 2012). In this study we have used a coupling of two chemistry transport models to calculate the air pollution concentration at different scales; the DEHM model to calculate the air pollution levels with a resolution down to 5.6 km x 5.6 km and the UBM model (Urban Background Model ; Berkowicz, 2000; Brandt et al., 2001) to further calculate the air pollution at 1 km x 1 km resolution for Denmark using results from DEHM as boundary conditions. Both the emission data based on the SPREAD model (Plejdrup and Gyldenkærne, 2011) as well as the population density has been represented in the model system with the same high resolution. The new developments of the integrated model system will be presented as well as results for health impacts and related external costs over the years 2006-2014 for Denmark. Furthermore, a sensitivity study of the health impact using coarse and fine resolutions in the model system has been carried out to evaluate the effect of improved description of the geographical population distribution with respect to location of local emissions. References Berkowicz, R., 2000. A Simple Model for Urban Background Pollution. Environmental Monitoring and Assessment, 65, 1/2, 259-267. Brandt, J., J. H. Christensen, L. M. Frohn, F. Palmgren, R. Berkowicz and Z. Zlatev, 2001: "Operational air pollution forecasts from European to local scale". Atmospheric Environment, Vol. 35, Sup. No. 1, pp. S91-S98, 2001 Brandt

A Unified Spatiotemporal Modeling Approach for Predicting Concentrations of Multiple Air Pollutants in the Multi-Ethnic Study of Atherosclerosis and Air Pollution

PubMed Central

Olives, Casey; Kim, Sun-Young; Sheppard, Lianne; Sampson, Paul D.; Szpiro, Adam A.; Oron, Assaf P.; Lindström, Johan; Vedal, Sverre; Kaufman, Joel D.

2014-01-01

Background: Cohort studies of the relationship between air pollution exposure and chronic health effects require predictions of exposure over long periods of time. Objectives: We developed a unified modeling approach for predicting fine particulate matter, nitrogen dioxide, oxides of nitrogen, and black carbon (as measured by light absorption coefficient) in six U.S. metropolitan regions from 1999 through early 2012 as part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Methods: We obtained monitoring data from regulatory networks and supplemented those data with study-specific measurements collected from MESA Air community locations and participants’ homes. In each region, we applied a spatiotemporal model that included a long-term spatial mean, time trends with spatially varying coefficients, and a spatiotemporal residual. The mean structure was derived from a large set of geographic covariates that was reduced using partial least-squares regression. We estimated time trends from observed time series and used spatial smoothing methods to borrow strength between observations. Results: Prediction accuracy was high for most models, with cross-validation R2 (R2CV) > 0.80 at regulatory and fixed sites for most regions and pollutants. At home sites, overall R2CV ranged from 0.45 to 0.92, and temporally adjusted R2CV ranged from 0.23 to 0.92. Conclusions: This novel spatiotemporal modeling approach provides accurate fine-scale predictions in multiple regions for four pollutants. We have generated participant-specific predictions for MESA Air to investigate health effects of long-term air pollution exposures. These successes highlight modeling advances that can be adopted more widely in modern cohort studies. Citation: Keller JP, Olives C, Kim SY, Sheppard L, Sampson PD, Szpiro AA, Oron AP, Lindström J, Vedal S, Kaufman JD. 2015. A unified spatiotemporal modeling approach for predicting concentrations of multiple air pollutants in the Multi

Geoinformation modeling system for analysis of atmosphere pollution impact on vegetable biosystems using space images

NASA Astrophysics Data System (ADS)

Polichtchouk, Yuri; Ryukhko, Viatcheslav; Tokareva, Olga; Alexeeva, Mary

2002-02-01

Geoinformation modeling system structure for assessment of the environmental impact of atmospheric pollution on forest- swamp ecosystems of West Siberia is considered. Complex approach to the assessment of man-caused impact based on the combination of sanitary-hygienic and landscape-geochemical approaches is reported. Methodical problems of analysis of atmosphere pollution impact on vegetable biosystems using geoinformation systems and remote sensing data are developed. Landscape structure of oil production territories in southern part of West Siberia are determined on base of processing of space images from spaceborn Resource-O. Particularities of atmosphere pollution zones modeling caused by gas burning in torches in territories of oil fields are considered. For instance, a pollution zones were revealed modeling of contaminants dispersal in atmosphere by standard model. Polluted landscapes areas are calculated depending on oil production volume. It is shown calculated data is well approximated by polynomial models.

A linked simulation-optimization model for solving the unknown groundwater pollution source identification problems.

PubMed

Ayvaz, M Tamer

2010-09-20

This study proposes a linked simulation-optimization model for solving the unknown groundwater pollution source identification problems. In the proposed model, MODFLOW and MT3DMS packages are used to simulate the flow and transport processes in the groundwater system. These models are then integrated with an optimization model which is based on the heuristic harmony search (HS) algorithm. In the proposed simulation-optimization model, the locations and release histories of the pollution sources are treated as the explicit decision variables and determined through the optimization model. Also, an implicit solution procedure is proposed to determine the optimum number of pollution sources which is an advantage of this model. The performance of the proposed model is evaluated on two hypothetical examples for simple and complex aquifer geometries, measurement error conditions, and different HS solution parameter sets. Identified results indicated that the proposed simulation-optimization model is an effective way and may be used to solve the inverse pollution source identification problems. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Anticancer, antibacterial and pollutant degradation potential of silver nanoparticles from Hyphaene thebaica.

PubMed

Bello, Bello Aminu; Khan, Shahid Ali; Khan, Jalaluddin Awllia; Syed, Fareeduddin Quadri; Mirza, Muqtadir Baig; Shah, Luqman; Khan, Sher Bahadar

2017-08-26

We present here the biosynthesis of AgNps from the aqueous extract of H. thebaica fruit, and monitored through UV-Vis spectrophotometer. The functional group were characterized through ATR-FTIR spectroscopy, the particle size, morphologies and elemental composition of the nanoparticles were investigated by using TEM, FESEM and EDS respectively. The anti-proliferation activity of the synthesized AgNps was carried out using MTT assay on human prostate (PC3), breast (MCF7) and liver (HepG2) cancer cell lines. The anti-proliferation assay showed that the AgNps were able to inhibit the proliferation of the cancer cell lines in a dose depending manner. The effect was found more pronounced on prostate (IC 50 2.6 mg/mL) followed by breast (IC 50 4.8 mg/mL) and then liver cancer cell lines (IC 50 6.8 mg/mL). The prepared AgNps were found to inhibit 99% growth of both E. coli and S. aureus after 24 h of incubation. The nanoparticles were used for the degradation of 4-nitrophenol (4-NP) and Congo red dyes (CR), which efficiently degrade CR, but make complex formation with 4-NP. Therefore, the AgNps synthesized from the aqueous fruit extract of H. thebaica have potential application in pharmacology and waste water treatment. Copyright © 2017 Elsevier Inc. All rights reserved.

Models of Fate and Transport of Pollutants in Surface Waters

NASA Astrophysics Data System (ADS)

Okome, Gloria Eloho

There is the need to answer very crucial questions of "what happens to pollutants in surface waters?" This question must be answered to determine the factors controlling fate and transport of chemicals and their evolutionary state in surface waters. Monitoring and experimental methods are used in establishing the environmental states. These measurements are used with the known scientific principles to identify processes and to estimate the future environmental conditions. Conceptual and computational models are needed to analyze environmental processes by applying the knowledge gained from experimentation and theory. Usually, a computational framework includes the mathematics and the physics of the phenomenon, and the measured characteristics to model pollutants interactions and transport in surface water. However, under certain conditions, the complexity of the situation in the actual environment precludes the utilization of these techniques. Pollutants in several forms: Nitrogen (Nitrate, Nitrite, Kjeldhal Nitrogen and Ammonia), Phosphorus (orthophosphate and total phosphorus), bacteria (E-coli and Fecal coliform), Salts (Chloride and Sulfate) are chosen to follow for this research. The objective of this research is to model the fate and transport of these pollutants in non-ideal conditions of surface water measurements and to develop computational methods to forecast their fate and transport. In an environment of extreme drought such as in the Brazos River basin, where small streams flow intermittently, there is added complexity due to the absence of regularly sampled data. The usual modeling techniques are no longer applicable because of sparse measurements in space and time. Still, there is a need to estimate the conditions of the environment from the information that is present. Alternative methods for this estimation must be devised and applied to this situation, which is the task of this dissertation. This research devices a forecasting technique that is

Assessing the polycyclic aromatic hydrocarbon (PAH) pollution of urban stormwater runoff: a dynamic modeling approach.

PubMed

Zheng, Yi; Lin, Zhongrong; Li, Hao; Ge, Yan; Zhang, Wei; Ye, Youbin; Wang, Xuejun

2014-05-15

Urban stormwater runoff delivers a significant amount of polycyclic aromatic hydrocarbons (PAHs), mostly of atmospheric origin, to receiving water bodies. The PAH pollution of urban stormwater runoff poses serious risk to aquatic life and human health, but has been overlooked by environmental modeling and management. This study proposed a dynamic modeling approach for assessing the PAH pollution and its associated environmental risk. A variable time-step model was developed to simulate the continuous cycles of pollutant buildup and washoff. To reflect the complex interaction among different environmental media (i.e. atmosphere, dust and stormwater), the dependence of the pollution level on antecedent weather conditions was investigated and embodied in the model. Long-term simulations of the model can be efficiently performed, and probabilistic features of the pollution level and its risk can be easily determined. The applicability of this approach and its value to environmental management was demonstrated by a case study in Beijing, China. The results showed that Beijing's PAH pollution of road runoff is relatively severe, and its associated risk exhibits notable seasonal variation. The current sweeping practice is effective in mitigating the pollution, but the effectiveness is both weather-dependent and compound-dependent. The proposed modeling approach can help identify critical timing and major pollutants for monitoring, assessing and controlling efforts to be focused on. The approach is extendable to other urban areas, as well as to other contaminants with similar fate and transport as PAHs. Copyright © 2014 Elsevier B.V. All rights reserved.

Modelling traffic air pollution in road tunnels

NASA Astrophysics Data System (ADS)

Bellasio, Roberto

This paper presents two models for the description of air pollutant concentrations in road tunnels due to traffic. Turbulence is assumed to depend on both atmospheric turbulence and vehicle's motion. Emissions are calculated with the COPERT90 methodology (Eggleston et al., 1991). Up to 34 different vehicle categories can be considered at the same time, with an arbitrary number of vehicles travelling inside the tunnel. Emissions are calculated as a function of the position inside the tunnel and of the time. Three pollutants can be simulated with the current version of the models, CO, NO x and VOC. It is also possible to consider vehicles with null emissions. The models are able to consider the effects of an arbitrary number of sinks. Flow rates and outdoor concentrations are a function of the time for each sink. The equation of conservation of mass has been solved with the control volumes method. Particular attention has been given to the formulation of stability conditions. Sensitivity analysis was conducted to verify the model answer to different input parameters such as initial concentration, boundary concentrations and vehicle-induced turbulence. Examples of application are given for a tunnel with urban traffic regime, including passenger cars with different fuels, light duty trucks, heavy duty trucks and motorbikes, and for an underground railway. Simulations have been carried out for the five working days of the week.

Effects of canyon geometry on the distribution of traffic-related air pollution in a large urban area: Implications of a multi-canyon air pollution dispersion model

NASA Astrophysics Data System (ADS)

Fu, Xiangwen; Liu, Junfeng; Ban-Weiss, George A.; Zhang, Jiachen; Huang, Xin; Ouyang, Bin; Popoola, Olalekan; Tao, Shu

2017-09-01

Street canyons are ubiquitous in urban areas. Traffic-related air pollutants in street canyons can adversely affect human health. In this study, an urban-scale traffic pollution dispersion model is developed considering street distribution, canyon geometry, background meteorology, traffic assignment, traffic emissions and air pollutant dispersion. In the model, vehicle exhausts generated from traffic flows first disperse inside street canyons along the micro-scale wind field generated by computational fluid dynamics (CFD) model. Then, pollutants leave the street canyon and further disperse over the urban area. On the basis of this model, the effects of canyon geometry on the distribution of NOx and CO from traffic emissions were studied over the center of Beijing. We found that an increase in building height leads to heavier pollution inside canyons and lower pollution outside canyons at pedestrian level, resulting in higher domain-averaged concentrations over the area. In addition, canyons with highly even or highly uneven building heights on each side of the street tend to lower the urban-scale air pollution concentrations at pedestrian level. Further, increasing street widths tends to lead to lower pollutant concentrations by reducing emissions and enhancing ventilation simultaneously. Our results indicate that canyon geometry strongly influences human exposure to traffic pollutants in the populated urban area. Carefully planning street layout and canyon geometry while considering traffic demand as well as local weather patterns may significantly reduce inhalation of unhealthy air by urban residents.

Translocation of silver nanoparticles in the ex vivo human placenta perfusion model characterized by single particle ICP-MS.

PubMed

Vidmar, Janja; Loeschner, Katrin; Correia, Manuel; Larsen, Erik H; Manser, Pius; Wichser, Adrian; Boodhia, Kailen; Al-Ahmady, Zahraa S; Ruiz, Jaimé; Astruc, Didier; Buerki-Thurnherr, Tina

2018-06-15

With the extensive use of silver nanoparticles (AgNPs) in various consumer products their potential toxicity is of great concern especially for highly sensitive population groups such as pregnant women and even the developing fetus. To understand if AgNPs are taken up and cross the human placenta, we studied their translocation and accumulation in the human ex vivo placenta perfusion model by single particle ICP-MS (spICP-MS). The impact of different surface modifications on placental transfer was assessed by AgNPs with two different modifications: polyethylene glycol (AgPEG NPs) and sodium carboxylate (AgCOONa NPs). AgNPs and ionic Ag were detected in the fetal circulation in low but not negligible amounts. Slightly higher Ag translocation across the placental barrier for perfusion with AgPEG NPs and higher AgNP accumulation in placental tissue for perfusion with AgCOONa NPs were observed. Since these AgNPs are soluble in water, we tried to distinguish between the translocation of dissolved and particulate Ag. Perfusion with AgNO3 revealed the formation of Ag containing NPs in both circulations over time, of which the amount and their size in the fetal circulation were comparable to those from perfusion experiments with both AgNP types. Although we were not able to clarify whether intact AgNPs and/or Ag precipitates from dissolved Ag cross the placental barrier, our study highlights that uptake of Ag ions and/or dissolution of AgNPs in the tissue followed by re-precipitation in the fetal circulation needs to be considered as an important pathway in studies of AgNP translocation across biological barriers.

An integrated Bayesian model for estimating the long-term health effects of air pollution by fusing modelled and measured pollution data: A case study of nitrogen dioxide concentrations in Scotland.

PubMed

Huang, Guowen; Lee, Duncan; Scott, Marian

2015-01-01

The long-term health effects of air pollution can be estimated using a spatio-temporal ecological study, where the disease data are counts of hospital admissions from populations in small areal units at yearly intervals. Spatially representative pollution concentrations for each areal unit are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over grid level concentrations from an atmospheric dispersion model. We propose a novel fusion model for estimating spatially aggregated pollution concentrations using both the modelled and monitored data, and relate these concentrations to respiratory disease in a new study in Scotland between 2007 and 2011. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Integrating a street-canyon model with a regional Gaussian dispersion model for improved characterisation of near-road air pollution

NASA Astrophysics Data System (ADS)

Fallah-Shorshani, Masoud; Shekarrizfard, Maryam; Hatzopoulou, Marianne

2017-03-01

The development and use of dispersion models that simulate traffic-related air pollution in urban areas has risen significantly in support of air pollution exposure research. In order to accurately estimate population exposure, it is important to generate concentration surfaces that take into account near-road concentrations as well as the transport of pollutants throughout an urban region. In this paper, an integrated modelling chain was developed to simulate ambient Nitrogen Dioxide (NO2) in a dense urban neighbourhood while taking into account traffic emissions, the regional background, and the transport of pollutants within the urban canopy. For this purpose, we developed a hybrid configuration including 1) a street canyon model, which simulates pollutant transfer along streets and intersections, taking into account the geometry of buildings and other obstacles, and 2) a Gaussian puff model, which resolves the transport of contaminants at the top of the urban canopy and accounts for regional meteorology. Each dispersion model was validated against measured concentrations and compared against the hybrid configuration. Our results demonstrate that the hybrid approach significantly improves the output of each model on its own. An underestimation appears clearly for the Gaussian model and street-canyon model compared to observed data. This is due to ignoring the building effect by the Gaussian model and undermining the contribution of other roads by the canyon model. The hybrid approach reduced the RMSE (of observed vs. predicted concentrations) by 16%-25% compared to each model on its own, and increased FAC2 (fraction of predictions within a factor of two of the observations) by 10%-34%.

Multi-scale modeling of urban air pollution: development of a Street-in-Grid model

NASA Astrophysics Data System (ADS)

Kim, Youngseob; Wu, You; Seigneur, Christian; Roustan, Yelva

2016-04-01

A new multi-scale model of urban air pollution is presented. This model combines a chemical-transport model (CTM) that includes a comprehensive treatment of atmospheric chemistry and transport at spatial scales greater than 1 km and a street-network model that describes the atmospheric concentrations of pollutants in an urban street network. The street-network model is based on the general formulation of the SIRANE model and consists of two main components: a street-canyon component and a street-intersection component. The street-canyon component calculates the mass transfer velocity at the top of the street canyon (roof top) and the mean wind velocity within the street canyon. The estimation of the mass transfer velocity depends on the intensity of the standard deviation of the vertical velocity at roof top. The effect of various formulations of this mass transfer velocity on the pollutant transport at roof-top level is examined. The street-intersection component calculates the mass transfer from a given street to other streets across the intersection. These mass transfer rates among the streets are calculated using the mean wind velocity calculated for each street and are balanced so that the total incoming flow rate is equal to the total outgoing flow rate from the intersection including the flow between the intersection and the overlying atmosphere at roof top. In the default option, the Leighton photostationary cycle among ozone (O3) and nitrogen oxides (NO and NO2) is used to represent the chemical reactions within the street network. However, the influence of volatile organic compounds (VOC) on the pollutant concentrations increases when the nitrogen oxides (NOx) concentrations are low. To account for the possible VOC influence on street-canyon chemistry, the CB05 chemical kinetic mechanism, which includes 35 VOC model species, is implemented in this street-network model. A sensitivity study is conducted to assess the uncertainties associated with the use of

Multi-model assessment of health impacts of air pollution in Europe and the U.S.

NASA Astrophysics Data System (ADS)

Im, Ulas; Brandt, Jørgen; Christensen, Jesper H.; Geels, Camilla; Hansen, Kaj M.; Andersen, Mikael S.; Solazzo, Efisio; Hogrefe, Christian; Galmarini, Stefano

2017-04-01

According to the World Health Organization (WHO), air pollution is now the world's largest single environmental health risk. Assessments of health impacts and the associated external costs related to air pollution are estimated based on observed and/or modelled air pollutant levels. Chemistry and transport models (CTMs) are useful tools to calculate the concentrations of health-related pollutants taking into account the non-linearities in the chemistry and the complex interactions between meteorology and chemistry. However, the CTMs include different chemical and aerosol schemes that introduce differences in the representation of the processes. Likewise, will differences in the emissions and boundary conditions used in the models add to the overall uncertainties. These uncertainties are introduced also into the health impact estimates using output from the CTMs. Multi-model (MM) ensembles can be useful to minimize these uncertainties introduced by the individual CTMs. In the present study, the simulated surface concentrations of health related air pollutants for the year 2010 from fifteen modelling groups participating in the AQMEII exercise, serve as input to the Economic Valuation of Air Pollution model (EVA), in order to calculate the impacts of these pollutants on human health and the associated external costs in Europe and U.S. In addition, the impacts of a 20% global emission reduction scenario on the human health and associated costs have been calculated. Preliminary results show that in Europe and U.S., the MM mean number of premature deaths due to air pollution is calculated to be 400 000 and 160 000, respectively. Estimated health impacts among different models can vary up to a factor of 3 and 1.2 in Europe and U.S., respectively. PM is calculated to be the major pollutant affecting the health impacts and the differences in models regarding the treatment of aerosol composition, physics and dynamics is a key factor. The total MM mean costs due to health

Air Quality Modeling of Traffic-related Air Pollutants for the NEXUS Study

EPA Science Inventory

The paper presents the results of the model applications to estimate exposure metrics in support of an epidemiologic study in Detroit, Michigan. A major challenge in traffic-related air pollution exposure studies is the lack of information regarding pollutant exposure characteriz...

Advection-diffusion model for the simulation of air pollution distribution from a point source emission

NASA Astrophysics Data System (ADS)

Ulfah, S.; Awalludin, S. A.; Wahidin

2018-01-01

Advection-diffusion model is one of the mathematical models, which can be used to understand the distribution of air pollutant in the atmosphere. It uses the 2D advection-diffusion model with time-dependent to simulate air pollution distribution in order to find out whether the pollutants are more concentrated at ground level or near the source of emission under particular atmospheric conditions such as stable, unstable, and neutral conditions. Wind profile, eddy diffusivity, and temperature are considered in the model as parameters. The model is solved by using explicit finite difference method, which is then visualized by a computer program developed using Lazarus programming software. The results show that the atmospheric conditions alone influencing the level of concentration of pollutants is not conclusive as the parameters in the model have their own effect on each atmospheric condition.

Measurement error in epidemiologic studies of air pollution based on land-use regression models.

PubMed

Basagaña, Xavier; Aguilera, Inmaculada; Rivera, Marcela; Agis, David; Foraster, Maria; Marrugat, Jaume; Elosua, Roberto; Künzli, Nino

2013-10-15

Land-use regression (LUR) models are increasingly used to estimate air pollution exposure in epidemiologic studies. These models use air pollution measurements taken at a small set of locations and modeling based on geographical covariates for which data are available at all study participant locations. The process of LUR model development commonly includes a variable selection procedure. When LUR model predictions are used as explanatory variables in a model for a health outcome, measurement error can lead to bias of the regression coefficients and to inflation of their variance. In previous studies dealing with spatial predictions of air pollution, bias was shown to be small while most of the effect of measurement error was on the variance. In this study, we show that in realistic cases where LUR models are applied to health data, bias in health-effect estimates can be substantial. This bias depends on the number of air pollution measurement sites, the number of available predictors for model selection, and the amount of explainable variability in the true exposure. These results should be taken into account when interpreting health effects from studies that used LUR models.

Establishment and application of the estimation model for pollutant concentrfation in agriculture drain

NASA Astrophysics Data System (ADS)

Li, Qiangkun; Hu, Yawei; Jia, Qian; Song, Changji

2018-02-01

It is the key point of quantitative research on agricultural non-point source pollution load, the estimation of pollutant concentration in agricultural drain. In the guidance of uncertainty theory, the synthesis of fertilization and irrigation is used as an impulse input to the farmland, meanwhile, the pollutant concentration in agricultural drain is looked as the response process corresponding to the impulse input. The migration and transformation of pollutant in soil is expressed by Inverse Gaussian Probability Density Function. The law of pollutants migration and transformation in soil at crop different growth periods is reflected by adjusting parameters of Inverse Gaussian Distribution. Based on above, the estimation model for pollutant concentration in agricultural drain at field scale was constructed. Taking the of Qing Tong Xia Irrigation District in Ningxia as an example, the concentration of nitrate nitrogen and total phosphorus in agricultural drain was simulated by this model. The results show that the simulated results accorded with measured data approximately and Nash-Sutcliffe coefficients were 0.972 and 0.964, respectively.

Antimicrobial and anticancer activity of AgNPs coated with Alphonsea sclerocarpa extract.

PubMed

Doddapaneni, Suman Joshi D S; Amgoth, Chander; Kalle, Arunasree M; Suryadevara, Surya Narayana; Alapati, Krishna Satya

2018-03-01

The synthesis and characterization of an aggregate of AgNPs coated with plant extract (PE) from Alphonsea sclerocarpa and its significant antimicrobial activity and inhibition on K562 (blood cancer) cells have been appended in the article. Synthesis of aggregate [(AgNPs)-(PE)] has been followed by a facile eco-friendly approach without using any harmful chemicals. The morphology of an aggregate [(AgNPs)-(PE)] was confirmed by TEM and SEM microscopic characterizations. Properties like solid state, the presence of functional groups, and elemental composition have been characterized through the XRD, FTIR, and EDAX. The biocompatibility of synthesized aggregate of [(AgNPs)-(PE)] was confirmed by the MTT assay. An in vitro cell (HEK293)-based studies were performed for the biocompatibility tests and it is found that the aggregate [(AgNPs)-(PE)] is not harmful to normal/healthy cells. Even though A. sclerocarpa show the antimicrobial (antibacterial and antifungal) activity, it has been further enhanced with the developed aggregate of [(AgNPs)-(PE)]. Furthermore, it has been extended to examine the cellular inhibition on K562 cells and obtained > 75% cell inhibition for 24 h treated cells.

Modeling population exposures to outdoor sources of hazardous air pollutants.

PubMed

Ozkaynak, Halûk; Palma, Ted; Touma, Jawad S; Thurman, James

2008-01-01

Accurate assessment of human exposures is an important part of environmental health effects research. However, most air pollution epidemiology studies rely upon imperfect surrogates of personal exposures, such as information based on available central-site outdoor concentration monitoring or modeling data. In this paper, we examine the limitations of using outdoor concentration predictions instead of modeled personal exposures for over 30 gaseous and particulate hazardous air pollutants (HAPs) in the US. The analysis uses the results from an air quality dispersion model (the ASPEN or Assessment System for Population Exposure Nationwide model) and an inhalation exposure model (the HAPEM or Hazardous Air Pollutant Exposure Model, Version 5), applied by the US. Environmental protection Agency during the 1999 National Air Toxic Assessment (NATA) in the US. Our results show that the total predicted chronic exposure concentrations of outdoor HAPs from all sources are lower than the modeled ambient concentrations by about 20% on average for most gaseous HAPs and by about 60% on average for most particulate HAPs (mainly, due to the exclusion of indoor sources from our modeling analysis and lower infiltration of particles indoors). On the other hand, the HAPEM/ASPEN concentration ratio averages for onroad mobile source exposures were found to be greater than 1 (around 1.20) for most mobile-source related HAPs (e.g. 1, 3-butadiene, acetaldehyde, benzene, formaldehyde) reflecting the importance of near-roadway and commuting environments on personal exposures to HAPs. The distribution of the ratios of personal to ambient concentrations was found to be skewed for a number of the VOCs and reactive HAPs associated with major source emissions, indicating the importance of personal mobility factors. We conclude that the increase in personal exposures from the corresponding predicted ambient levels tends to occur near locations where there are either major emission sources of HAPs

The River Basin Model: Computer Output. Water Pollution Control Research Series.

ERIC Educational Resources Information Center

Envirometrics, Inc., Washington, DC.

This research report is part of the Water Pollution Control Research Series which describes the results and progress in the control and abatement of pollution in our nation's waters. The River Basin Model described is a computer-assisted decision-making tool in which a number of computer programs simulate major processes related to water use that…

Simulation of population-based commuter exposure to NO₂ using different air pollution models.

PubMed

Ragettli, Martina S; Tsai, Ming-Yi; Braun-Fahrländer, Charlotte; de Nazelle, Audrey; Schindler, Christian; Ineichen, Alex; Ducret-Stich, Regina E; Perez, Laura; Probst-Hensch, Nicole; Künzli, Nino; Phuleria, Harish C

2014-05-12

We simulated commuter routes and long-term exposure to traffic-related air pollution during commute in a representative population sample in Basel (Switzerland), and evaluated three air pollution models with different spatial resolution for estimating commute exposures to nitrogen dioxide (NO2) as a marker of long-term exposure to traffic-related air pollution. Our approach includes spatially and temporally resolved data on actual commuter routes, travel modes and three air pollution models. Annual mean NO2 commuter exposures were similar between models. However, we found more within-city and within-subject variability in annual mean (±SD) NO2 commuter exposure with a high resolution dispersion model (40 ± 7 µg m(-3), range: 21-61) than with a dispersion model with a lower resolution (39 ± 5 µg m(-3); range: 24-51), and a land use regression model (41 ± 5 µg m(-3); range: 24-54). Highest median cumulative exposures were calculated along motorized transport and bicycle routes, and the lowest for walking. For estimating commuter exposure within a city and being interested also in small-scale variability between roads, a model with a high resolution is recommended. For larger scale epidemiological health assessment studies, models with a coarser spatial resolution are likely sufficient, especially when study areas include suburban and rural areas.

Silver nanoparticles induce tight junction disruption and astrocyte neurotoxicity in a rat blood-brain barrier primary triple coculture model.

PubMed

Xu, Liming; Dan, Mo; Shao, Anliang; Cheng, Xiang; Zhang, Cuiping; Yokel, Robert A; Takemura, Taro; Hanagata, Nobutaka; Niwa, Masami; Watanabe, Daisuke

2015-01-01

Silver nanoparticles (Ag-NPs) can enter the brain and induce neurotoxicity. However, the toxicity of Ag-NPs on the blood-brain barrier (BBB) and the underlying mechanism(s) of action on the BBB and the brain are not well understood. To investigate Ag-NP suspension (Ag-NPS)-induced toxicity, a triple coculture BBB model of rat brain microvascular endothelial cells, pericytes, and astrocytes was established. The BBB permeability and tight junction protein expression in response to Ag-NPS, NP-released Ag ions, and polystyrene-NP exposure were investigated. Ultrastructural changes of the microvascular endothelial cells, pericytes, and astrocytes were observed using transmission electron microscopy (TEM). Global gene expression of astrocytes was measured using a DNA microarray. A triple coculture BBB model of primary rat brain microvascular endothelial cells, pericytes, and astrocytes was established, with the transendothelial electrical resistance values >200 Ω·cm(2). After Ag-NPS exposure for 24 hours, the BBB permeability was significantly increased and expression of the tight junction (TJ) protein ZO-1 was decreased. Discontinuous TJs were also observed between microvascular endothelial cells. After Ag-NPS exposure, severe mitochondrial shrinkage, vacuolations, endoplasmic reticulum expansion, and Ag-NPs were observed in astrocytes by TEM. Global gene expression analysis showed that three genes were upregulated and 20 genes were downregulated in astrocytes treated with Ag-NPS. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that the 23 genes were associated with metabolic processes, biosynthetic processes, response to stimuli, cell death, the MAPK pathway, and so on. No GO term and KEGG pathways were changed in the released-ion or polystyrene-NP groups. Ag-NPS inhibited the antioxidant defense of the astrocytes by increasing thioredoxin interacting protein, which inhibits the Trx system, and decreasing Nr4a1 and Dusp1

Silver nanoparticles induce tight junction disruption and astrocyte neurotoxicity in a rat blood–brain barrier primary triple coculture model

PubMed Central

Xu, Liming; Dan, Mo; Shao, Anliang; Cheng, Xiang; Zhang, Cuiping; Yokel, Robert A; Takemura, Taro; Hanagata, Nobutaka; Niwa, Masami; Watanabe, Daisuke

2015-01-01

Background Silver nanoparticles (Ag-NPs) can enter the brain and induce neurotoxicity. However, the toxicity of Ag-NPs on the blood–brain barrier (BBB) and the underlying mechanism(s) of action on the BBB and the brain are not well understood. Method To investigate Ag-NP suspension (Ag-NPS)-induced toxicity, a triple coculture BBB model of rat brain microvascular endothelial cells, pericytes, and astrocytes was established. The BBB permeability and tight junction protein expression in response to Ag-NPS, NP-released Ag ions, and polystyrene-NP exposure were investigated. Ultrastructural changes of the microvascular endothelial cells, pericytes, and astrocytes were observed using transmission electron microscopy (TEM). Global gene expression of astrocytes was measured using a DNA microarray. Results A triple coculture BBB model of primary rat brain microvascular endothelial cells, pericytes, and astrocytes was established, with the transendothelial electrical resistance values >200 Ω·cm2. After Ag-NPS exposure for 24 hours, the BBB permeability was significantly increased and expression of the tight junction (TJ) protein ZO-1 was decreased. Discontinuous TJs were also observed between microvascular endothelial cells. After Ag-NPS exposure, severe mitochondrial shrinkage, vacuolations, endoplasmic reticulum expansion, and Ag-NPs were observed in astrocytes by TEM. Global gene expression analysis showed that three genes were upregulated and 20 genes were downregulated in astrocytes treated with Ag-NPS. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that the 23 genes were associated with metabolic processes, biosynthetic processes, response to stimuli, cell death, the MAPK pathway, and so on. No GO term and KEGG pathways were changed in the released-ion or polystyrene-NP groups. Ag-NPS inhibited the antioxidant defense of the astrocytes by increasing thioredoxin interacting protein, which inhibits the Trx system, and

“Modeling Trends in Air Pollutant Concentrations over the ...

EPA Pesticide Factsheets

Regional model calculations over annual cycles have pointed to the need for accurately representing impacts of long-range transport. Linking regional and global scale models have met with mixed success as biases in the global model can propagate and influence regional calculations and often confound interpretation of model results. Since transport is efficient in the free-troposphere and since simulations over Continental scales and annual cycles provide sufficient opportunity for “atmospheric turn-over”, i.e., exchange between the free-troposphere and the boundary-layer, a conceptual framework is needed wherein interactions between processes occurring at various spatial and temporal scales can be consistently examined. The coupled WRF-CMAQ model is expanded to hemispheric scales and model simulations over period spanning 1990-current are analyzed to examine changes in hemispheric air pollution resulting from changes in emissions over this period. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for pr

Asian pollution climatically modulates mid-latitude cyclones following hierarchical modelling and observational analysis

NASA Astrophysics Data System (ADS)

Wang, Yuan; Zhang, Renyi; Saravanan, R.

2014-01-01

Increasing levels of anthropogenic aerosols in Asia have raised considerable concern regarding its potential impact on the global atmosphere, but the magnitude of the associated climate forcing remains to be quantified. Here, using a novel hierarchical modelling approach and observational analysis, we demonstrate modulated mid-latitude cyclones by Asian pollution over the past three decades. Regional and seasonal simulations using a cloud-resolving model show that Asian pollution invigorates winter cyclones over the northwest Pacific, increasing precipitation by 7% and net cloud radiative forcing by 1.0 W m-2 at the top of the atmosphere and by 1.7 W m-2 at the Earth’s surface. A global climate model incorporating the diabatic heating anomalies from Asian pollution produces a 9% enhanced transient eddy meridional heat flux and reconciles a decadal variation of mid-latitude cyclones derived from the Reanalysis data. Our results unambiguously reveal a large impact of the Asian pollutant outflows on the global general circulation and climate.

Economic-environmental modeling of point source pollution in Jefferson County, Alabama, USA.

PubMed

Kebede, Ellene; Schreiner, Dean F; Huluka, Gobena

2002-05-01

This paper uses an integrated economic-environmental model to assess the point source pollution from major industries in Jefferson County, Northern Alabama. Industrial expansion generates employment, income, and tax revenue for the public sector; however, it is also often associated with the discharge of chemical pollutants. Jefferson County is one of the largest industrial counties in Alabama that experienced smog warnings and ambient ozone concentration, 1996-1999. Past studies of chemical discharge from industries have used models to assess the pollution impact of individual plants. This study, however, uses an extended Input-Output (I-O) economic model with pollution emission coefficients to assess direct and indirect pollutant emission for several major industries in Jefferson County. The major findings of the study are: (a) the principal emission by the selected industries are volatile organic compounds (VOC) and these contribute to the ambient ozone concentration; (b) the direct and indirect emissions are significantly higher than the direct emission by some industries, indicating that an isolated analysis will underestimate the emission by an industry; (c) while low emission coefficient industries may suggest industry choice they may also emit the most hazardous chemicals. This study is limited by the assumptions made, and the data availability, however it provides a useful analytical tool for direct and cumulative emission estimation and generates insights on the complexity in choice of industries.

Air Pollution Data for Model Evaluation and Application

EPA Science Inventory

One objective of designing an air pollution monitoring network is to obtain data for evaluating air quality models that are used in the air quality management process and scientific discovery.^1.2 A common use is to relate emissions to air quality, including assessing ...

A novel multifunctional electrochemical platform for simultaneous detection, elimination, and inactivation of pathogenic bacteria based on the Vancomycin-functionalised AgNPs/3D-ZnO nanorod arrays.

PubMed

Yang, Zhiqing; Wang, Yi; Zhang, Dun

2017-12-15

A novel fast, sensitive, and specific multifunctional electrochemical platform has been proposed for simultaneous detection, elimination, and inactivation of pathogenic bacteria for the first time. The platform is constituted with three-dimensional ZnO nanorod arrays (3D-ZnO) decorated with sliver nanoparticles (AgNPs) and functionalized with vancomycin (Van). Based on the specific recognition of Van for Gram-positive bacteria, the fabricated electrochemical platform has presented high detection sensitivity to Staphylococcus aureus with a low detection limit of 330cfu/mL and adaptable bacterial-elimination efficiency (50%) at low concentrations (1000-2000cfu/mL). Moreover, the platform has shown high antibacterial activity (99.99%) arising from the synergistic germicidal effect of the composited antibacterial AgNPs and Van units. The current work could provide new strategies to construct advanced platforms for simultaneous detection, elimination, and inactivation of various pathogenic bacteria. Copyright © 2017 Elsevier B.V. All rights reserved.

Psychological effect on single-species population models in a polluted environment.

PubMed

Wei, Fengying; Chen, Lihong

2017-08-01

We formulate and investigate the psychological effect of single-species population models in a polluted environment in this paper. For the deterministic single-species population model, the conditions that guarantee the local extinction and persistence in the mean are derived firstly. We then show that, around the pollution-free equilibrium, the stochastic single-species population is weakly persistent in the mean, and is stochastically permanent under some conditions. As a consequence, some numerical simulations demonstrate the efficiency of the main results. Copyright © 2017 Elsevier Inc. All rights reserved.

Models for predicting the ratio of particulate pollutant concentrations inside vehicles to roadways

PubMed Central

Hudda, N.; Fruin, S. A.

2013-01-01

Under closed-window driving conditions, the in-vehicle-to-outside (I/O) concentration ratio for traffic-related particulate pollutants ranges from nearly zero to one, and varies up to five-fold across a fleet of vehicles, thus strongly affecting occupant exposures. Concentrations of five particulate pollutants (particle-bound polycyclic aromatic hydrocarbons, black carbon, ultrafine particle number, and fine and coarse particulate mass) were measured simultaneously while systematically varying key influential parameters (i.e., vehicle type, ventilation, and speed). The I/O ratios for these pollutants were primarily determined by vehicle air exchange rate (AER), AER being mostly a function of ventilation setting (recirculation or outside air), vehicle characteristics (e.g., age, interior volume) and driving speed. Small (±0.15) but measurable differences in I/O ratios between pollutants were observed although ratios were highly correlated. This allowed us to build on previous studies of ultrafine particle number I/O ratios to develop predictive models for other particulate pollutants. These models explained over 60% of measured variation, using ventilation setting, driving speed, and easily-obtained vehicle characteristics as predictors. Our results suggest that I/O ratios for different particulate pollutants need not necessarily be measured individually and that exposure to all particulate pollutants may be reduced significantly by simple ventilation choices. PMID:23957386

Multivariate space-time modelling of multiple air pollutants and their health effects accounting for exposure uncertainty.

PubMed

Huang, Guowen; Lee, Duncan; Scott, E Marian

2018-03-30

The long-term health effects of air pollution are often estimated using a spatio-temporal ecological areal unit study, but this design leads to the following statistical challenges: (1) how to estimate spatially representative pollution concentrations for each areal unit; (2) how to allow for the uncertainty in these estimated concentrations when estimating their health effects; and (3) how to simultaneously estimate the joint effects of multiple correlated pollutants. This article proposes a novel 2-stage Bayesian hierarchical model for addressing these 3 challenges, with inference based on Markov chain Monte Carlo simulation. The first stage is a multivariate spatio-temporal fusion model for predicting areal level average concentrations of multiple pollutants from both monitored and modelled pollution data. The second stage is a spatio-temporal model for estimating the health impact of multiple correlated pollutants simultaneously, which accounts for the uncertainty in the estimated pollution concentrations. The novel methodology is motivated by a new study of the impact of both particulate matter and nitrogen dioxide concentrations on respiratory hospital admissions in Scotland between 2007 and 2011, and the results suggest that both pollutants exhibit substantial and independent health effects. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Change Detection Analysis of Water Pollution in Coimbatore Region using Different Color Models

NASA Astrophysics Data System (ADS)

Jiji, G. Wiselin; Devi, R. Naveena

2017-12-01

The data acquired through remote sensing satellites furnish facts about the land and water at varying resolutions and has been widely used for several change detection studies. Apart from the existence of many change detection methodologies and techniques, emergence of new ones continues to subsist. Existing change detection techniques exploit images that are either in gray scale or RGB color model. In this paper we introduced color models for performing change detection for water pollution. Here the polluted lakes are classified and post-classification change detection techniques are applied to RGB images and results obtained are analysed for changes to exist or not. Furthermore RGB images obtained after classification when converted to any of the two color models YCbCr and YIQ is found to produce the same results as that of the RGB model images. Thus it can be concluded that other color models like YCbCr, YIQ can be used as substitution to RGB color model for analysing change detection with regard to water pollution.

Updated model assessment of pollution at major U. S. Airports

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yamartino, R.J.; Rote, D.M.

1979-02-01

The air quality impact of aircraft at and around Los Angeles International Airport (LAX) is simulated for hours of peak aircraft operation and worst case pollutant dispersion conditions. An updated version of the Argonne Airport Vicinity Air Pollution (AVAP) model is used in the simulation; model refinements reflect new theoretical formulations and data from field programs at LAX, O'Hare, and John F. Kennedy International Airports. Maximum carbon monoxide concentrations at LAX are found to be low relative to the NAAQS. Relatively high, widespread hydrocarbon levels indicate that aircraft emissions may aggravate oxidant problems near the airport. Concentrations of oxides ofmore » nitrogen are high enough relative to proposed standards to warrant further study. Similar modeling is underway for the O'Hare and JFK airports.« less

Modelling of point and diffuse pollution: application of the Moneris model in the Ipojuca river basin, Pernambuco State, Brazil.

PubMed

de Lima Barros, Alessandra Maciel; do Carmo Sobral, Maria; Gunkel, Günter

2013-01-01

Emissions of pollutants and nutrients are causing several problems in aquatic ecosystems, and in general an excess of nutrients, specifically nitrogen and phosphorus, is responsible for the eutrophication process in water bodies. In most developed countries, more attention is given to diffuse pollution because problems with point pollution have already been solved. In many non-developed countries basic data for point and diffuse pollution are not available. The focus of the presented studies is to quantify nutrient emissions from point and diffuse sources in the Ipojuca river basin, Pernambuco State, Brazil, using the Moneris model (Modelling Nutrient Emissions in River Systems). This model has been developed in Germany and has already been implemented in more than 600 river basins. The model is mainly based on river flow, water quality and geographical information system data. According to the Moneris model results, untreated domestic sewage is the major source of nutrients in the Ipojuca river basin. The Moneris model has shown itself to be a useful tool that allows the identification and quantification of point and diffuse nutrient sources, thus enabling the adoption of measures to reduce them. The Moneris model, conducted for the first time in a tropical river basin with intermittent flow, can be used as a reference for implementation in other watersheds.

Spatial measurement error and correction by spatial SIMEX in linear regression models when using predicted air pollution exposures.

PubMed

Alexeeff, Stacey E; Carroll, Raymond J; Coull, Brent

2016-04-01

Spatial modeling of air pollution exposures is widespread in air pollution epidemiology research as a way to improve exposure assessment. However, there are key sources of exposure model uncertainty when air pollution is modeled, including estimation error and model misspecification. We examine the use of predicted air pollution levels in linear health effect models under a measurement error framework. For the prediction of air pollution exposures, we consider a universal Kriging framework, which may include land-use regression terms in the mean function and a spatial covariance structure for the residuals. We derive the bias induced by estimation error and by model misspecification in the exposure model, and we find that a misspecified exposure model can induce asymptotic bias in the effect estimate of air pollution on health. We propose a new spatial simulation extrapolation (SIMEX) procedure, and we demonstrate that the procedure has good performance in correcting this asymptotic bias. We illustrate spatial SIMEX in a study of air pollution and birthweight in Massachusetts. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

An empirical assessment of exposure measurement error and effect attenuation in bi-pollutant epidemiologic models

EPA Science Inventory

Background: Using multipollutant models to understand combined health effects of exposure to multiple pollutants is becoming more common. However, complex relationships between pollutants and differing degrees of exposure error across pollutants can make health effect estimates f...

Incorporating Measurement Error from Modeled Air Pollution Exposures into Epidemiological Analyses.

PubMed

Samoli, Evangelia; Butland, Barbara K

2017-12-01

Outdoor air pollution exposures used in epidemiological studies are commonly predicted from spatiotemporal models incorporating limited measurements, temporal factors, geographic information system variables, and/or satellite data. Measurement error in these exposure estimates leads to imprecise estimation of health effects and their standard errors. We reviewed methods for measurement error correction that have been applied in epidemiological studies that use model-derived air pollution data. We identified seven cohort studies and one panel study that have employed measurement error correction methods. These methods included regression calibration, risk set regression calibration, regression calibration with instrumental variables, the simulation extrapolation approach (SIMEX), and methods under the non-parametric or parameter bootstrap. Corrections resulted in small increases in the absolute magnitude of the health effect estimate and its standard error under most scenarios. Limited application of measurement error correction methods in air pollution studies may be attributed to the absence of exposure validation data and the methodological complexity of the proposed methods. Future epidemiological studies should consider in their design phase the requirements for the measurement error correction method to be later applied, while methodological advances are needed under the multi-pollutants setting.

Study on the Influence of Building Materials on Indoor Pollutants and Pollution Sources

NASA Astrophysics Data System (ADS)

Wang, Yao

2018-01-01

The paper summarizes the achievements and problems of indoor air quality research at home and abroad. The pollutants and pollution sources in the room are analyzed systematically. The types of building materials and pollutants are also discussed. The physical and chemical properties and health effects of main pollutants were analyzed and studied. According to the principle of mass balance, the basic mathematical model of indoor air quality is established. Considering the release rate of pollutants and indoor ventilation, a mathematical model for predicting the concentration of indoor air pollutants is derived. The model can be used to analyze and describe the variation of pollutant concentration in indoor air, and to predict and calculate the concentration of pollutants in indoor air at a certain time. The results show that the mathematical model established in this study can be used to analyze and predict the variation law of pollutant concentration in indoor air. The evaluation model can be used to evaluate the impact of indoor air quality and evaluation of current situation. Especially in the process of building and interior decoration, through pre-evaluation, it can provide reliable design parameters for selecting building materials and determining ventilation volume.

An empirical assessment of exposure measurement errors and effect attenuation in bi-pollutant epidemiologic models

EPA Science Inventory

Using multipollutant models to understand the combined health effects of exposure to multiple pollutants is becoming more common. However, the complex relationships between pollutants and differing degrees of exposure error across pollutants can make health effect estimates from ...

FUZZY COMPUTATIONAL MODELS TO EVALUATE THE EFFECTS OF AIR POLLUTION ON CHILDREN.

PubMed

David, Gleise Silva; Rizol, Paloma Maria Silva Rocha; Nascimento, Luiz Fernando Costa

2018-01-01

To build a fuzzy computational model to estimate the number of hospitalizations of children aged up to 10 years due to respiratory conditions based on pollutants and climatic factors in the city of São José do Rio Preto, Brazil. A computational model was constructed using the fuzzy logic. The model has 4 inputs, each with 2 membership functions generating 16 rules, and the output with 5 pertinence functions, based on the Mamdani's method, to estimate the association between the pollutants and the number of hospitalizations. Data from hospitalizations, from 2011-2013, were obtained in DATASUS - and the pollutants Particulate Matter (PM10) and Nitrogen Dioxide (NO2), wind speed and temperature were obtained by the Environmental Company of São Paulo State (Cetesb). A total of 1,161 children were hospitalized in the period and the mean of pollutants was 36 and 51 µg/m3 - PM10 and NO2, respectively. The best values of the Pearson correlation (0.34) and accuracy measured by the Receiver Operating Characteristic (ROC) curve (NO2 - 96.7% and PM10 - 90.4%) were for hospitalizations on the same day of exposure. The model was effective in predicting the number of hospitalizations of children and could be used as a tool in the hospital management of the studied region.

[Priority pollutants ranking and screening of coke industry based on USEtox model].

PubMed

Hao, Tian; Du, Peng-Fei; Du, Bin; Zeng, Si-Yu

2014-01-01

Thesis aims at evaluating and setting priority to human toxicity and ecotoxicity of coking pollutants. A field research and sampling project are conducted in coke plant in Shanxi so as to complete the coke emission inventory. The USEtox model representing recommended practice in LCIA characterization is applied to the emission inventory to quantify the potential impacts on human toxicity and ecotoxicity of emerging pollutants. Priority pollutants, production procedures and effects of changing plant site on the toxicity are analyzed. As conclusions, benzo(a) pyrene, benzene, Zn and As are identified as the priority pollutants in human toxicity, while pyrene and anthracene in ecotoxicity. Coal charging is the dominant procedure for organic toxicity and priority pollutants include benzo (a) pyrene, benzene, naphthalene, etc. While coke drenching is the dominant procedure for metal toxicity and priority pollutants include Zn, As, Ti, Hg etc. Emission to rural environment can reduce the organic toxicity significantly compared to the emission to urban environment. However, the site changing has no effect on metal toxicity and might increase the risk of the metal pollution to rural water and soil.

Study of non-Hodgkin's lymphoma mortality associated with industrial pollution in Spain, using Poisson models

PubMed Central

Ramis, Rebeca; Vidal, Enrique; García-Pérez, Javier; Lope, Virginia; Aragonés, Nuria; Pérez-Gómez, Beatriz; Pollán, Marina; López-Abente, Gonzalo

2009-01-01

Background Non-Hodgkin's lymphomas (NHLs) have been linked to proximity to industrial areas, but evidence regarding the health risk posed by residence near pollutant industries is very limited. The European Pollutant Emission Register (EPER) is a public register that furnishes valuable information on industries that release pollutants to air and water, along with their geographical location. This study sought to explore the relationship between NHL mortality in small areas in Spain and environmental exposure to pollutant emissions from EPER-registered industries, using three Poisson-regression-based mathematical models. Methods Observed cases were drawn from mortality registries in Spain for the period 1994–2003. Industries were grouped into the following sectors: energy; metal; mineral; organic chemicals; waste; paper; food; and use of solvents. Populations having an industry within a radius of 1, 1.5, or 2 kilometres from the municipal centroid were deemed to be exposed. Municipalities outside those radii were considered as reference populations. The relative risks (RRs) associated with proximity to pollutant industries were estimated using the following methods: Poisson Regression; mixed Poisson model with random provincial effect; and spatial autoregressive modelling (BYM model). Results Only proximity of paper industries to population centres (>2 km) could be associated with a greater risk of NHL mortality (mixed model: RR:1.24, 95% CI:1.09–1.42; BYM model: RR:1.21, 95% CI:1.01–1.45; Poisson model: RR:1.16, 95% CI:1.06–1.27). Spatial models yielded higher estimates. Conclusion The reported association between exposure to air pollution from the paper, pulp and board industry and NHL mortality is independent of the model used. Inclusion of spatial random effects terms in the risk estimate improves the study of associations between environmental exposures and mortality. The EPER could be of great utility when studying the effects of industrial pollution

Tuning the inflammatory response to silver nanoparticles via quercetin in Caco-2 (co-)cultures as model of the human intestinal mucosa.

PubMed

Martirosyan, Alina; Grintzalis, Konstantinos; Polet, Madeleine; Laloux, Laurie; Schneider, Yves-Jacques

2016-06-24

Interaction of nanoparticles with food matrix components may cause unpredictable health complications. Using an improved Caco-2 cell-based in vitro (co-)culture model the potential of quercetin as one of the major food flavonoids to alter the effect of silver nanoparticles (Ag-NPs) <20 nm in the human intestinal mucosa at real life concentrations was investigated. Ag-NPs (15-90 μg/ml) decreased cell viability and reduced thiol groups, induced oxidative/nitrosative stress and lipid peroxidation and led to activity changes of various antioxidant enzymes after 3h exposure. The contribution of Ag(+) ions within the concentrations released from nanoparticles was shown to be less important, compared to Ag-NPs. While leading to inflammatory response in the intestines, Ag-NPs, paradoxically, also showed a potential anti-infammatory effect manifested in down-regulated IL-8 levels. Quercetin, co-administered with Ag-NPs, led to a reduction of cytotoxicity, oxidative stress, and recovered metabolic activity of Caco-2 cells, suggesting the protective effects of this flavonoid against the harmful effect of Ag-NPs. Quercetin not only alleviated the effect of Ag-NPs on the gastrointestinal cells, but also demonstrated a potential to serve as a tool for reversible modulation of intestinal permeability. Copyright © 2016. Published by Elsevier Ireland Ltd.

How Good and Useful Are Air Pollution Models?

ERIC Educational Resources Information Center

Environmental Science and Technology, 1973

1973-01-01

The Regional Air Pollution Study (RAPS) to be conducted in St. Louis, is the largest air monitoring program of the Environmental Protection Agency. A key segment will be the collection of a data base on which this system of mathematical models can be tested and upon which submodels can be validated. (BL)

Monitoring Mediterranean marine pollution using remote sensing and hydrodynamic modelling

NASA Astrophysics Data System (ADS)

La Loggia, Goffredo; Capodici, Fulvio; Ciraolo, Giuseppe; Drago, Aldo; Maltese, Antonino

2011-11-01

Human activities contaminate both coastal areas and open seas, even though impacts are different in terms of pollutants, ecosystems and recovery time. In particular, Mediterranean offshore pollution is mainly related to maritime transport of oil, accounting for 25% of the global maritime traffic and, during the last 25 years, for nearly 7% of the world oil accidents, thus causing serious biological impacts on both open sea and coastal zone habitats. This paper provides a general review of maritime pollution monitoring using integrated approaches of remote sensing and hydrodynamic modeling; focusing on the main results of the MAPRES (Marine pollution monitoring and detection by aerial surveillance and satellite images) research project on the synergistic use of remote sensing, forecasting, cleanup measures and environmental consequences. The paper also investigates techniques of oil spill detection using SAR images, presenting the first results of "Monitoring of marine pollution due to oil slick", a COSMO-SkyMed funded research project where X-band SAR constellation images provided by the Italian Space Agency are used. Finally, the prospect of using real time observations of marine surface conditions is presented through CALYPSO project (CALYPSO-HF Radar Monitoring System and Response against Marine Oil Spills in the Malta Channel), partly financed by the EU under the Operational Programme Italia-Malta 2007-2013. The project concerns the setting up of a permanent and fully operational HF radar observing system, capable of recording surface currents (in real-time with hourly updates) in the stretch of sea between Malta and Sicily. A combined use of collected data and numerical models, aims to optimize intervention and response in the case of marine oil spills.

Air pollution and survival within the Washington University-EPRI veterans cohort: risks based on modeled estimates of ambient levels of hazardous and criteria air pollutants.

PubMed

Lipfert, Frederick W; Wyzga, Ronald E; Baty, Jack D; Miller, J Philip

2009-04-01

For this paper, we considered relationships between mortality, vehicular traffic density, and ambient levels of 12 hazardous air pollutants, elemental carbon (EC), oxides of nitrogen (NOx), sulfur dioxide (SO2), and sulfate (SO4(2-)). These pollutant species were selected as markers for specific types of emission sources, including vehicular traffic, coal combustion, smelters, and metal-working industries. Pollutant exposures were estimated using emissions inventories and atmospheric dispersion models. We analyzed associations between county ambient levels of these pollutants and survival patterns among approximately 70,000 U.S. male veterans by mortality period (1976-2001 and subsets), type of exposure model, and traffic density level. We found significant associations between all-cause mortality and traffic-related air quality indicators and with traffic density per se, with stronger associations for benzene, formaldehyde, diesel particulate, NOx, and EC. The maximum effect on mortality for all cohort subjects during the 26-yr follow-up period is approximately 10%, but most of the pollution-related deaths in this cohort occurred in the higher-traffic counties, where excess risks approach 20%. However, mortality associations with diesel particulates are similar in high- and low-traffic counties. Sensitivity analyses show risks decreasing slightly over time and minor differences between linear and logarithmic exposure models. Two-pollutant models show stronger risks associated with specific traffic-related pollutants than with traffic density per se, although traffic density retains statistical significance in most cases. We conclude that tailpipe emissions of both gases and particles are among the most significant and robust predictors of mortality in this cohort and that most of those associations have weakened over time. However, we have not evaluated possible contributions from road dust or traffic noise. Stratification by traffic density level suggests the

Regression trees modeling and forecasting of PM10 air pollution in urban areas

NASA Astrophysics Data System (ADS)

Stoimenova, M.; Voynikova, D.; Ivanov, A.; Gocheva-Ilieva, S.; Iliev, I.

2017-10-01

Fine particulate matter (PM10) air pollution is a serious problem affecting the health of the population in many Bulgarian cities. As an example, the object of this study is the pollution with PM10 of the town of Pleven, Northern Bulgaria. The measured concentrations of this air pollutant for this city consistently exceeded the permissible limits set by European and national legislation. Based on data for the last 6 years (2011-2016), the analysis shows that this applies both to the daily limit of 50 micrograms per cubic meter and the allowable number of daily concentration exceedances to 35 per year. Also, the average annual concentration of PM10 exceeded the prescribed norm of no more than 40 micrograms per cubic meter. The aim of this work is to build high performance mathematical models for effective prediction and forecasting the level of PM10 pollution. The study was conducted with the powerful flexible data mining technique Classification and Regression Trees (CART). The values of PM10 were fitted with respect to meteorological data such as maximum and minimum air temperature, relative humidity, wind speed and direction and others, as well as with time and autoregressive variables. As a result the obtained CART models demonstrate high predictive ability and fit the actual data with up to 80%. The best models were applied for forecasting the level pollution for 3 to 7 days ahead. An interpretation of the modeling results is presented.

Cartographic modelling of aerotechnogenic pollution in snow cover in the landscapes of the Kola Peninsula.

PubMed

Ratkin, N E; Asming, V E; Koshkin, V V

2001-01-01

The goal of this work was to develop computational techniques for sulphates, nickel and copper accumulation in the snow in the local pollution zone. The main task was to reveal the peculiarities of formation and pollution of snow cover on the region with complex cross-relief. A digital cartographic model of aerotechnogenic pollution of snow cover in the landscapes of the local zone has been developed, based on five-year experimental data. Data regarding annual emissions from the industrial complex, information about distribution of wind and the sum of precipitation from meteostation "Nikel" for the winter period, allowed the model to ensure: * material presentation in the form of maps of water capacity and accumulation of sulphates, nickel and copper in the snow over any winter period in retrospective; * calculation of water capacity and accumulation of pollutants for watersheds and other natural-territorial complexes; * solution of the opposite problem about the determination of the emissions of sulphates, nickel and copper from the enterprise by measuring snow pollution in datum points. The model can be used in other northern regions of the Russian Federation with similar physical-geographical and climatic conditions. The relationships between the sum of precipitation and water capacity in the landscapes of the same type and also the relationships between pollution content in snow and relief, pollution content in snow and distance from the source of emissions, were used as the basis for the model.

Simulation of Population-Based Commuter Exposure to NO2 Using Different Air Pollution Models

PubMed Central

Ragettli, Martina S.; Tsai, Ming-Yi; Braun-Fahrländer, Charlotte; de Nazelle, Audrey; Schindler, Christian; Ineichen, Alex; Ducret-Stich, Regina E.; Perez, Laura; Probst-Hensch, Nicole; Künzli, Nino; Phuleria, Harish C.

2014-01-01

We simulated commuter routes and long-term exposure to traffic-related air pollution during commute in a representative population sample in Basel (Switzerland), and evaluated three air pollution models with different spatial resolution for estimating commute exposures to nitrogen dioxide (NO2) as a marker of long-term exposure to traffic-related air pollution. Our approach includes spatially and temporally resolved data on actual commuter routes, travel modes and three air pollution models. Annual mean NO2 commuter exposures were similar between models. However, we found more within-city and within-subject variability in annual mean (±SD) NO2 commuter exposure with a high resolution dispersion model (40 ± 7 µg m−3, range: 21–61) than with a dispersion model with a lower resolution (39 ± 5 µg m−3; range: 24–51), and a land use regression model (41 ± 5 µg m−3; range: 24–54). Highest median cumulative exposures were calculated along motorized transport and bicycle routes, and the lowest for walking. For estimating commuter exposure within a city and being interested also in small-scale variability between roads, a model with a high resolution is recommended. For larger scale epidemiological health assessment studies, models with a coarser spatial resolution are likely sufficient, especially when study areas include suburban and rural areas. PMID:24823664

QUANTIFYING SUBGRID POLLUTANT VARIABILITY IN EULERIAN AIR QUALITY MODELS

EPA Science Inventory

In order to properly assess human risk due to exposure to hazardous air pollutants or air toxics, detailed information is needed on the location and magnitude of ambient air toxic concentrations. Regional scale Eulerian air quality models are typically limited to relatively coar...

Comparison of Six Highway Air Pollution Dispersion Models Using Synthetic Data

DOT National Transportation Integrated Search

1977-09-01

This is the second of two studies conducted by the Transportation Systems Center (TSC) to test the performance of highway air pollution dispersion models, using synthetic data (i.e., either measured or artificially constructed input data for models, ...

STEMS-Air: a simple GIS-based air pollution dispersion model for city-wide exposure assessment.

PubMed

Gulliver, John; Briggs, David

2011-05-15

Current methods of air pollution modelling do not readily meet the needs of air pollution mapping for short-term (i.e. daily) exposure studies. The main limiting factor is that for those few models that couple with a GIS there are insufficient tools for directly mapping air pollution both at high spatial resolution and over large areas (e.g. city wide). A simple GIS-based air pollution model (STEMS-Air) has been developed for PM(10) to meet these needs with the option to choose different exposure averaging periods (e.g. daily and annual). STEMS-Air uses the grid-based FOCALSUM function in ArcGIS in conjunction with a fine grid of emission sources and basic information on meteorology to implement a simple Gaussian plume model of air pollution dispersion. STEMS-Air was developed and validated in London, UK, using data on concentrations of PM(10) from routinely available monitoring data. Results from the validation study show that STEMS-Air performs well in predicting both daily (at four sites) and annual (at 30 sites) concentrations of PM(10). For daily modelling, STEMS-Air achieved r(2) values in the range 0.19-0.43 (p<0.001) based solely on traffic-related emissions and r(2) values in the range 0.41-0.63 (p<0.001) when adding information on 'background' levels of PM(10). For annual modelling of PM(10), the model returned r(2) in the range 0.67-0.77 (P<0.001) when compared with monitored concentrations. The model can thus be used for rapid production of daily or annual city-wide air pollution maps either as a screening process in urban air quality planning and management, or as the basis for health risk assessment and epidemiological studies. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.

Kinetic modelling of a diesel-polluted clayey soil bioremediation process.

PubMed

Fernández, Engracia Lacasa; Merlo, Elena Moliterni; Mayor, Lourdes Rodríguez; Camacho, José Villaseñor

2016-07-01

A mathematical model is proposed to describe a diesel-polluted clayey soil bioremediation process. The reaction system under study was considered a completely mixed closed batch reactor, which initially contacted a soil matrix polluted with diesel hydrocarbons, an aqueous liquid-specific culture medium and a microbial inoculation. The model coupled the mass transfer phenomena and the distribution of hydrocarbons among four phases (solid, S; water, A; non-aqueous liquid, NAPL; and air, V) with Monod kinetics. In the first step, the model simulating abiotic conditions was used to estimate only the mass transfer coefficients. In the second step, the model including both mass transfer and biodegradation phenomena was used to estimate the biological kinetic and stoichiometric parameters. In both situations, the model predictions were validated with experimental data that corresponded to previous research by the same authors. A correct fit between the model predictions and the experimental data was observed because the modelling curves captured the major trends for the diesel distribution in each phase. The model parameters were compared to different previously reported values found in the literature. Pearson correlation coefficients were used to show the reproducibility level of the model. Copyright © 2016. Published by Elsevier B.V.

Stable Isotope Mixing Models as a Tool for Tracking Sources of Water and Water Pollutants

EPA Science Inventory

One goal of monitoring pollutants is to be able to trace the pollutant to its source. Here we review how mixing models using stable isotope information on water and water pollutants can help accomplish this goal. A number of elements exist in multiple stable (non-radioactive) i...

[Applying temporally-adjusted land use regression models to estimate ambient air pollution exposure during pregnancy].

PubMed

Zhang, Y J; Xue, F X; Bai, Z P

2017-03-06

The impact of maternal air pollution exposure on offspring health has received much attention. Precise and feasible exposure estimation is particularly important for clarifying exposure-response relationships and reducing heterogeneity among studies. Temporally-adjusted land use regression (LUR) models are exposure assessment methods developed in recent years that have the advantage of having high spatial-temporal resolution. Studies on the health effects of outdoor air pollution exposure during pregnancy have been increasingly carried out using this model. In China, research applying LUR models was done mostly at the model construction stage, and findings from related epidemiological studies were rarely reported. In this paper, the sources of heterogeneity and research progress of meta-analysis research on the associations between air pollution and adverse pregnancy outcomes were analyzed. The methods of the characteristics of temporally-adjusted LUR models were introduced. The current epidemiological studies on adverse pregnancy outcomes that applied this model were systematically summarized. Recommendations for the development and application of LUR models in China are presented. This will encourage the implementation of more valid exposure predictions during pregnancy in large-scale epidemiological studies on the health effects of air pollution in China.

A Critical Commentary on the 2017 AGNP Consensus Guidelines for Therapeutic Drug Monitoring in Neuropsychopharmacology.

PubMed

de Leon, Jose

2018-01-01

In 2004, 2011, and 2017, the Arbeitsgemeinschaft für Neuropsychopharmakologie und Pharmakopsychiatrie (AGNP), a group of German-speaking psychiatric researchers and psychiatrists, published successive versions of therapeutic drug monitoring (TDM) expert group consensus guidelines. The 2017 version has as a major strength its encyclopedic nature, including 1358 references. The guideline has 3 major sections: 1) theoretical aspects of TDM, 2) drug concentration levels in blood to guide neuropsychopharmacotherapy, and 3) practical aspects of TDM in psychiatry and neurology. The writer hopes the time is right for a TDM guideline in psychiatry, which is indicated for: 1) psychiatric researchers ready to value how TDM can contribute to moving psychopharmacology forward, 2) flexible clinicians ready to improve their patient care by personalizing dosing, and 3) today's psychiatry residents prepared as a new generation ready to be trained in TDM and willing to continue incorporating TDM as new psychiatric drugs are marketed. © Georg Thieme Verlag KG Stuttgart · New York.

Diurnal cycle of air pollution in the Kathmandu Valley, Nepal: 2. Modeling results

NASA Astrophysics Data System (ADS)

Panday, Arnico K.; Prinn, Ronald G.; SchäR, Christoph

2009-11-01

After completing a 9-month field experiment studying air pollution and meteorology in the Kathmandu Valley, Nepal, we set up the mesoscale meteorological model MM5 to simulate the Kathmandu Valley's meteorology with a horizontal resolution of up to 1 km. After testing the model against available data, we used it to address specific questions to understand the factors that control the observed diurnal cycle of air pollution in this urban basin in the Himalayas. We studied the dynamics of the basin's nocturnal cold air pool, its dissipation in the morning, and the subsequent growth and decay of the mixed layer over the valley. During mornings, we found behavior common to large basins, with upslope flows and basin-center subsidence removing the nocturnal cold air pool. During afternoons the circulation in the Kathmandu Valley exhibited patterns common to plateaus, with cooler denser air originating over lower regions west of Kathmandu arriving through mountain passes and spreading across the basin floor, thereby reducing the mixed layer depth. We also examined the pathways of pollutant ventilation out of the valley. The bulk of the pollution ventilation takes place during the afternoon, when strong westerly winds blow in through the western passes of the valley, and the pollutants are rapidly carried out through passes on the east and south sides of the valley. In the evening, pollutants first accumulate near the surface, but then are lifted slightly when katabatic flows converge underneath. The elevated polluted layers are mixed back down in the morning, contributing to the morning pollution peak. Later in the morning a fraction of the valley's pollutants travels up the slopes of the valley rim mountains before the westerly winds begin.

Forecasting human exposure to atmospheric pollutants in Portugal - A modelling approach

NASA Astrophysics Data System (ADS)

Borrego, C.; Sá, E.; Monteiro, A.; Ferreira, J.; Miranda, A. I.

2009-12-01

Air pollution has become one main environmental concern because of its known impact on human health. Aiming to inform the population about the air they are breathing, several air quality modelling systems have been developed and tested allowing the assessment and forecast of air pollution ambient levels in many countries. However, every day, an individual is exposed to different concentrations of atmospheric pollutants as he/she moves from and to different outdoor and indoor places (the so-called microenvironments). Therefore, a more efficient way to prevent the population from the health risks caused by air pollution should be based on exposure rather than air concentrations estimations. The objective of the present study is to develop a methodology to forecast the human exposure of the Portuguese population based on the air quality forecasting system available and validated for Portugal since 2005. Besides that, a long-term evaluation of human exposure estimates aims to be obtained using one-year of this forecasting system application. Additionally, a hypothetical 50% emission reduction scenario has been designed and studied as a contribution to study emission reduction strategies impact on human exposure. To estimate the population exposure the forecasting results of the air quality modelling system MM5-CHIMERE have been combined with the population spatial distribution over Portugal and their time-activity patterns, i.e. the fraction of the day time spent in specific indoor and outdoor places. The population characterization concerning age, work, type of occupation and related time spent was obtained from national census and available enquiries performed by the National Institute of Statistics. A daily exposure estimation module has been developed gathering all these data and considering empirical indoor/outdoor relations from literature to calculate the indoor concentrations in each one of the microenvironments considered, namely home, office/school, and other

ADDRESSING HUMAN EXPOSURES TO AIR POLLUTANTS AROUND BUILDINGS IN URBAN AREAS WITH COMPUTATIONAL FLUID DYNAMICS MODELS

EPA Science Inventory

This paper discusses the status and application of Computational Fluid Dynamics (CFD) models to address challenges for modeling human exposures to air pollutants around urban building microenvironments. There are challenges for more detailed understanding of air pollutant sour...

REPRESENTATION OF ATMOSPHERIC MOTION IN MODELS OF REGIONAL-SCALE AIR POLLUTION

EPA Science Inventory

A method is developed for generating ensembles of wind fields for use in regional scale (1000 km) models of transport and diffusion. The underlying objective is a methodology for representing atmospheric motion in applied air pollution models that permits explicit treatment of th...

Modeling indoor air pollution of outdoor origin in homes of SAPALDIA subjects in Switzerland.

PubMed

Meier, Reto; Schindler, Christian; Eeftens, Marloes; Aguilera, Inmaculada; Ducret-Stich, Regina E; Ineichen, Alex; Davey, Mark; Phuleria, Harish C; Probst-Hensch, Nicole; Tsai, Ming-Yi; Künzli, Nino

2015-09-01

Given the shrinking spatial contrasts in outdoor air pollution in Switzerland and the trends toward tightly insulated buildings, the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) needs to understand to what extent outdoor air pollution remains a determinant for residential indoor exposure. The objectives of this paper are to identify determining factors for indoor air pollution concentrations of particulate matter (PM), ultrafine particles in the size range from 15 to 300nm, black smoke measured as light absorbance of PM (PMabsorbance) and nitrogen dioxide (NO2) and to develop predictive indoor models for SAPALDIA. Multivariable regression models were developed based on indoor and outdoor measurements among homes of selected SAPALDIA participants in three urban (Basel, Geneva, Lugano) and one rural region (Wald ZH) in Switzerland, various home characteristics and reported indoor sources such as cooking. Outdoor levels of air pollutants were important predictors for indoor air pollutants, except for the coarse particle fraction. The fractions of outdoor concentrations infiltrating indoors were between 30% and 66%, the highest one was observed for PMabsorbance. A modifying effect of open windows was found for NO2 and the ultrafine particle number concentration. Cooking was associated with increased particle and NO2 levels. This study shows that outdoor air pollution remains an important determinant of residential indoor air pollution in Switzerland. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modelling the bioaccumulation of persistent organic pollutants in agricultural food chains for regulatory exposure assessment.

PubMed

Takaki, Koki; Wade, Andrew J; Collins, Chris D

2017-02-01

New models for estimating bioaccumulation of persistent organic pollutants in the agricultural food chain were developed using recent improvements to plant uptake and cattle transfer models. One model named AgriSim was based on K OW regressions of bioaccumulation in plants and cattle, while the other was a steady-state mechanistic model, AgriCom. The two developed models and European Union System for the Evaluation of Substances (EUSES), as a benchmark, were applied to four reported food chain (soil/air-grass-cow-milk) scenarios to evaluate the performance of each model simulation against the observed data. The four scenarios considered were as follows: (1) polluted soil and air, (2) polluted soil, (3) highly polluted soil surface and polluted subsurface and (4) polluted soil and air at different mountain elevations. AgriCom reproduced observed milk bioaccumulation well for all four scenarios, as did AgriSim for scenarios 1 and 2, but EUSES only did this for scenario 1. The main causes of the deviation for EUSES and AgriSim were the lack of the soil-air-plant pathway and the ambient air-plant pathway, respectively. Based on the results, it is recommended that soil-air-plant and ambient air-plant pathway should be calculated separately and the K OW regression of transfer factor to milk used in EUSES be avoided. AgriCom satisfied the recommendations that led to the low residual errors between the simulated and the observed bioaccumulation in agricultural food chain for the four scenarios considered. It is therefore recommended that this model should be incorporated into regulatory exposure assessment tools. The model uncertainty of the three models should be noted since the simulated concentration in milk from 5th to 95th percentile of the uncertainty analysis often varied over two orders of magnitude. Using a measured value of soil organic carbon content was effective to reduce this uncertainty by one order of magnitude.

Development of a global pollution model for CO, CH4, and CH2O

NASA Technical Reports Server (NTRS)

Peters, L. K.

1974-01-01

The current status of a global pollution model for carbon monoxide, methane, and formaldehyde is described. The physico-chemical action is considered of these three pollutants in the troposphere. This geographic restriction is convenient since the tropopause provides a natural boundary across which little transport occurs. The data on sources and sinks for these pollutants is based on available information and assumptions relative to the major man-made and natural contributions. The distributions and concentrations of methane, formaldehyde, and carbon monoxide in the atmosphere are interrelated by the chemical reactions in which they participate. A chemical kinetic model based on the pseudo-steady state approximation for the intermediate species was developed to account for these reactions. The numerical procedure used to mathematically describe the pollution transport is a mass conservative scheme employing an integral flux approach.

An Examination of a Model of Anti-Pollution Behavior.

ERIC Educational Resources Information Center

Iwata, Osamu

1981-01-01

Reports results of a study in which Japanese female undergraduates (N=118) responded to an environmental concern scale based upon a model of anti-pollution behavior focusing on: approach to information, confidence in science and technology, appreciation of natural beauty, causes, consequences, and purchasing and coping behaviors. (DC)

Validation and optimization of SST k-ω turbulence model for pollutant dispersion within a building array

NASA Astrophysics Data System (ADS)

Yu, Hesheng; Thé, Jesse

2016-11-01

The prediction of the dispersion of air pollutants in urban areas is of great importance to public health, homeland security, and environmental protection. Computational Fluid Dynamics (CFD) emerges as an effective tool for pollutant dispersion modelling. This paper reports and quantitatively validates the shear stress transport (SST) k-ω turbulence closure model and its transitional variant for pollutant dispersion under complex urban environment for the first time. Sensitivity analysis is performed to establish recommendation for the proper use of turbulence models in urban settings. The current SST k-ω simulation is validated rigorously by extensive experimental data using hit rate for velocity components, and the "factor of two" of observations (FAC2) and fractional bias (FB) for concentration field. The simulation results show that current SST k-ω model can predict flow field nicely with an overall hit rate of 0.870, and concentration dispersion with FAC2 = 0.721 and FB = 0.045. The flow simulation of the current SST k-ω model is slightly inferior to that of a detached eddy simulation (DES), but better than that of standard k-ε model. However, the current study is the best among these three model approaches, when validated against measurements of pollutant dispersion in the atmosphere. This work aims to provide recommendation for proper use of CFD to predict pollutant dispersion in urban environment.

Modeling of Electrochemical Process for the Treatment of Wastewater Containing Organic Pollutants

NASA Astrophysics Data System (ADS)

Rodrigo, Manuel A.; Cañizares, Pablo; Lobato, Justo; Sáez, Cristina

Electrocoagulation and electrooxidation are promising electrochemical technologies that can be used to remove organic pollutants contained in wastewaters. To make these technologies competitive with the conventional technologies that are in use today, a better understanding of the processes involved must be achieved. In this context, the development of mathematical models that are consistent with the processes occurring in a physical system is a relevant advance, because such models can help to understand what is happening in the treatment process. In turn, a more detailed knowledge of the physical system can be obtained, and tools for a proper design of the processes, or for the analysis of operating problems, are attained. The modeling of these technologies can be carried out using single-variable or multivariable models. Likewise, the position dependence of the model species can be described with different approaches. In this work, a review of the basics of the modeling of these processes and a description of several representative models for electrochemical oxidation and coagulation are carried out. Regarding electrooxidation, two models are described: one which summarizes the pollution of a wastewater in only one model species and that considers a macroscopic approach to formulate the mass balances and other that considers more detailed profile of concentration to describe the time course of pollutants and intermediates through a mixed maximum gradient/macroscopic approach. On the topic of electrochemical coagulation, two different approaches are also described in this work: one that considers the hydrodynamic conditions as the main factor responsible for the electrochemical coagulation processes and the other that considers the chemical interaction of the reagents and the pollutants as the more significant processes in the description of the electrochemical coagulation of organic compounds. In addition, in this work it is also described a multivariable model

Natural marine bacteria as model organisms for the hazard-assessment of consumer products containing silver nanoparticles.

PubMed

Echavarri-Bravo, Virginia; Paterson, Lynn; Aspray, Thomas J; Porter, Joanne S; Winson, Michael K; Hartl, Mark G J

2017-09-01

Scarce information is available regarding the fate and toxicology of engineered silver nanoparticles (AgNPs) in the marine environment, especially when compared to other environmental compartments. Hence, the antibacterial activity of the NM-300 AgNPs (OECD programme) and a household product containing colloidal AgNPs (Mesosilver) was investigated using marine bacteria, pure cultures and natural mixed populations (microcosm approach). Bacterial susceptibility to AgNPs was species-specific, with Gram negative bacteria being more resistant than the Gram positive species (NM-300 concentration used ranged between 0.062 and 1.5 mg L -1 ), and the Mesosilver product was more toxic than the NM-300. Bacterial viability and the physiological status (O 2 uptake measured by respirometry) of the microbial community in the microcosm was negatively affected at an initial concentration of 1 mg L -1 NM-300. The high chloride concentrations in the media/seawater led to the formation of silver-chloro complexes thus enhancing AgNP toxicity. We recommend the use of natural marine bacteria as models when assessing the environmental relevant antibacterial properties of products containing nanosilver. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

DIDEM - An integrated model for comparative health damage costs calculation of air pollution

NASA Astrophysics Data System (ADS)

Ravina, Marco; Panepinto, Deborah; Zanetti, Maria Chiara

2018-01-01

Air pollution represents a continuous hazard to human health. Administration, companies and population need efficient indicators of the possible effects given by a change in decision, strategy or habit. The monetary quantification of health effects of air pollution through the definition of external costs is increasingly recognized as a useful indicator to support decision and information at all levels. The development of modelling tools for the calculation of external costs can provide support to analysts in the development of consistent and comparable assessments. In this paper, the DIATI Dispersion and Externalities Model (DIDEM) is presented. The DIDEM model calculates the delta-external costs of air pollution comparing two alternative emission scenarios. This tool integrates CALPUFF's advanced dispersion modelling with the latest WHO recommendations on concentration-response functions. The model is based on the impact pathway method. It was designed to work with a fine spatial resolution and a local or national geographic scope. The modular structure allows users to input their own data sets. The DIDEM model was tested on a real case study, represented by a comparative analysis of the district heating system in Turin, Italy. Additional advantages and drawbacks of the tool are discussed in the paper. A comparison with other existing models worldwide is reported.

Multiscale modeling of multi-decadal trends in air pollutant concentrations and their radiative properties: the role of models in an integrated observing system

NASA Astrophysics Data System (ADS)

Mathur, R.; Xing, J.; Szykman, J.; Gan, C. M.; Hogrefe, C.; Pleim, J. E.

2015-12-01

Air Pollution simulation models must address the increasing complexity arising from new model applications that treat multi-pollutant interactions across varying space and time scales. Setting and attaining lower ambient air quality standards requires an improved understanding and quantification of source attribution amongst the multiple anthropogenic and natural sources, on time scales ranging from episodic to annual and spatial scales ranging from urban to continental. Changing emission patterns over the developing regions of the world are likely to exacerbate the impacts of long-range pollutant transport on background pollutant levels, which may then impact the attainment of local air quality standards. Thus, strategies for reduction of pollution levels of surface air over a region are complicated not only by the interplay of local emissions sources and several complex physical, chemical, dynamical processes in the atmosphere, but also hemispheric background levels of pollutants. Additionally, as short-lived climate forcers, aerosols and ozone exert regionally heterogeneous radiative forcing and influence regional climate trends. EPA's coupled WRF-CMAQ modeling system is applied over a domain encompassing the northern hemisphere for the period spanning 1990-2010. This period has witnessed significant reductions in anthropogenic emissions in North America and Europe as a result of implementation of control measures and dramatic increases across Asia associated with economic and population growth, resulting in contrasting trends in air pollutant distributions and transport patterns across the northern hemisphere. Model results (trends in pollutant concentrations, optical and radiative characteristics) across the northern hemisphere are analyzed in conjunction with surface, aloft and remote sensing measurements to contrast the differing trends in air pollution and aerosol-radiation interactions in these regions over the past two decades. Given the future LEO (Trop

Multi-model evaluation of short-lived pollutant distributions over east Asia during summer 2008

NASA Astrophysics Data System (ADS)

Quennehen, B.; Raut, J.-C.; Law, K. S.; Daskalakis, N.; Ancellet, G.; Clerbaux, C.; Kim, S.-W.; Lund, M. T.; Myhre, G.; Olivié, D. J. L.; Safieddine, S.; Skeie, R. B.; Thomas, J. L.; Tsyro, S.; Bazureau, A.; Bellouin, N.; Hu, M.; Kanakidou, M.; Klimont, Z.; Kupiainen, K.; Myriokefalitakis, S.; Quaas, J.; Rumbold, S. T.; Schulz, M.; Cherian, R.; Shimizu, A.; Wang, J.; Yoon, S.-C.; Zhu, T.

2016-08-01

The ability of seven state-of-the-art chemistry-aerosol models to reproduce distributions of tropospheric ozone and its precursors, as well as aerosols over eastern Asia in summer 2008, is evaluated. The study focuses on the performance of models used to assess impacts of pollutants on climate and air quality as part of the EU ECLIPSE project. Models, run using the same ECLIPSE emissions, are compared over different spatial scales to in situ surface, vertical profiles and satellite data. Several rather clear biases are found between model results and observations, including overestimation of ozone at rural locations downwind of the main emission regions in China, as well as downwind over the Pacific. Several models produce too much ozone over polluted regions, which is then transported downwind. Analysis points to different factors related to the ability of models to simulate VOC-limited regimes over polluted regions and NOx limited regimes downwind. This may also be linked to biases compared to satellite NO2, indicating overestimation of NO2 over and to the north of the northern China Plain emission region. On the other hand, model NO2 is too low to the south and west of this region and over South Korea/Japan. Overestimation of ozone is linked to systematic underestimation of CO particularly at rural sites and downwind of the main Chinese emission regions. This is likely to be due to enhanced destruction of CO by OH. Overestimation of Asian ozone and its transport downwind implies that radiative forcing from this source may be overestimated. Model-observation discrepancies over Beijing do not appear to be due to emission controls linked to the Olympic Games in summer 2008.With regard to aerosols, most models reproduce the satellite-derived AOD patterns over eastern China. Our study nevertheless reveals an overestimation of ECLIPSE model mean surface BC and sulphate aerosols in urban China in summer 2008. The effect of the short-term emission mitigation in Beijing

An Eulerian model for scavenging of pollutants by raindrops

NASA Astrophysics Data System (ADS)

Kumar, Sudarshan

An Eulerian model for simulating the coupled processes of gas-phase depletion and aqueousphase accumulation of the pollutant species during a rain event has been formulated. The model is capable of taking into account any realistic vertical profile of pollutant species concentrations and time-dependent initial aqueous-phase concentrations at the cloud base. The model considers the processes of single species absorption and dissociation in the aqueous phase. The coupled partial differential equations constituting the model are discretized into a set of ordinary differential equations by using the Galerkin method with chapeau functions as the basis functions. These equations are solved to obtain the pollutant concentrations of the gas phase and raindrops as well as the pH of raindrops as a function of time and distance below cloud-base. Simulations are performed for scavenging of gaseous HNO 3, H 2O 2, SO 2, formaldehyde and NH 3. For the case of highly soluble HNO 3 and H 2O 2, raindrops are far from equilibrium with the gas phase and their capacity for absorption of these gases is undiminished even as they reach ground level. The gas-phase concentrations for these species decrease exponentially with time and the washout is determined primarily by the rain intensity and mass-transfer coefficient of the gaseous species to the raindrops. The pollutant species concentrations in raindrops are an almost linear function of the distance below the cloud base. For the simulation conditions considered in this study, the half-life periods of these gases for removal from the atmosphere range from 15 to 40 min. For SO 2 and formaldehyde, the aqueous-phase concentrations approach equilibrium as the drops fall to ground level and the gas-phase concentrations show large gradients in the vertical. Half-life periods for SO 2 range from 1.3 to 13 h depending on the initial raindrop pH and rain intensity. For formaldehyde, the half-life ranges from 19 to 63 min. Solubility of NH 3 is a

A REVIEW OF BIOACCUMULATION MODELING APPROACHES FOR PERSISTENT ORGANIC POLLUTANTS

EPA Science Inventory

Persistent organic pollutants and mercury are likely to bioaccumulate in biological components of the environment, including fish and wildlife. The complex and long-term dynamics involved with bioaccumulation are often represented with models. Current scientific developments in t...

The NLS-Based Nonlinear Grey Multivariate Model for Forecasting Pollutant Emissions in China.

PubMed

Pei, Ling-Ling; Li, Qin; Wang, Zheng-Xin

2018-03-08

The relationship between pollutant discharge and economic growth has been a major research focus in environmental economics. To accurately estimate the nonlinear change law of China's pollutant discharge with economic growth, this study establishes a transformed nonlinear grey multivariable (TNGM (1, N )) model based on the nonlinear least square (NLS) method. The Gauss-Seidel iterative algorithm was used to solve the parameters of the TNGM (1, N ) model based on the NLS basic principle. This algorithm improves the precision of the model by continuous iteration and constantly approximating the optimal regression coefficient of the nonlinear model. In our empirical analysis, the traditional grey multivariate model GM (1, N ) and the NLS-based TNGM (1, N ) models were respectively adopted to forecast and analyze the relationship among wastewater discharge per capita (WDPC), and per capita emissions of SO₂ and dust, alongside GDP per capita in China during the period 1996-2015. Results indicated that the NLS algorithm is able to effectively help the grey multivariable model identify the nonlinear relationship between pollutant discharge and economic growth. The results show that the NLS-based TNGM (1, N ) model presents greater precision when forecasting WDPC, SO₂ emissions and dust emissions per capita, compared to the traditional GM (1, N ) model; WDPC indicates a growing tendency aligned with the growth of GDP, while the per capita emissions of SO₂ and dust reduce accordingly.

A Bayesian Multivariate Receptor Model for Estimating Source Contributions to Particulate Matter Pollution using National Databases.

PubMed

Hackstadt, Amber J; Peng, Roger D

2014-11-01

Time series studies have suggested that air pollution can negatively impact health. These studies have typically focused on the total mass of fine particulate matter air pollution or the individual chemical constituents that contribute to it, and not source-specific contributions to air pollution. Source-specific contribution estimates are useful from a regulatory standpoint by allowing regulators to focus limited resources on reducing emissions from sources that are major contributors to air pollution and are also desired when estimating source-specific health effects. However, researchers often lack direct observations of the emissions at the source level. We propose a Bayesian multivariate receptor model to infer information about source contributions from ambient air pollution measurements. The proposed model incorporates information from national databases containing data on both the composition of source emissions and the amount of emissions from known sources of air pollution. The proposed model is used to perform source apportionment analyses for two distinct locations in the United States (Boston, Massachusetts and Phoenix, Arizona). Our results mirror previous source apportionment analyses that did not utilize the information from national databases and provide additional information about uncertainty that is relevant to the estimation of health effects.

Updated model assessment of pollution at major U. S. airports

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yamartino, R.J.; Rote, D.M.

1979-02-01

The air quality impact of aircraft at and around Los Angeles International Airport (LAX) was simulated for hours of peak aircraft operation and 'worst case' pollutant dispersion conditions by using an updated version of the Argonne Airport Vicinity Air Pollution model; field programs at LAX, O'Hara, and John F. Kennedy International Airports determined the 'worst case' conditions. Maximum carbon monoxide concentrations at LAX were low relative to National Ambient Air Quality Standards; relatively high and widespread hydrocarbon concentrations indicated that aircraft emissions may aggravate oxidant problems near the airport; nitrogen oxide concentrations were close to the levels set in proposedmore » standards. Data on typical time-in-mode for departing and arriving aircraft, the 8/4/77 diurnal variation in airport activity, and carbon monoxide concentration isopleths are given, and the update factors in the model are discussed.« less

Impact of covariate models on the assessment of the air pollution-mortality association in a single- and multipollutant context.

PubMed

Sacks, Jason D; Ito, Kazuhiko; Wilson, William E; Neas, Lucas M

2012-10-01

With the advent of multicity studies, uniform statistical approaches have been developed to examine air pollution-mortality associations across cities. To assess the sensitivity of the air pollution-mortality association to different model specifications in a single and multipollutant context, the authors applied various regression models developed in previous multicity time-series studies of air pollution and mortality to data from Philadelphia, Pennsylvania (May 1992-September 1995). Single-pollutant analyses used daily cardiovascular mortality, fine particulate matter (particles with an aerodynamic diameter ≤2.5 µm; PM(2.5)), speciated PM(2.5), and gaseous pollutant data, while multipollutant analyses used source factors identified through principal component analysis. In single-pollutant analyses, risk estimates were relatively consistent across models for most PM(2.5) components and gaseous pollutants. However, risk estimates were inconsistent for ozone in all-year and warm-season analyses. Principal component analysis yielded factors with species associated with traffic, crustal material, residual oil, and coal. Risk estimates for these factors exhibited less sensitivity to alternative regression models compared with single-pollutant models. Factors associated with traffic and crustal material showed consistently positive associations in the warm season, while the coal combustion factor showed consistently positive associations in the cold season. Overall, mortality risk estimates examined using a source-oriented approach yielded more stable and precise risk estimates, compared with single-pollutant analyses.

Computer Modeling of Transportation-Generated Air Pollution : State-of-the-Art Survey, II

DOT National Transportation Integrated Search

1978-06-01

THE STATE-OF-THE-ART IS SURVEYED IN AIR POLLUTION MODELLING WITH PARTICULAR EMPHASIS ON THE MODELING OF DISPERSION FROM TRANSPORTATION SOURCES. MODELS WHICH HAVE ACTUALLY BEEN IMPLEMENTED ARE STRESSED AND THE COMPUTATIONAL ASPECTS OF THESE MODELS ARE...

Computer Modeling of Transportation-Generated Air Pollution : State-of-the-Art Survey, II

DOT National Transportation Integrated Search

1978-06-01

The state-of-the-art is surveyed in air pollution modeling with particular emphasis on the modeling of dispersion from transportation sources. Models which have actually been implemented are stressed and the computational aspects of these models are ...

Computer Modeling of Transportation-Generated Air Pollution - a State-of-the-Art Survey

DOT National Transportation Integrated Search

1972-06-01

THE STATE-OF-THE-ART IS SURVEYED IN AIR POLLUTION MODELLING WITH PARTICULAR EMPHASIS ON THE MODELING OF DISPERSION FROM TRANSPORTATION SOURCES. MODELS WHICH HAVE ACTUALLY BEEN IMPLEMENTED ARE STRESSED AND THE COMPUTATIONAL ASPECTS OF THESE MODELS ARE...

Topical Silver Nanoparticles Result in Improved Bleb Function by Increasing Filtration and Reducing Fibrosis in a Rabbit Model of Filtration Surgery

PubMed Central

Butler, Michelle R.; Prospero Ponce, Claudia M.; Weinstock, Y. Etan; Orengo-Nania, Silvia; Chevez-Barrios, Patricia; Frankfort, Benjamin J.

2013-01-01

Purpose. To compare the effects of silver nanoparticles (AgNPs) and mitomycin C (MMC) on intraocular pressure (IOP) and external, histologic, and immunohistochemical bleb characteristics in a rabbit model of filtration surgery. Methods. Filtration surgery with concurrent topical application of either AgNPs or MMC was performed on 14 pigmented Dutch Belted rabbits. IOP and bleb characteristics were compared on postoperative day 1 and at weeks 1 through 6. Hematoxylin and eosin staining and smooth muscle actin (SMA) immunohistochemistry were performed at postoperative week 6. Results. Average IOP across all time points was reduced 5.8 and 3.8 mm Hg in AgNP- and MMC-treated eyes, respectively. At week 6, IOP was reduced 4.1 and 0.2 mm Hg in AgNP- and MMC-treated eyes, respectively. Blebs were smaller, thicker, and less ischemic in AgNP-treated eyes. AgNP-treated eyes showed less fibrosis and more stromal edema, suggesting increased filtration, and also had fewer SMA-positive myofibroblasts, suggesting reduced bleb contraction. AgNP-treated eyes showed more lymphocytes than MMC-treated eyes. There were few complications in both groups. Conclusions. In a rabbit model of filtration surgery, AgNPs are a reasonable alternative to MMC as adjunctive therapy. Compared to MMC, AgNPs result in an improved and sustained reduction of IOP and promote blebs with decreased fibrosis and ischemia as well as increased filtration despite a smaller overall size. This combination may offer an opportunity to promote long-term surgical IOP reduction with an improved complication profile. PMID:23766475

A multi-model assessment of pollution transport to the Arctic

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shindell, D T; Chin, M; Dentener, F

2008-03-13

We examine the response of Arctic gas and aerosol concentrations to perturbations in pollutant emissions from Europe, East and South Asia, and North America using results from a coordinated model intercomparison. These sensitivities to regional emissions (mixing ratio change per unit emission) vary widely across models and species. Intermodel differences are systematic, however, so that the relative importance of different regions is robust. North America contributes the most to Arctic ozone pollution. For aerosols and CO, European emissions dominate at the Arctic surface but East Asian emissions become progressively more important with altitude, and are dominant in the upper troposphere.more » Sensitivities show strong seasonality: surface sensitivities typically maximize during boreal winter for European and during spring for East Asian and North American emissions. Mid-tropospheric sensitivities, however, nearly always maximize during spring or summer for all regions. Deposition of black carbon (BC) onto Greenland is most sensitive to North American emissions. North America and Europe each contribute {approx}40% of total BC deposition to Greenland, with {approx}20% from East Asia. Elsewhere in the Arctic, both sensitivity and total BC deposition are dominated by European emissions. Model diversity for aerosols is especially large, resulting primarily from differences in aerosol physical and chemical processing (including removal). Comparison of modeled aerosol concentrations with observations indicates problems in the models, and perhaps, interpretation of the measurements. For gas phase pollutants such as CO and O{sub 3}, which are relatively well-simulated, the processes contributing most to uncertainties depend on the source region and altitude examined. Uncertainties in the Arctic surface CO response to emissions perturbations are dominated by emissions for East Asian sources, while uncertainties in transport, emissions, and oxidation are comparable for

A combined experimental-modelling method for the detection and analysis of pollution in coastal zones

NASA Astrophysics Data System (ADS)

Limić, Nedzad; Valković, Vladivoj

1996-04-01

Pollution of coastal seas with toxic substances can be efficiently detected by examining toxic materials in sediment samples. These samples contain information on the overall pollution from surrounding sources such as yacht anchorages, nearby industries, sewage systems, etc. In an efficient analysis of pollution one must determine the contribution from each individual source. In this work it is demonstrated that a modelling method can be utilized for solving this latter problem. The modelling method is based on a unique interpretation of concentrations in sediments from all sampling stations. The proposed method is a synthesis consisting of the utilization of PIXE as an efficient method of pollution concentration determination and the code ANCOPOL (N. Limic and R. Benis, The computer code ANCOPOL, SimTel/msdos/geology, 1994 [1]) for the calculation of contributions from the main polluters. The efficiency and limits of the proposed method are demonstrated by discussing trace element concentrations in sediments of Punat Bay on the island of Krk in Croatia.

Mouse models to unravel the role of inhaled pollutants on allergic sensitization and airway inflammation

PubMed Central

2010-01-01

Air pollutant exposure has been linked to a rise in wheezing illnesses. Clinical data highlight that exposure to mainstream tobacco smoke (MS) and environmental tobacco smoke (ETS) as well as exposure to diesel exhaust particles (DEP) could promote allergic sensitization or aggravate symptoms of asthma, suggesting a role for these inhaled pollutants in the pathogenesis of asthma. Mouse models are a valuable tool to study the potential effects of these pollutants in the pathogenesis of asthma, with the opportunity to investigate their impact during processes leading to sensitization, acute inflammation and chronic disease. Mice allow us to perform mechanistic studies and to evaluate the importance of specific cell types in asthma pathogenesis. In this review, the major clinical effects of tobacco smoke and diesel exhaust exposure regarding to asthma development and progression are described. Clinical data are compared with findings from murine models of asthma and inhalable pollutant exposure. Moreover, the potential mechanisms by which both pollutants could aggravate asthma are discussed. PMID:20092634

Impact of exposure time, particle size and uptake pathway on silver nanoparticle effects on circulating immune cells in mytilus galloprovincialis.

PubMed

Bouallegui, Younes; Ben Younes, Ridha; Turki, Faten; Oueslati, Ridha

2017-12-01

Nanomaterials have increasingly emerged as potential pollutants to aquatic organisms. Nanomaterials are known to be taken up by hemocytes of marine invertebrates including Mytilus galloprovincialis. Indeed, assessments of hemocyte-related parameters are a valuable tool in the determination of potentials for nanoparticle (NP) toxicity. The present study assessed the effects from two size types of silver nanoparticles (AgNP: <50 nm and <100 nm) on the frequency of hemocytes subpopulations as immunomodulation biomarkers exposed in a mollusk host. Studies were performed using exposures prior to and after inhibition of potential NP uptake pathways (i.e. clathrin- and caveolae-mediated endocytosis) and over different durations of exposure (3, 6 and 12 h). Differential hemocyte counts (DHC) revealed significant variations in frequency of different immune cells in mussels exposed for 3 hr to either AgNP size. However, as exposure duration progressed cell levels were subsequently differentially altered depending on particle size (i.e. no significant effects after 3 h with larger AgNP). AgNP effects were also delayed/varied after blockade of either clathrin- or caveolae-mediated endocytosis. The results also noted significant negative correlations between changes in levels hyalinocytes and acidophils or in levels basophils and acidophils as a result of AgNP exposure. From these results, we concluded AgNP effects on mussels were size and duration of exposure dependent. This study highlighted how not only was NP size important, but that differing internalization mechanisms could be key factors impacting on the potential for NP in the environment to induce immunomodulation in a model/test sentinel host like M. galloprovincialis.

High-resolution modelling of health impacts and related external cost from air pollution over 36 years using the integrated model system EVA

NASA Astrophysics Data System (ADS)

Brandt, Jørgen; Andersen, Mikael S.; Bønløkke, Jakob; Christensen, Jesper H.; Geels, Camilla; Hansen, Kaj M.; Hertel, Ole; Im, Ulas; Jensen, Steen S.; Ketzel, Matthias; Nielsen, Ole-Kenneth; Plejdrup, Marlene S.; Sigsgaard, Torben

2016-04-01

A high-resolution assessment of health impacts from air pollution and related external cost has been conducted for Denmark using the integrated EVA model system. The EVA system is based on the impact-pathway methodology, where the site-specific emissions will result, via atmospheric transport and chemistry, in a concentration distribution, which together with detailed population data, is used to estimate the population-level exposure. Using exposure-response functions and economic valuations, the exposure is transformed into impacts on human health and related external costs. In this study we have used a coupling of two chemistry transport models to calculate the air pollution concentration at different domain and scales; the Danish Eulerian Hemispheric Model (DEHM) to calculate the air pollution levels in the Northern Hemisphere with a resolution down to 5.6 km x 5.6 km and the Urban Background Model (UBM) to further calculate the air pollution in Denmark at 1 km x 1 km resolution using results from DEHM as boundary conditions. Both the emission data as well as the population density has been represented in the model system with the same high resolution. Previous health impact assessments related to air pollution have been made on a lower resolution. In this study, the integrated model system, EVA, has been used to estimate the health impacts and related external cost for Denmark at a 1 km x 1 km resolution. New developments of the integrated model system will be presented as well as the development of health impacts and related external costs in Europe and Denmark over a period of 36 years (1979-2014). Acknowledgements This work was funded by: DCE - National Centre for Environment and Energy. Project: "Health impacts and external costs from air pollution in Denmark over 25 years" and NordForsk under the Nordic Programme on Health and Welfare. Project: "Understanding the link between air pollution and distribution of related health impacts and welfare in the

Predicting changes of glass optical properties in polluted atmospheric environment by a neural network model

NASA Astrophysics Data System (ADS)

Verney-Carron, A.; Dutot, A. L.; Lombardo, T.; Chabas, A.

2012-07-01

Soiling results from the deposition of pollutants on materials. On glass, it leads to an alteration of its intrinsic optical properties. The nature and intensity of this phenomenon mirrors the pollution of an environment. This paper proposes a new statistical model in order to predict the evolution of haze (H) (i.e. diffuse/direct transmitted light ratio) as a function of time and major pollutant concentrations in the atmosphere (SO2, NO2, and PM10 (Particulate Matter < 10 μm)). The model was parameterized by using a large set of data collected in European cities (especially, Paris and its suburbs, Athens, Krakow, Prague, and Rome) during field exposure campaigns (French, European, and international programs). This statistical model, called NEUROPT-Glass, comes from an artificial neural network with two hidden layers and uses a non-linear parametric regression named Multilayer Perceptron (MLP). The results display a high determination coefficient (R2 = 0.88) between the measured and the predicted hazes and minimizes the dispersion of data compared to existing multilinear dose-response functions. Therefore, this model can be used with a great confidence in order to predict the soiling of glass as a function of time in world cities with different levels of pollution or to assess the effect of pollution reduction policies on glass soiling problems in urban environments.

A review of AirQ Models and their applications for forecasting the air pollution health outcomes.

PubMed

Oliveri Conti, Gea; Heibati, Behzad; Kloog, Itai; Fiore, Maria; Ferrante, Margherita

2017-03-01

Even though clean air is considered as a basic requirement for the maintenance of human health, air pollution continues to pose a significant health threat in developed and developing countries alike. Monitoring and modeling of classic and emerging pollutants is vital to our knowledge of health outcomes in exposed subjects and to our ability to predict them. The ability to anticipate and manage changes in atmospheric pollutant concentrations relies on an accurate representation of the chemical state of the atmosphere. The task of providing the best possible analysis of air pollution thus requires efficient computational tools enabling efficient integration of observational data into models. A number of air quality models have been developed and play an important role in air quality management. Even though a large number of air quality models have been discussed or applied, their heterogeneity makes it difficult to select one approach above the others. This paper provides a brief review on air quality models with respect to several aspects such as prediction of health effects.

Predictive modelling of the dielectric response of plasmonic substrates: application to the interpretation of ellipsometric spectra

NASA Astrophysics Data System (ADS)

Pugliara, A.; Bayle, M.; Bonafos, C.; Carles, R.; Respaud, M.; Makasheva, K.

2018-03-01

A predictive modelling of plasmonic substrates appropriate to read ellipsometric spectra is presented in this work. We focus on plasmonic substrates containing a single layer of silver nanoparticles (AgNPs) embedded in silica matrices. The model uses the Abeles matrix formalism and is based on the quasistatic approximation of the classical Maxwell-Garnett mixing rule, however accounting for the electronic confinement effect through the damping parameter. It is applied on samples elaborated by: (i) RF-diode sputtering followed by Plasma Enhanced Chemical Vapor Deposition (PECVD) and (ii) Low Energy Ion Beam Synthesis (LE-IBS), and represents situations with increasing degree of complexity that can be accounted for by the model. It allows extraction of the main characteristics of the AgNPs population: average size, volume fraction and distance of the AgNPs layer from the matrix free surface. Model validation is achieved through comparison with results obtained from transmission electron microscopy approving for its applicability. The advantages and limitations of the proposed model are discussed after eccentricity-based statistical analysis along with further developments related to the quality of comparison between the model-generated spectra and the experimentally-recorded ellipsometric spectra.

Electrostatic Assemblies of Well-Dispersed AgNPs on the Surface of Electrospun Nanofibers as Highly Active SERS Substrates for Wide-Range pH Sensing.

PubMed

Yang, Tong; Ma, Jun; Zhen, Shu Jun; Huang, Cheng Zhi

2016-06-15

Surface-enhanced Raman scattering (SERS) has shown high promise in analysis and bioanalysis, wherein noble metal nanoparticles (NMNPs) such as silver nanoparticles were employed as substrates because of their strong localized surface plasmon resonance (LSPR) properties. However, SERS-based pH sensing was restricted because of the aggregation of NMNPs in acidic medium or biosamples with high ionic strength. Herein, by using the electrostatic interaction as a driving force, AgNPs are assembled on the surface of ethylene imine polymer (PEI)/poly(vinyl alcohol) (PVA) electrospun nanofibers, which are then applied as highly sensitive and reproducible SERS substrate with an enhancement factor (EF) of 10(7)-10(8). When p-aminothiophenol (p-ATP) is used as an indicator with its b2 mode, a good and wide linear response to pH ranging from 2.56 to 11.20 could be available, and the as-prepared nanocomposite fibers then could be fabricated as excellent pH sensors in complicated biological samples such as urine, considering that the pH of urine could reflect the acid-base status of a person. This work not only emerges a cost-effective, direct, and convenient approach to homogeneously decorate AgNPs on the surface of polymer nanofibers but also supplies a route for preparing other noble metal nanofibrous sensing membranes.

Explaining nitrate pollution pressure on the groundwater resource in Kinshasa using a multivariate statistical modelling approach

NASA Astrophysics Data System (ADS)

Mfumu Kihumba, Antoine; Vanclooster, Marnik

2013-04-01

Drinking water in Kinshasa, the capital of the Democratic Republic of Congo, is provided by extracting groundwater from the local aquifer, particularly in peripheral areas. The exploited groundwater body is mainly unconfined and located within a continuous detrital aquifer, primarily composed of sedimentary formations. However, the aquifer is subjected to an increasing threat of anthropogenic pollution pressure. Understanding the detailed origin of this pollution pressure is important for sustainable drinking water management in Kinshasa. The present study aims to explain the observed nitrate pollution problem, nitrate being considered as a good tracer for other pollution threats. The analysis is made in terms of physical attributes that are readily available using a statistical modelling approach. For the nitrate data, use was made of a historical groundwater quality assessment study, for which the data were re-analysed. The physical attributes are related to the topography, land use, geology and hydrogeology of the region. Prior to the statistical modelling, intrinsic and specific vulnerability for nitrate pollution was assessed. This vulnerability assessment showed that the alluvium area in the northern part of the region is the most vulnerable area. This area consists of urban land use with poor sanitation. Re-analysis of the nitrate pollution data demonstrated that the spatial variability of nitrate concentrations in the groundwater body is high, and coherent with the fragmented land use of the region and the intrinsic and specific vulnerability maps. For the statistical modeling use was made of multiple regression and regression tree analysis. The results demonstrated the significant impact of land use variables on the Kinshasa groundwater nitrate pollution and the need for a detailed delineation of groundwater capture zones around the monitoring stations. Key words: Groundwater , Isotopic, Kinshasa, Modelling, Pollution, Physico-chemical.

Modeling of storm runoff and pollutant wash off processes during storm event in rapidly urbanizing catchment

NASA Astrophysics Data System (ADS)

Qin, H. P.; Yu, X. Y.; Khu, S. T.

2009-04-01

Many urban catchments in developing countries are undergoing fast economic growth, population expansion and land use/cover change. Due to the mixture of agricultural/industrial/residential land use or different urbanization level as well as lack of historical monitoring data in the developing area, storm-water runoff pollution modeling is faced with challenges of considerable spatial variations and data insufficiency. Shiyan Reservoir catchment is located in the rapidly urbanizing coastal region of Southeast China. It has six sub-catchments with largely different land use patterns and urbanization levels. A simple semi-distributed model was used to simulate the storm-water runoff pollution process during storm event in the catchment. The model adopted modified IHACRES model and exponential wash-off functions to describe storm-runoff and pollutant wash-off processes, respectively, in each of six sub-catchments. Temporary hydrological and water quality monitoring sites were set at the downstream section of each sub-catchment in Feb-May 2007, spanning non-rain and rain seasons. And the model was calibrated for storm-runoff and water quality data during two typical storm events with rainfall amount of 10mm/4hr and 73mm/5hr, respectively. The results indicated that the Nash-Sutcliffe (NS) coefficients are greater than 0.65 and 0.55 respectively for storm-runoff model calibration and validation. However although NS coefficients can reach 0.7~0.9 for pollutant wash-off model calibration based on measured data in each storm event, the simulation data can not fit well with the measured data in model validation. According to field survey observation, many litters and residuals were found to distribute in disorder in some sub-catchments or their drainage systems and to instantaneously wash off into the surface water when the rainfall amount and intensity are large enough. In order to improve storm-water runoff pollution simulation in the catchment, the variations of pollutant

Development of a distributed air pollutant dry deposition modeling framework.

PubMed

Hirabayashi, Satoshi; Kroll, Charles N; Nowak, David J

2012-12-01

A distributed air pollutant dry deposition modeling system was developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry deposition of carbon monoxide (CO), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), and particulate matter less than 10 microns (PM10) to trees can be spatially quantified. Employing nationally available road network, traffic volume, air pollutant emission/measurement and meteorological data, the developed system provides a framework for the U.S. city managers to identify spatial patterns of urban forest and locate potential areas for future urban forest planting and protection to improve air quality. To exhibit the usability of the framework, a case study was performed for July and August of 2005 in Baltimore, MD. Copyright © 2012 Elsevier Ltd. All rights reserved.

The NLS-Based Nonlinear Grey Multivariate Model for Forecasting Pollutant Emissions in China

PubMed Central

Pei, Ling-Ling; Li, Qin

2018-01-01

The relationship between pollutant discharge and economic growth has been a major research focus in environmental economics. To accurately estimate the nonlinear change law of China’s pollutant discharge with economic growth, this study establishes a transformed nonlinear grey multivariable (TNGM (1, N)) model based on the nonlinear least square (NLS) method. The Gauss–Seidel iterative algorithm was used to solve the parameters of the TNGM (1, N) model based on the NLS basic principle. This algorithm improves the precision of the model by continuous iteration and constantly approximating the optimal regression coefficient of the nonlinear model. In our empirical analysis, the traditional grey multivariate model GM (1, N) and the NLS-based TNGM (1, N) models were respectively adopted to forecast and analyze the relationship among wastewater discharge per capita (WDPC), and per capita emissions of SO2 and dust, alongside GDP per capita in China during the period 1996–2015. Results indicated that the NLS algorithm is able to effectively help the grey multivariable model identify the nonlinear relationship between pollutant discharge and economic growth. The results show that the NLS-based TNGM (1, N) model presents greater precision when forecasting WDPC, SO2 emissions and dust emissions per capita, compared to the traditional GM (1, N) model; WDPC indicates a growing tendency aligned with the growth of GDP, while the per capita emissions of SO2 and dust reduce accordingly. PMID:29517985

Bioinspired anchoring AgNPs onto micro-nanoporous TiO2 orthopedic coatings: Trap-killing of bacteria, surface-regulated osteoblast functions and host responses.

PubMed

Jia, Zhaojun; Xiu, Peng; Li, Ming; Xu, Xuchen; Shi, Yuying; Cheng, Yan; Wei, Shicheng; Zheng, Yufeng; Xi, Tingfei; Cai, Hong; Liu, Zhongjun

2016-01-01

The therapeutic applications of silver nanoparticles (AgNPs) against biomedical device-associated infections (BAI), by local delivery, are encountered with risks of detachment, instability and nanotoxicity in physiological milieus. To firmly anchor AgNPs onto modified biomaterial surfaces through tight physicochemical interactions would potentially relieve these concerns. Herein, we present a strategy for hierarchical TiO2/Ag coating, in an attempt to endow medical titanium (Ti) with anticorrosion and antibacterial properties whilst maintaining normal biological functions. In brief, by harnessing the adhesion and reactivity of bioinspired polydopamine, silver nanoparticles were easily immobilized onto peripheral surface and incorporated into interior cavity of a micro/nanoporous TiO2 ceramic coating in situ grown from template Ti. The resulting coating protected the substrate well from corrosion and gave a sustained release of Ag(+) up to 28 d. An interesting germicidal effect, termed "trap-killing", was observed against Staphylococcus aureus strain. The multiple osteoblast responses, i.e. adherence, spreading, proliferation, and differentiation, were retained normal or promoted, via a putative surface-initiated self-regulation mechanism. After subcutaneous implantation for a month, the coated specimens elicited minimal, comparable inflammatory responses relative to the control. Moreover, this simple and safe functionalization strategy manifested a good degree of flexibility towards three-dimensional sophisticated objects. Expectedly, it can become a prospective bench to bedside solution to current challenges facing orthopedics. Copyright © 2015 Elsevier Ltd. All rights reserved.

Radioactive Pollution Estimate for Fukushima Nuclear Power Plant by a Particle Model

NASA Astrophysics Data System (ADS)

Saito, Keisuke; Ogawa, Susumu

2016-06-01

On Mar 12, 2011, very wide radioactive pollution occurred by a hydrogen explosion in Fukushima Nuclear Power Plant. A large amount of radioisotopes started with four times of explosions. With traditional atmospheric diffusion models could not reconstruct radioactive pollution in Fukushima. Then, with a particle model, this accident was reconstructed from meteorological archive and Radar- AMeDAS. Calculations with the particle model were carried out for Mar 12, 15, 18 and 20 when east southeast winds blew for five hours continuously. Meteorological archive is expressed by wind speeds and directions in five-km grid every hour with eight classes of height till 3000 m. Radar- AMeDAS is precipitation data in one-km grid every thirty minutes. Particles are ten scales of 0.01 to 0.1 mm in diameter with specific weight of 2.65 and vertical speeds given by Stokes equation. But, on Mar 15, it rained from 16:30 and then the particles fell down at a moment as wet deposit in calculation. On the other hand, the altitudes on the ground were given by DEM with 1 km-grid. The spatial dose by emitted radioisotopes was referred to the observation data at monitoring posts of Tokyo Electric Power Company. The falling points of radioisotopes were expressed on the map using the particle model. As a result, the same distributions were obtained as the surface spatial dose of radioisotopes in aero-monitoring by Ministry of Education, Culture, Sports, Science and Technology. Especially, on Mar 15, the simulated pollution fitted to the observation, which extended to the northwest of Fukushima Daiichi Nuclear Power Plant and caused mainly sever pollution. By the particle model, the falling positions on the ground were estimated each particle size. Particles with more than 0.05 mm of size were affected by the topography and blocked by the mountains with the altitudes of more than 700 m. The particle model does not include the atmospheric stability, the source height, and deposit speeds. The

Modeling and evaluation of urban pollution events of atmospheric heavy metals from a large Cu-smelter.

PubMed

Chen, Bing; Stein, Ariel F; Castell, Nuria; Gonzalez-Castanedo, Yolanda; Sanchez de la Campa, A M; de la Rosa, J D

2016-01-01

Metal smelting and processing are highly polluting activities that have a strong influence on the levels of heavy metals in air, soil, and crops. We employ an atmospheric transport and dispersion model to predict the pollution levels originated from the second largest Cu-smelter in Europe. The model predicts that the concentrations of copper (Cu), zinc (Zn), and arsenic (As) in an urban area close to the Cu-smelter can reach 170, 70, and 30 ng m−3, respectively. The model captures all the observed urban pollution events, but the magnitude of the elemental concentrations is predicted to be lower than that of the observed values; ~300, ~500, and ~100 ng m−3 for Cu, Zn, and As, respectively. The comparison between model and observations showed an average correlation coefficient of 0.62 ± 0.13. The simulation shows that the transport of heavy metals reaches a peak in the afternoon over the urban area. The under-prediction in the peak is explained by the simulated stronger winds compared with monitoring data. The stronger simulated winds enhance the transport and dispersion of heavy metals to the regional area, diminishing the impact of pollution events in the urban area. This model, driven by high resolution meteorology (2 km in horizontal), predicts the hourly-interval evolutions of atmospheric heavy metal pollutions in the close by urban area of industrial hotspot.

INITIAL APPL;ICATION OF THE ADAPTIVE GRID AIR POLLUTION MODEL

EPA Science Inventory

The paper discusses an adaptive-grid algorithm used in air pollution models. The algorithm reduces errors related to insufficient grid resolution by automatically refining the grid scales in regions of high interest. Meanwhile the grid scales are coarsened in other parts of the d...

Characterization Urban Heat Island Effect and Modelling of Secondary Pollutant Formations at Urban Hotspots

NASA Astrophysics Data System (ADS)

Undi, G. S. N. V. K. S. N. S.

2017-12-01

More than 60 percent of the world population is living the urban zones by 2020. This socio of economic transformations will bring considerable changes to the ambient atmosphere. More than 70 percent of the air pollutants in the urban hotspots are from vehicular emissions. in the urban hotspots. In the urban hotspots, the meteorological and dispersion conditions will have different characteristics than in surrounding rural areas. Reactive pollutants transformations are drastically influenced by the local meteorological conditions. The complexity of urban structure alters the pollutants dispersion in the hotspots. This relationship between urban meteorology and air pollution is an important aspect of consideration. In the atmosphere, drastic changes have been noticed from micro to regional and global scales. However, the characteristics of air pollutant emissions vary with time and space, favorable dispersion conditions transport them from local to regional scale. In the present study, the impact of land cover change on Urban Heat Island effect (UHI) has been characterized by considering the three different zones with varying land use patterns. An attempt has been made to estimate the impact of UHI on secondary pollutants (O3) transformations. Envi-Met model has been used to characterize the UHI intensity for the selected zones. Meteorological and air quality measurements were carried out at the selected locations. The diurnal variations of Ozone (O3) concentration for three zones are correlated with the UHI intensity. And the monitoring and model results of O3 concentrations are in good agreement. It is observed from the obtained model results that the metrological parameters influence on local air quality is significant in urban zones.

Adaptive hierarchical grid model of water-borne pollutant dispersion

NASA Astrophysics Data System (ADS)

Borthwick, A. G. L.; Marchant, R. D.; Copeland, G. J. M.

Water pollution by industrial and agricultural waste is an increasingly major public health issue. It is therefore important for water engineers and managers to be able to predict accurately the local behaviour of water-borne pollutants. This paper describes the novel and efficient coupling of dynamically adaptive hierarchical grids with standard solvers of the advection-diffusion equation. Adaptive quadtree grids are able to focus on regions of interest such as pollutant fronts, while retaining economy in the total number of grid elements through selective grid refinement. Advection is treated using Lagrangian particle tracking. Diffusion is solved separately using two grid-based methods; one is by explicit finite differences, the other a diffusion-velocity approach. Results are given in two dimensions for pure diffusion of an initially Gaussian plume, advection-diffusion of the Gaussian plume in the rotating flow field of a forced vortex, and the transport of species in a rectangular channel with side wall boundary layers. Close agreement is achieved with analytical solutions of the advection-diffusion equation and simulations from a Lagrangian random walk model. An application to Sepetiba Bay, Brazil is included to demonstrate the method with complex flows and topography.

Air pollution exposure prediction approaches used in air pollution epidemiology studies.

PubMed

Özkaynak, Halûk; Baxter, Lisa K; Dionisio, Kathie L; Burke, Janet

2013-01-01

Epidemiological studies of the health effects of outdoor air pollution have traditionally relied upon surrogates of personal exposures, most commonly ambient concentration measurements from central-site monitors. However, this approach may introduce exposure prediction errors and misclassification of exposures for pollutants that are spatially heterogeneous, such as those associated with traffic emissions (e.g., carbon monoxide, elemental carbon, nitrogen oxides, and particulate matter). We review alternative air quality and human exposure metrics applied in recent air pollution health effect studies discussed during the International Society of Exposure Science 2011 conference in Baltimore, MD. Symposium presenters considered various alternative exposure metrics, including: central site or interpolated monitoring data, regional pollution levels predicted using the national scale Community Multiscale Air Quality model or from measurements combined with local-scale (AERMOD) air quality models, hybrid models that include satellite data, statistically blended modeling and measurement data, concentrations adjusted by home infiltration rates, and population-based human exposure model (Stochastic Human Exposure and Dose Simulation, and Air Pollutants Exposure models) predictions. These alternative exposure metrics were applied in epidemiological applications to health outcomes, including daily mortality and respiratory hospital admissions, daily hospital emergency department visits, daily myocardial infarctions, and daily adverse birth outcomes. This paper summarizes the research projects presented during the symposium, with full details of the work presented in individual papers in this journal issue.

Statistics of concentrations due to single air pollution sources to be applied in numerical modelling of pollutant dispersion

NASA Astrophysics Data System (ADS)

Tumanov, Sergiu

A test of goodness of fit based on rank statistics was applied to prove the applicability of the Eggenberger-Polya discrete probability law to hourly SO 2-concentrations measured in the vicinity of single sources. With this end in view, the pollutant concentration was considered an integral quantity which may be accepted if one properly chooses the unit of measurement (in this case μg m -3) and if account is taken of the limited accuracy of measurements. The results of the test being satisfactory, even in the range of upper quantiles, the Eggenberger-Polya law was used in association with numerical modelling to estimate statistical parameters, e.g. quantiles, cumulative probabilities of threshold concentrations to be exceeded, and so on, in the grid points of a network covering the area of interest. This only needs accurate estimations of means and variances of the concentration series which can readily be obtained through routine air pollution dispersion modelling.

A robust sebum, oil, and particulate pollution model for assessing cleansing efficacy of human skin.

PubMed

Peterson, G; Rapaka, S; Koski, N; Kearney, M; Ortblad, K; Tadlock, L

2017-06-01

With increasing concerns over the rise of atmospheric particulate pollution globally and its impact on systemic health and skin ageing, we have developed a pollution model to mimic particulate matter trapped in sebum and oils creating a robust (difficult to remove) surrogate for dirty, polluted skin. To evaluate the cleansing efficacy/protective effect of a sonic brush vs. manual cleansing against particulate pollution (trapped in grease/oil typical of human sebum). The pollution model (Sebollution; sebum pollution model; SPM) consists of atmospheric particulate matter/pollution combined with grease/oils typical of human sebum. Twenty subjects between the ages of 18-65 were enrolled in a single-centre, cleansing study comparisons between the sonic cleansing brush (normal speed) compared to manual cleansing. Equal amount of SPM was applied to the centre of each cheek (left and right). Method of cleansing (sonic vs. manual) was randomized to the side of the face (left or right) for each subject. Each side was cleansed for five-seconds using the sonic cleansing device with sensitive brush head or manually, using equal amounts of water and a gel cleanser. Photographs (VISIA-CR, Canfield Imaging, NJ, USA) were taken at baseline (before application of the SPM), after application of SPM (pre-cleansing), and following cleansing. Image analysis (ImageJ, NIH, Bethesda, MD, USA) was used to quantify colour intensity (amount of particulate pollutants on the skin) using a scale of 0 to 255 (0 = all black pixels; 255 = all white pixels). Differences between the baseline and post-cleansing values (pixels) are reported as the amount of SPM remaining following each method of cleansing. Using a robust cleansing protocol to assess removal of pollutants (SPM; atmospheric particulate matter trapped in grease/oil), the sonic brush removed significantly more SPM than manual cleansing (P < 0.001). While extreme in colour, this pollution method easily allows assessment of efficacy through

Modeling the Impact of Arctic Shipping Pollution on Air Quality off the Coast of Northern Norway

NASA Astrophysics Data System (ADS)

Thomas, J. L.; Law, K.; Marelle, L.; Raut, J.; Jalkanen, J.; Johansson, L.; Roiger, A.; Schlager, H.; Kim, J.; Reiter, A.; Weinzierl, B.; Rose, M.; Fast, J. D.

2013-12-01

As the Arctic is undergoing rapid and potentially irreversible changes, such as the shrinking and thinning of sea-ice cover, the levels of atmospheric pollution are expected to rise dramatically due to the emergence of local pollution sources including shipping. Shipping routes through the Arctic (such as Russia's Northern Sea Route) are already used as an alternative to the traditional global transit shipping routes. In summer 2012, the ACCESS (Arctic Climate Change, Economy, and Society) aircraft campaign focused on studying pollution sources off the coast of northern Norway to quantify emissions from shipping and other anthropogenic pollution sources. To complement these measurements, a regional chemical transport model is used to study the impact of shipping pollution on gas and aerosol concentrations in the region. WRF-Chem (The Weather Research and Forecasting Model with Chemistry, which simulates gas and aerosols simultaneously with meteorology) is run with real time shipping emissions from STEAM (Ship Traffic Emission Assessment Model) for July 2012. The STEAM model calculates gas and aerosol emissions of marine traffic based on the ship type and location provided by the Automatic Identification System (AIS). Use of real time position, speed, and ship specific information allows for development of emissions with very high spatial (1x1 km) and temporal (30 min) resolution, which are used in the regional model runs. STEAM emissions have been specifically generated for shipping off the coast of Norway during the entire ACCESS campaign period. Simulated ship plumes from high-resolution model runs are compared to aircraft measurements. The regional impact of current summertime shipping is also examined. At present, relatively light ship traffic off the coast of northern Norway results in only a small impact of shipping pollution on regional atmospheric chemistry. The impact of increased future shipping on regional atmospheric chemistry is also assessed.

Modelling of light pollution in suburban areas using remotely sensed imagery and GIS.

PubMed

Chalkias, C; Petrakis, M; Psiloglou, B; Lianou, M

2006-04-01

This paper describes a methodology for modelling light pollution using geographical information systems (GIS) and remote sensing (RS) technology. The proposed approach attempts to address the issue of environmental assessment in sensitive suburban areas. The modern way of life in developing countries is conductive to environmental degradation in urban and suburban areas. One specific parameter for this degradation is light pollution due to intense artificial night lighting. This paper aims to assess this parameter for the Athens metropolitan area, using modern analytical and data capturing technologies. For this purpose, night-time satellite images and analogue maps have been used in order to create the spatial database of the GIS for the study area. Using GIS advanced analytical functionality, visibility analysis was implemented. The outputs for this analysis are a series of maps reflecting direct and indirect light pollution around the city of Athens. Direct light pollution corresponds to optical contact with artificial night light sources, while indirect light pollution corresponds to optical contact with the sky glow above the city. Additionally, the assessment of light pollution in different periods allows for dynamic evaluation of the phenomenon. The case study demonstrates high levels of light pollution in Athens suburban areas and its increase over the last decade.

The probability distribution model of air pollution index and its dominants in Kuala Lumpur

NASA Astrophysics Data System (ADS)

AL-Dhurafi, Nasr Ahmed; Razali, Ahmad Mahir; Masseran, Nurulkamal; Zamzuri, Zamira Hasanah

2016-11-01

This paper focuses on the statistical modeling for the distributions of air pollution index (API) and its sub-indexes data observed at Kuala Lumpur in Malaysia. Five pollutants or sub-indexes are measured including, carbon monoxide (CO); sulphur dioxide (SO2); nitrogen dioxide (NO2), and; particulate matter (PM10). Four probability distributions are considered, namely log-normal, exponential, Gamma and Weibull in search for the best fit distribution to the Malaysian air pollutants data. In order to determine the best distribution for describing the air pollutants data, five goodness-of-fit criteria's are applied. This will help in minimizing the uncertainty in pollution resource estimates and improving the assessment phase of planning. The conflict in criterion results for selecting the best distribution was overcome by using the weight of ranks method. We found that the Gamma distribution is the best distribution for the majority of air pollutants data in Kuala Lumpur.

Spatial-temporal modeling of the association between air pollution exposure and preterm birth: identifying critical windows of exposure.

PubMed

Warren, Joshua; Fuentes, Montserrat; Herring, Amy; Langlois, Peter

2012-12-01

Exposure to high levels of air pollution during the pregnancy is associated with increased probability of preterm birth (PTB), a major cause of infant morbidity and mortality. New statistical methodology is required to specifically determine when a particular pollutant impacts the PTB outcome, to determine the role of different pollutants, and to characterize the spatial variability in these results. We develop a new Bayesian spatial model for PTB which identifies susceptible windows throughout the pregnancy jointly for multiple pollutants (PM(2.5) , ozone) while allowing these windows to vary continuously across space and time. We geo-code vital record birth data from Texas (2002-2004) and link them with standard pollution monitoring data and a newly introduced EPA product of calibrated air pollution model output. We apply the fully spatial model to a region of 13 counties in eastern Texas consisting of highly urban as well as rural areas. Our results indicate significant signal in the first two trimesters of pregnancy with different pollutants leading to different critical windows. Introducing the spatial aspect uncovers critical windows previously unidentified when space is ignored. A proper inference procedure is introduced to correctly analyze these windows. © 2012, The International Biometric Society.

Modeling Regional Pollution Episodes With The Ctm Mocage.

NASA Astrophysics Data System (ADS)

Dufour, A.; Brocheton, F.; Amodei, M.; Peuch, V.-H.

Several regional ozone pollution episodes have been studied in the context of two recent extensive field campaigns in France: ESQUIF, in the Paris region and ES- COMPTE, in the vicinity of Marseilles. MOCAGE is an off-line multi-scale Chem- istry and Transport Model (CTM), driven by the operational numerical weather pre- diction models of Météo-France, ARPEGE and ALADIN. It covers from the global to the regional scale, by means of up to four levels of nested domains, and extends up to the middle stratosphere; thus, there is no need for external boundary conditions, neither on the horizontal or on the vertical. These original features allows to cover with MOCAGE a wide range of scientific applications, from routine air-pollution fore- casts to long-term simulations related to climate issues. The present study focuses on the simulation of regional-scale photo-oxidant episodes and on the impact on larger scales of the transport of ozone, of precursors and of reservoir species. The first ex- ample concerns a polluted episode of the ESQUIF campaign (IOP6). In addition to ground measurements, 8 flights have documented the situation, showing a diversity of chemical regimes. This variability is quite satisfactorily reproduced by the model. A special attention was also paid to vertical and horizontal exchanges, particularly to interactions between the boundary layer and the free troposphere. An interesting case of an ill-represented residual nocturnal plume in the simulation of ESQUIF IOP5 will be presented: during this IOP, the vertical structure of the lower troposphere was well characterized by four flights. Free troposphere concentrations of ozone appear to be well reproduced by the model, except for the intensity and vertical extent of a residual plume, which are overestimated. For the day after, in addition to a direct impact on surface concentrations, the simulated development of the boundary layer is found to be too slow ; both errors contribute to an

Receptor model-based source apportionment of particulate pollution in Hyderabad, India.

PubMed

Guttikunda, Sarath K; Kopakka, Ramani V; Dasari, Prasad; Gertler, Alan W

2013-07-01

Air quality in Hyderabad, India, often exceeds the national ambient air quality standards, especially for particulate matter (PM), which, in 2010, averaged 82.2 ± 24.6, 96.2 ± 12.1, and 64.3 ± 21.2 μg/m(3) of PM10, at commercial, industrial, and residential monitoring stations, respectively, exceeding the national ambient standard of 60 μg/m(3). In 2005, following an ordinance passed by the Supreme Court of India, a source apportionment study was conducted to quantify source contributions to PM pollution in Hyderabad, using the chemical mass balance (version 8.2) receptor model for 180 ambient samples collected at three stations for PM10 and PM2.5 size fractions for three seasons. The receptor modeling results indicated that the PM10 pollution is dominated by the direct vehicular exhaust and road dust (more than 60%). PM2.5 with higher propensity to enter the human respiratory tracks, has mixed sources of vehicle exhaust, industrial coal combustion, garbage burning, and secondary PM. In order to improve the air quality in the city, these findings demonstrate the need to control emissions from all known sources and particularly focus on the low-hanging fruits like road dust and waste burning, while the technological and institutional advancements in the transport and industrial sectors are bound to enhance efficiencies. Andhra Pradesh Pollution Control Board utilized these results to prepare an air pollution control action plan for the city.

Globalizing Air Pollution

NASA Astrophysics Data System (ADS)

Lin, J.

2017-12-01

Recent studies have revealed the issue of globalizing air pollution through complex coupling of atmospheric transport (physical route) and economic trade (socioeconomic route). Recognition of such globalizing air pollution has important implications for understanding the impacts of regional and global consumption (of goods and services) on air quality, public health, climate and the ecosystems. And addressing these questions often requires improved modeling, measurements and economic-emission statistics. This talk will introduce the concept and mechanism of globalizing air pollution, with following demonstrations based on recent works on modeling, satellite measurement and multi-disciplinary assessment.

Model studies of laser absorption computed tomography for remote air pollution measurement

NASA Technical Reports Server (NTRS)

Wolfe, D. C., Jr.; Byer, R. L.

1982-01-01

Model studies of the potential of laser absorption-computed tomography are presented which demonstrate the possibility of sensitive remote atmospheric pollutant measurements, over kilometer-sized areas, with two-dimensional resolution, at modest laser source powers. An analysis of this tomographic reconstruction process as a function of measurement SNR, laser power, range, and system geometry, shows that the system is able to yield two-dimensional maps of pollutant concentrations at ranges and resolutions superior to those attainable with existing, direct-detection laser radars.

Global Land Use Regression Model for Nitrogen Dioxide Air Pollution.

PubMed

Larkin, Andrew; Geddes, Jeffrey A; Martin, Randall V; Xiao, Qingyang; Liu, Yang; Marshall, Julian D; Brauer, Michael; Hystad, Perry

2017-06-20

Nitrogen dioxide is a common air pollutant with growing evidence of health impacts independent of other common pollutants such as ozone and particulate matter. However, the worldwide distribution of NO 2 exposure and associated impacts on health is still largely uncertain. To advance global exposure estimates we created a global nitrogen dioxide (NO 2 ) land use regression model for 2011 using annual measurements from 5,220 air monitors in 58 countries. The model captured 54% of global NO 2 variation, with a mean absolute error of 3.7 ppb. Regional performance varied from R 2 = 0.42 (Africa) to 0.67 (South America). Repeated 10% cross-validation using bootstrap sampling (n = 10,000) demonstrated a robust performance with respect to air monitor sampling in North America, Europe, and Asia (adjusted R 2 within 2%) but not for Africa and Oceania (adjusted R 2 within 11%) where NO 2 monitoring data are sparse. The final model included 10 variables that captured both between and within-city spatial gradients in NO 2 concentrations. Variable contributions differed between continental regions, but major roads within 100 m and satellite-derived NO 2 were consistently the strongest predictors. The resulting model can be used for global risk assessments and health studies, particularly in countries without existing NO 2 monitoring data or models.

Interaction of pollution abatement with world dynamics

NASA Technical Reports Server (NTRS)

Smith, G. L.

1973-01-01

The world dynamics model of Jay W. Forrester was modified to account for pollution abatement. In the modified model, it is assumed that as pollution increases, efforts are made to control pollution. There is a competition between food supply, material standard of living, and pollution abatement for capital, and time is required for diversion of capital toward pollution abatement. Inclusion of pollution abatement in the model drastically alters the response of the world system for the case in which depletion of natural resources is not considered. Instead of undergoing a pollution catastrophe, all system levels move more or less smoothly toward an equilibrium. A FORTRAN program listing of the modified world dynamics model is included.

A vegetation modeling concept for Building and Environmental Aerodynamics wind tunnel tests and its application in pollutant dispersion studies.

PubMed

Gromke, Christof

2011-01-01

A new vegetation modeling concept for Building and Environmental Aerodynamics wind tunnel investigations was developed. The modeling concept is based on fluid dynamical similarity aspects and allows the small-scale modeling of various kinds of vegetation, e.g. field crops, shrubs, hedges, single trees and forest stands. The applicability of the modeling concept was validated in wind tunnel pollutant dispersion studies. Avenue trees in urban street canyons were modeled and their implications on traffic pollutant dispersion were investigated. The dispersion experiments proved the modeling concept to be practicable for wind tunnel studies and suggested to provide reliable concentration results. Unfavorable effects of trees on pollutant dispersion and natural ventilation in street canyons were revealed. Increased traffic pollutant concentrations were found in comparison to the tree-free reference case. Copyright © 2010 Elsevier Ltd. All rights reserved.

Development of model for prediction of Leachate Pollution Index (LPI) in absence of leachate parameters.

PubMed

Lothe, Anjali G; Sinha, Alok

2017-05-01

Leachate pollution index (LPI) is an environmental index which quantifies the pollution potential of leachate generated in landfill site. Calculation of Leachate pollution index (LPI) is based on concentration of 18 parameters present in leachate. However, in case of non-availability of all 18 parameters evaluation of actual values of LPI becomes difficult. In this study, a model has been developed to predict the actual values of LPI in case of partial availability of parameters. This model generates eleven equations that helps in determination of upper and lower limit of LPI. The geometric mean of these two values results in LPI value. Application of this model to three landfill site results in LPI value with an error of ±20% for ∑ i n w i ⩾0.6. Copyright © 2016 Elsevier Ltd. All rights reserved.

The relationship between odour annoyance scores and modelled ambient air pollution in Sarnia, "Chemical Valley", Ontario.

PubMed

Atari, Dominic Odwa; Luginaah, Isaac N; Fung, Karen

2009-10-01

This study aimed at establishing the relationship between annoyance scores and modelled air pollution in "Chemical Valley", Sarnia, Ontario (Canada). Annoyance scores were taken from a community health survey (N = 774); and respondents' exposure to nitrogen dioxide (NO(2)) and sulphur dioxide (SO(2)) were estimated using land use regression (LUR) models. The associations were examined by univariate analysis while multivariate logistic regression was used to examine the determinants of odour annoyance. The results showed that odour annoyance was significantly correlated to modelled pollutants at the individual (NO(2), r = 0.15; SO(2), r = 0.13) and census tract (NO(2), r = 0.56; SO(2), r = 0.67) levels. The exposure-response relationships show that residents of Sarnia react to very low pollution concentrations levels even if they are within the Ontario ambient air quality criteria. The study found that exposure to high NO(2) and SO(2) concentrations, gender, and perception of health effects were significant determinants of individual odour annoyance reporting. The observed association between odour annoyance and modelled ambient pollution suggest that individual and census tract level annoyance scores may serve as proxies for air quality in exposed communities because they capture the within area spatial variability of pollution. However, questionnaire-based odour annoyance scores need to be validated longitudinally and across different scales if they are to be adopted for use at the national level.

Accounting for spatial effects in land use regression for urban air pollution modeling.

PubMed

Bertazzon, Stefania; Johnson, Markey; Eccles, Kristin; Kaplan, Gilaad G

2015-01-01

In order to accurately assess air pollution risks, health studies require spatially resolved pollution concentrations. Land-use regression (LUR) models estimate ambient concentrations at a fine spatial scale. However, spatial effects such as spatial non-stationarity and spatial autocorrelation can reduce the accuracy of LUR estimates by increasing regression errors and uncertainty; and statistical methods for resolving these effects--e.g., spatially autoregressive (SAR) and geographically weighted regression (GWR) models--may be difficult to apply simultaneously. We used an alternate approach to address spatial non-stationarity and spatial autocorrelation in LUR models for nitrogen dioxide. Traditional models were re-specified to include a variable capturing wind speed and direction, and re-fit as GWR models. Mean R(2) values for the resulting GWR-wind models (summer: 0.86, winter: 0.73) showed a 10-20% improvement over traditional LUR models. GWR-wind models effectively addressed both spatial effects and produced meaningful predictive models. These results suggest a useful method for improving spatially explicit models. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Assessing the effects of rural livelihood transition on non-point source pollution: a coupled ABM-IECM model.

PubMed

Yuan, Chengcheng; Liu, Liming; Ye, Jinwei; Ren, Guoping; Zhuo, Dong; Qi, Xiaoxing

2017-05-01

Water pollution caused by anthropogenic activities and driven by changes in rural livelihood strategies in an agricultural system has received increasing attention in recent decades. To simulate the effects of rural household livelihood transition on non-point source (NPS) pollution, a model combining an agent-based model (ABM) and an improved export coefficient model (IECM) was developed. The ABM was adopted to simulate the dynamic process of household livelihood transition, and the IECM was employed to estimate the effects of household livelihood transition on NPS pollution. The coupled model was tested in a small catchment in the Dongting Lake region, China. The simulated results reveal that the transition of household livelihood strategies occurred with the changes in the prices of rice, pig, and labor. Thus, the cropping system, land-use intensity, resident population, and number of pigs changed in the small catchment from 2000 to 2014. As a result of these changes, the total nitrogen load discharged into the river initially increased from 6841.0 kg in 2000 to 8446.3 kg in 2004 and then decreased to 6063.9 kg in 2014. Results also suggest that rural living, livestock, paddy field, and precipitation alternately became the main causes of NPS pollution in the small catchment, and the midstream region of the small catchment was the primary area for NPS pollution from 2000 to 2014. Despite some limitations, the coupled model provides an innovative way to simulate the effects of rural household livelihood transition on NPS pollution with the change of socioeconomic factors, and thereby identify the key factors influencing water pollution to provide valuable suggestions on how agricultural environmental risks can be reduced through the regulation of the behaviors of farming households in the future.

A new conceptual model for quantifying transboundary contribution of atmospheric pollutants in the East Asian Pacific rim region.

PubMed

Lai, I-Chien; Lee, Chon-Lin; Huang, Hu-Ching

2016-03-01

Transboundary transport of air pollution is a serious environmental concern as pollutant affects both human health and the environment. Many numerical approaches have been utilized to quantify the amounts of pollutants transported to receptor regions, based on emission inventories from possible source regions. However, sparse temporal-spatial observational data and uncertainty in emission inventories might make the transboundary transport contribution difficult to estimate. This study presents a conceptual quantitative approach that uses transport pathway classification in combination with curve fitting models to simulate an air pollutant concentration baseline for pollution background concentrations. This approach is used to investigate the transboundary transport contribution of atmospheric pollutants to a metropolitan area in the East Asian Pacific rim region. Trajectory analysis categorized pollution sources for the study area into three regions: East Asia, Southeast Asia, and Taiwan cities. The occurrence frequency and transboundary contribution results suggest the predominant source region is the East Asian continent. This study also presents an application to evaluate heavy pollution cases for health concerns. This new baseline construction model provides a useful tool for the study of the contribution of transboundary pollution delivered to receptors, especially for areas deficient in emission inventories and regulatory monitoring data for harmful air pollutants. Copyright © 2015 Elsevier Ltd. All rights reserved.

Uncertainty Modeling of Pollutant Transport in Atmosphere and Aquatic Route Using Soft Computing

NASA Astrophysics Data System (ADS)

Datta, D.

2010-10-01

Hazardous radionuclides are released as pollutants in the atmospheric and aquatic environment (ATAQE) during the normal operation of nuclear power plants. Atmospheric and aquatic dispersion models are routinely used to assess the impact of release of radionuclide from any nuclear facility or hazardous chemicals from any chemical plant on the ATAQE. Effect of the exposure from the hazardous nuclides or chemicals is measured in terms of risk. Uncertainty modeling is an integral part of the risk assessment. The paper focuses the uncertainty modeling of the pollutant transport in atmospheric and aquatic environment using soft computing. Soft computing is addressed due to the lack of information on the parameters that represent the corresponding models. Soft-computing in this domain basically addresses the usage of fuzzy set theory to explore the uncertainty of the model parameters and such type of uncertainty is called as epistemic uncertainty. Each uncertain input parameters of the model is described by a triangular membership function.

Application of oil spill model to marine pollution and risk control problems

NASA Astrophysics Data System (ADS)

Aseev, Nikita; Agoshkov, Valery; Sheloput, Tatyana

2017-04-01

Oil transportation by sea induces challenging problems of environmental control. Millions of tonnes of oil are yearly released during routine ship operations, not to mention vast spills due to different accidents (e.g. tanker collisions, grounding, etc.). Oil pollution is dangerous to marine organisms such as plants, fish and mammals, leading to widespread damage to our planet. In turn, fishery and travel agencies can lose money and clients, and ship operators are obliged to pay huge penalties for environmental pollution. In this work we present the method of accessing oil pollution of marine environment using recently developed oil spill model. The model describes basic processes of the oil slick evolution: oil transport due to currents, drift under the action of wind, spreading on the surface, evaporation, emulsification and dispersion. Such parameters as slick location, mass, density of oil, water content, viscosity and density of "water-in-oil" emulsion can be calculated. We demonstrate how to apply the model to damage calculation problems using a concept of average damage to particular marine area. We also formulate the problem of oil spill risk control, when some accident parameters are not known, but their probability distribution is given. We propose a new algorithm to solve such problems and show results of our model simulations. The work can be interesting to broad environmental, physics and mathematics community. The work is supported by Russian Foundation for Basic Research grant 16-31-00510.

Land use regression models to assess air pollution exposure in Mexico City using finer spatial and temporal input parameters.

PubMed

Son, Yeongkwon; Osornio-Vargas, Álvaro R; O'Neill, Marie S; Hystad, Perry; Texcalac-Sangrador, José L; Ohman-Strickland, Pamela; Meng, Qingyu; Schwander, Stephan

2018-05-17

The Mexico City Metropolitan Area (MCMA) is one of the largest and most populated urban environments in the world and experiences high air pollution levels. To develop models that estimate pollutant concentrations at fine spatiotemporal scales and provide improved air pollution exposure assessments for health studies in Mexico City. We developed finer spatiotemporal land use regression (LUR) models for PM 2.5 , PM 10 , O 3 , NO 2 , CO and SO 2 using mixed effect models with the Least Absolute Shrinkage and Selection Operator (LASSO). Hourly traffic density was included as a temporal variable besides meteorological and holiday variables. Models of hourly, daily, monthly, 6-monthly and annual averages were developed and evaluated using traditional and novel indices. The developed spatiotemporal LUR models yielded predicted concentrations with good spatial and temporal agreements with measured pollutant levels except for the hourly PM 2.5 , PM 10 and SO 2 . Most of the LUR models met performance goals based on the standardized indices. LUR models with temporal scales greater than one hour were successfully developed using mixed effect models with LASSO and showed superior model performance compared to earlier LUR models, especially for time scales of a day or longer. The newly developed LUR models will be further refined with ongoing Mexico City air pollution sampling campaigns to improve personal exposure assessments. Copyright © 2018. Published by Elsevier B.V.

Geochemical modelling and speciation studies of metal pollutants present in selected water systems in South Africa

NASA Astrophysics Data System (ADS)

Magu, M. M.; Govender, P. P.; Ngila, J. C.

2016-04-01

Metal pollutants in water poses great threats to living beings and hence requires to be monitored regularly to avoid loss of lives. Various analytical methods are available to monitor these pollutants in water and can be improved with time. Modelling of metal pollutants in any water system helps chemists, engineers and environmentalists to greatly understand the various chemical processes in such systems. Water samples were collected from waste water treatment plant and river from highlands close to its source all the way to the ocean as it passing through areas with high anthropogenic activities. Pre-concentration of pollutants in the samples was done through acid digestion and metal pollutants were analysed using inductively coupled plasma-optical emission spectra (ICP-OES) to determine the concentration levels. Metal concentrations ranged between 0.1356-0.4658 mg/L for Al; 0.0031-0.0050 mg/L for Co, 0.0019-0.0956 mg/L for Cr; 0.0028-0.3484 mg/L for Cu; 0.0489-0.3474 mg/L for Fe; 0.0033-0.0285 mg/L for Mn; 0.0056-0.0222 mg/L for Ni; 0.0265-0.4753 mg/L for Pb and 0.0052-0.5594 mg/L for Zn. Modelling work was performed using PHREEQC couple with Geochemist's workbench (GWB) to determine speciation dynamics and bioavailability of these pollutants. Modelling thus adds value to analytical methods and hence a better complementary tool to laboratory-based experimental studies.

Using a chemistry transport model to account for the spatial variability of exposure concentrations in epidemiologic air pollution studies.

PubMed

Valari, Myrto; Menut, Laurent; Chatignoux, Edouard

2011-02-01

Environmental epidemiology and more specifically time-series analysis have traditionally used area-averaged pollutant concentrations measured at central monitors as exposure surrogates to associate health outcomes with air pollution. However, spatial aggregation has been shown to contribute to the overall bias in the estimation of the exposure-response functions. This paper presents the benefit of adding features of the spatial variability of exposure by using concentration fields modeled with a chemistry transport model instead of monitor data and accounting for human activity patterns. On the basis of county-level census data for the city of Paris, France, and a Monte Carlo simulation, a simple activity model was developed accounting for the temporal variability between working and evening hours as well as during transit. By combining activity data with modeled concentrations, the downtown, suburban, and rural spatial patterns in exposure to nitrogen dioxide, ozone, and PM2.5 (particulate matter [PM] < or = 10 microm in aerodynamic diameter) were captured and parametrized. Exposures predicted with this model were used in a time-series study of the short-term effect of air pollution on total nonaccidental mortality for the 4-yr period from 2001 to 2004. It was shown that the time series of the exposure surrogates developed here are less correlated across co-pollutants than in the case of the area-averaged monitor data. This led to less biased exposure-response functions when all three co-pollutants were inserted simultaneously in the same regression model. This finding yields insight into pollutant-specific health effects that are otherwise masked by the high correlation among co-pollutants.

A modeling framework for characterizing near-road air pollutant concentration at community scales

EPA Science Inventory

In this study, we combine information from transportation network, traffic emissions, and dispersion model to develop a framework to inform exposure estimates for traffic-related air pollutants (TRAPs) with a high spatial resolution. A Research LINE source dispersion model (R-LIN...

Simulating Urban Tree Effects on Air, Water, and Heat Pollution Mitigation: iTree-Hydro Model

NASA Astrophysics Data System (ADS)

Yang, Y.; Endreny, T. A.; Nowak, D.

2011-12-01

Urban and suburban development changes land surface thermal, radiative, porous, and roughness properties and pollutant loading rates, with the combined effect leading to increased air, water, and heat pollution (e.g., urban heat islands). In this research we present the USDA Forest Service urban forest ecosystem and hydrology model, iTree Eco and Hydro, used to analyze how tree cover can deliver valuable ecosystem services to mitigate air, water, and heat pollution. Air pollution mitigation is simulated by dry deposition processes based on detected pollutant levels for CO, NO2, SO2, O3 and atmospheric stability and leaf area indices. Water quality mitigation is simulated with event mean concentration loading algorithms for N, P, metals, and TSS, and by green infrastructure pollutant filtering algorithms that consider flow path dispersal areas. Urban cooling considers direct shading and indirect evapotranspiration. Spatially distributed estimates of hourly tree evapotranspiration during the growing season are used to estimate human thermal comfort. Two main factors regulating evapotranspiration are soil moisture and canopy radiation. Spatial variation of soil moisture is represented by a modified urban topographic index and radiation for each tree is modified by considering aspect, slope and shade from surrounding buildings or hills. We compare the urban cooling algorithms used in iTree-Hydro with the urban canopy and land surface physics schemes used in the Weather Research and Forecasting model. We conclude by identifying biophysical feedbacks between tree-modulated air and water quality environmental services and how these may respond to urban heating and cooling. Improvements to this iTree model are intended to assist managers identify valuable tree services for urban living.

Sources of contamination and modelled pollutant trajectories in a Mediterranean harbour (Tarragona, Spain).

PubMed

Mestres, M; Sierra, J P; Mösso, C; Sánchez-Arcilla, A

2010-06-01

The proximity of commercial harbours to residential areas and the growing environmental awareness of society have led most port authorities to include environmental management within their administration plan. Regarding water quality, it is necessary to have the capacity and tools to deal with contamination episodes that may damage marine ecosystems and human health, but also affect the normal functioning of harbours. This paper presents a description of the main pollutant sources in Tarragona Harbour (Spain), and a numerical analysis of several pollution episodes based on the Port Authority's actual environmental concerns. The results show that pollution generated inside the harbour tends to remain confined within the port, whereas it is very likely that oil spills from a nearby monobuoy may affect the neighbouring beaches. The present combination of numerical models proves itself a useful tool to assess the environmental risk associated to harbour activities and potential pollution spills.

Integration of Rs/gis for Surface Water Pollution Risk Modeling. Case Study: Al-Abrash Syrian Coastal Basin

NASA Astrophysics Data System (ADS)

Yaghi, Y.; Salim, H.

2017-09-01

Recently the topic of the quality of surface water (rivers - lakes) and the sea is an important topics at different levels. It is known that there are two major groups of pollutants: Point Source Pollution (PSP) and non-point Source pollution (NPSP). Historically most of the surface water pollution protection programs dealing with the first set of pollutants which comes from sewage pipes and factories drainage. With the growing need for current and future water security must stand on the current reality of the coastal rivers basin in terms of freshness and cleanliness and condition of water pollution. This research aims to assign the NPS pollutants that reach Al Abrash River and preparation of databases and producing of risk Pollution map for NPS pollutants in order to put the basin management plan to ensure the reduction of pollutants that reach the river. This research resulted of establishing of Databases of NPSP (Like pesticides and fertilizers) and producing of thematic maps for pollution severity and pollution risk based on the pollution models designed in GIS environment and utilizing from remote sensing data. Preliminary recommendations for managing these pollutants were put.

Control of Groundwater Pollution from Animal Feeding Operations: A Farm-Level Dynamic Model for Policy Analysis

NASA Astrophysics Data System (ADS)

Wang, J.; Baerenklau, K.

2012-12-01

Consolidation in livestock production generates higher farm incomes due to economies of scale, but it also brings waste disposal problems. Over-application of animal waste on adjacent land produces adverse environmental and health effects, including groundwater nitrate pollution. The situation is particularly noticeable in California. In respond to this increasingly severe problem, EPA published a type of command-and-control regulation for concentrated animal feeding operations (CAFOs) in 2003. The key component of the regulation is its nutrient management plans (NMPs), which intend to limit the land application rates of animal waste. Although previous studies provide a full perspective on potential economic impacts for CAFOs to meet nutrient standards, their models are static and fail to reflect changes in management practices other than spreading manure on additional land and changing cropping patterns. We develop a dynamic environmental-economic modeling framework for representative CAFOs. The framework incorporates four models (i.e., animal model, crop model, hydrologic model, and economic model) that include various components such as herd management, manure handling system, crop rotation, water sources, irrigation system, waste disposal options, and pollutant emissions. We also include the dynamics of soil characteristics in the rootzone as well as the spatial heterogeneity of the irrigation system. The operator maximizes discounted total farm profit over multiple periods subject to environmental regulations. Decision rules from the dynamic optimization problem demonstrate best management practices for CAFOs to improve their economic and environmental performance. Results from policy simulations suggest that direct quantity restrictions of emission or incentive-based emission policies are much more cost-effective than the standard approach of limiting the amount of animal waste that may be applied to fields (as shown in the figure below); reason being

Modelling of Carbon Monoxide Air Pollution in Larg Cities by Evaluetion of Spectral LANDSAT8 Images

NASA Astrophysics Data System (ADS)

Hamzelo, M.; Gharagozlou, A.; Sadeghian, S.; Baikpour, S. H.; Rajabi, A.

2015-12-01

Air pollution in large cities is one of the major problems that resolve and reduce it need multiple applications and environmental management. Of The main sources of this pollution is industrial activities, urban and transport that enter large amounts of contaminants into the air and reduces its quality. With Variety of pollutants and high volume manufacturing, local distribution of manufacturing centers, Testing and measuring emissions is difficult. Substances such as carbon monoxide, sulfur dioxide, and unburned hydrocarbons and lead compounds are substances that cause air pollution and carbon monoxide is most important. Today, data exchange systems, processing, analysis and modeling is of important pillars of management system and air quality control. In this study, using the spectral signature of carbon monoxide gas as the most efficient gas pollution LANDSAT8 images in order that have better spatial resolution than appropriate spectral bands and weather meters،SAM classification algorithm and Geographic Information System (GIS ), spatial distribution of carbon monoxide gas in Tehran over a period of one year from the beginning of 2014 until the beginning of 2015 at 11 map have modeled and then to the model valuation ،created maps were compared with the map provided by the Tehran quality comparison air company. Compare involved plans did with the error matrix and results in 4 types of care; overall, producer, user and kappa coefficient was investigated. Results of average accuracy were about than 80%, which indicates the fit method and data used for modeling.

A stable isotope model for combined source apportionment and degradation quantification of environmental pollutants

NASA Astrophysics Data System (ADS)

Lutz, Stefanie; Van Breukelen, Boris

2014-05-01

Natural attenuation can represent a complementary or alternative approach to engineered remediation of polluted sites. In this context, compound specific stable isotope analysis (CSIA) has proven a useful tool, as it can provide evidence of natural attenuation and assess the extent of in-situ degradation based on changes in isotope ratios of pollutants. Moreover, CSIA can allow for source identification and apportionment, which might help to identify major emission sources in complex contamination scenarios. However, degradation and mixing processes in aquifers can lead to changes in isotopic compositions, such that their simultaneous occurrence might complicate combined source apportionment (SA) and assessment of the extent of degradation (ED). We developed a mathematical model (stable isotope sources and sinks model; SISS model) based on the linear stable isotope mixing model and the Rayleigh equation that allows for simultaneous SA and quantification of the ED in a scenario of two emission sources and degradation via one reaction pathway. It was shown that the SISS model with CSIA of at least two elements contained in the pollutant (e.g., C and H in benzene) allows for unequivocal SA even in the presence of degradation-induced isotope fractionation. In addition, the model enables precise quantification of the ED provided degradation follows instantaneous mixing of two sources. If mixing occurs after two sources have degraded separately, the model can still yield a conservative estimate of the overall extent of degradation. The SISS model was validated against virtual data from a two-dimensional reactive transport model. The model results for SA and ED were in good agreement with the simulation results. The application of the SISS model to field data of benzene contamination was, however, challenged by large uncertainties in measured isotope data. Nonetheless, the use of the SISS model provided a better insight into the interplay of mixing and degradation

S argassum muticum-synthesized silver nanoparticles: an effective control tool against mosquito vectors and bacterial pathogens.

PubMed

Madhiyazhagan, Pari; Murugan, Kadarkarai; Kumar, Arjunan Naresh; Nataraj, Thiyagarajan; Dinesh, Devakumar; Panneerselvam, Chellasamy; Subramaniam, Jayapal; Mahesh Kumar, Palanisamy; Suresh, Udaiyan; Roni, Mathath; Nicoletti, Marcello; Alarfaj, Abdullah A; Higuchi, Akon; Munusamy, Murugan A; Benelli, Giovanni

2015-11-01

Mosquito-borne diseases represent a deadly threat for millions of people worldwide. Furthermore, pathogens and parasites polluting water also constitute a severe plague for populations of developing countries. In this research, silver nanoparticles (AgNP) were synthesized using the aqueous extract of the seaweed Sargassum muticum. The production of AgNP was confirmed by surface plasmon resonance band illustrated in UV-vis spectrophotometry. AgNP were characterized by FTIR, SEM, EDX, and XRD analyses. AgNP were mostly spherical in shape, crystalline in nature, with face-centered cubic geometry, and mean size was 43-79 nm. Toxicity of AgNP was assessed against Aedes aegypti, Anopheles stephensi, and Culex quinquefasciatus. In laboratory, AgNP were highly toxic against larvae and pupae of the three mosquito species. Maximum efficacy was observed against A. stephensi larvae, with LC50 ranging from 16.156 ppm (larva I) to 28.881 ppm (pupa). In the field, a single treatment with AgNP (10 × LC50) in water storage reservoirs was effective against the three mosquito vectors, allowing complete elimination of larval populations after 72 h. In ovicidal experiments, egg hatchability was reduced by 100% after treatment with 30 ppm of AgNP. Ovideterrence assays highlighted that 10 ppm of AgNP reduced oviposition rates of more than 70% in A. aegypti, A. stephensi, and C. quinquefasciatus (OAI = -0.61, -0.63, and -0.58, respectively). Antibacterial properties of AgNP were evaluated against Bacillus subtilis, Klebsiella pneumoniae, and Salmonella typhi using the agar disk diffusion and minimum inhibitory concentration protocol. AgNP tested at 50 ppm evoked growth inhibition zones larger than 5 mm in all tested bacteria. Overall, the chance to use S. muticum-synthesized AgNP for control of mosquito vectors seems promising since they are effective at low doses and may constitute an advantageous alternative to build newer and safer mosquito control tools. This is the first

Regional transport and dilution during high-pollution episodes in southern France: Summary of findings from the Field Experiment to Constraint Models of Atmospheric Pollution and Emissions Transport (ESCOMPTE)

NASA Astrophysics Data System (ADS)

Drobinski, P.; SaïD, F.; Ancellet, G.; Arteta, J.; Augustin, P.; Bastin, S.; Brut, A.; Caccia, J. L.; Campistron, B.; Cautenet, S.; Colette, A.; Coll, I.; Corsmeier, U.; Cros, B.; Dabas, A.; Delbarre, H.; Dufour, A.; Durand, P.; GuéNard, V.; Hasel, M.; Kalthoff, N.; Kottmeier, C.; Lasry, F.; Lemonsu, A.; Lohou, F.; Masson, V.; Menut, L.; Moppert, C.; Peuch, V. H.; Puygrenier, V.; Reitebuch, O.; Vautard, R.

2007-07-01

In the French Mediterranean basin the large city of Marseille and its industrialized suburbs (oil plants in the Fos-Berre area) are major pollutant sources that cause frequent and hazardous pollution episodes, especially in summer when intense solar heating enhances the photochemical activity and when the sea breeze circulation redistributes pollutants farther north in the countryside. This paper summarizes the findings of 5 years of research on the sea breeze in southern France and related mesoscale transport and dilution of pollutants within the Field Experiment to Constraint Models of Atmospheric Pollution and Emissions Transport (ESCOMPTE) program held in June and July 2001. This paper provides an overview of the experimental and numerical challenges identified before the ESCOMPTE field experiment and summarizes the key findings made in observation, simulation, and theory. We specifically address the role of large-scale atmospheric circulation to local ozone vertical distribution and the mesoscale processes driving horizontal advection of pollutants and vertical transport and mixing via entrainment at the top of the sea breeze or at the front and venting along the sloped terrain. The crucial importance of the interactions between processes of various spatial and temporal scales is thus highlighted. The advances in numerical modeling and forecasting of sea breeze events and ozone pollution episodes in southern France are also underlined. Finally, we conclude and point out some open research questions needing further investigation.

The Stability of Silver Nanoparticles in a Model of Pulmonary Surfactant

PubMed Central

Fen, Leo Bey; Chen, Shu; Kyo, Yoshihiko; Herpoldt, Karla-Luise; Terrill, Nicholas J.; Dunlop, Iain E.; McPhail, David S.; Shaffer, Milo S.; Schwander, Stephan; Gow, Andrew; Zhang, Junfeng (Jim); Chung, Kian Fan; Tetley, Teresa D.; Porter, Alexandra E.; Ryan, Mary P.

2013-01-01

The growing use of silver nanoparticles (AgNPs) in consumer products has raised concerns about their potential impact on the environment and human health. Whether AgNPs dissolve and release Ag+ ions, or coarsen to form large aggregates, is critical in determining their potential toxicity. In this work, the stability of AgNPs in dipalmitoylphosphatidylcholine (DPPC), the major component of pulmonary surfactant, was investigated as a function of pH. Spherical, citrate-capped AgNPs with average diameters of 14 ± 1.6 nm (n=200) were prepared by a chemical bath reduction. The kinetics of Ag+ ion release was strongly pH-dependent. After 14 days of incubation in sodium perchlorate (NaClO4) or perchloric acid (HClO4) solutions, the total fraction of AgNPs dissolved varied from ~10 % at pH 3, to ~2 % at pH 5, with negligible dissolution at pH 7. A decrease in pH from 7 to 3 also promoted particle aggregation and coarsening. DPPC (100 mg.L−1) delayed the release of Ag+ ions, but did not significantly alter the total amount of Ag+ released after two weeks. In addition, DPPC improved the dispersion of the AgNPs and inhibited aggregation and coarsening. TEM images revealed that the AgNPs were coated with a DPPC layer serving as a semi-permeable layer. Hence, lung lining fluid, particularly DPPC, can modify the aggregation state and kinetics of Ag+ ion release of inhaled AgNPs in the lung. These observations have important implications for predicting the potential reactivity of AgNPs in the lung and the environment. PMID:23988335

Modeling of a heavy haze-pollution in eastern China in winter, 2013

NASA Astrophysics Data System (ADS)

Li, J.; Song, Y.; Huang, X.; Li, M.

2013-12-01

In January 2013, China experienced the most serious haze events in recent years, with nearly all the cities in eastern China influenced. Beijing, Tianjin, Shijiazhuang, Hefei, Wuhan, Nanjing, and Changsha all reported unbelievable seriously high concentrations of aerosol particles especially PM2.5 which is adverse to human health. In our research, Weather Research and Forecasting (WRF-Chem) model was used to explore the formation mechanism of the event. Aqueous chemistry was very important due to the high humidity during the period. To reproduce the formation of secondary inorganic matter, we added SO2●H2O content when the relatively humidity was high enough for fog formation because mixing of droplets with different pH can lead to more sulfate production in aqueous than the application of Henry's law. On the other hand, considering the huge primary pollution of China containing large amount of crustal elements as well as the catalysis of iron and manganese to SO2 aqueous oxidation, we modified the Fe3+, Mn2+ and Ca2+ calculation in the module. The modeling results revealed a pollution belt in January, stretching from Hunan province to Beijing along with Hubei, Henan, Anhui, Jiangsu, Shandong, and Hebei. From January 7th 00:00 (Beijing time) to January 31th 20:00, the average dry PM2.5 concentration exceeded 200μg/m3 in the majority area and some places in Hubei, Henan and Anhui even reached up to 400μg/m3. High concentrations of sulfate and nitrate indicated that coal combustion and vehicle exhaust were both contributed to the air pollution. The simulation captured two haze events with a very large area covering, first from January 7th to 16th, second from 27th to 31st, which well accorded with the news. Besides huge emission of pollutants, meteorology conditions with high relatively humidity and low wind speed could facilitate the pollution as well. For Beijing, the simulated average PM2.5 concentration was 176μg/m3 which was 18.5% higher than the

Characterization and Placement of Wetlands for Integrated ...

EPA Pesticide Factsheets

Constructed wetlands have been recognized as an efficient and cost-effective conservation practice to protect water quality through reducing the transport of sediments and nutrients from upstream croplands to downstream water bodies. The challenge resides in targeting the strategic location of wetlands within agricultural watersheds to maximize the reduction in nutrient loads while minimizing their impact on crop production. Furthermore, agricultural watersheds involve complex interrelated processes requiring a systems approach to evaluate the inherent relationships between wetlands and multiple sediment/nutrient sources (sheet, rill, ephemeral gully, channels) and other conservation practices (filter strips). This study describes new capabilities of the USDA’s Annualized Agricultural Non-Point Source pollutant loading model, AnnAGNPS. A developed AnnAGNPS GIS-based wetland component, AgWet, is introduced to identify potential sites and characterize individual artificial or natural wetlands at a watershed scale. AgWet provides a simplified, semi-automated, and spatially distributed approach to quantitatively evaluate wetlands as potential conservation management alternatives. AgWet is integrated with other AnnAGNPS components providing seamless capabilities of estimating the potential sediment/nutrient reduction of individual wetlands. This technology provides conservationists the capability for improved management of watershed systems and support for nutrient

Initial study of sediment antagonism and characteristics of silver nanoparticle-coated biliary stents in an experimental animal model.

PubMed

Tian, Yigeng; Xia, Mingfeng; Zhang, Shuai; Fu, Zhen; Wen, Qingbin; Liu, Feng; Xu, Zongzhen; Li, Tao; Tian, Hu

2016-01-01

Plastic biliary stents used to relieve obstructive jaundice are frequently blocked by sediment, resulting in loss of drainage. We prepared stents coated with silver nanoparticles (AgNPs) and compared their ability to resist sedimentation with Teflon stents in a beagle model of obstructive jaundice. AgNP-coated Teflon biliary stents were prepared by chemical oxidation-reduction and evaluated in an obstructive jaundice model that was produced by ligation of common bile duct (CBD); animals were randomized to two equal groups for placement of AgNP-coated or Teflon control stents. Liver function and inflammatory index were found to be similar in the two groups, and the obstruction was relieved. Stents were removed 21 days after insertion and observed by scanning and transmission electron microscopy. The AgNP coating was analyzed by energy dispersive X-ray analysis (EDXA), and the composition of sediment was assayed by Fourier-transform infrared (FTIR) spectroscopy. Electron microscopy revealed a black, closely adherent AgNP stent coating, with thicknesses of 1.5-6 µm. Sediment thickness and density were greater on Teflon than on AgNP-coated stents. EDXA confirmed the stability and integrity of the AgNP coating before and after in vivo animal experimentation. FTIR spectroscopy identified stent sediment components including bilirubin, cholesterol, bile acid, protein, calcium, and other substances. AgNP-coated biliary stents resisted sediment accumulation in this canine model of obstructive jaundice caused by ligation of the CBD.

Initial study of sediment antagonism and characteristics of silver nanoparticle-coated biliary stents in an experimental animal model

PubMed Central

Tian, Yigeng; Xia, Mingfeng; Zhang, Shuai; Fu, Zhen; Wen, Qingbin; Liu, Feng; Xu, Zongzhen; Li, Tao; Tian, Hu

2016-01-01

Objective Plastic biliary stents used to relieve obstructive jaundice are frequently blocked by sediment, resulting in loss of drainage. We prepared stents coated with silver nanoparticles (AgNPs) and compared their ability to resist sedimentation with Teflon stents in a beagle model of obstructive jaundice. Methods AgNP-coated Teflon biliary stents were prepared by chemical oxidation–reduction and evaluated in an obstructive jaundice model that was produced by ligation of common bile duct (CBD); animals were randomized to two equal groups for placement of AgNP-coated or Teflon control stents. Liver function and inflammatory index were found to be similar in the two groups, and the obstruction was relieved. Stents were removed 21 days after insertion and observed by scanning and transmission electron microscopy. The AgNP coating was analyzed by energy dispersive X-ray analysis (EDXA), and the composition of sediment was assayed by Fourier-transform infrared (FTIR) spectroscopy. Results Electron microscopy revealed a black, closely adherent AgNP stent coating, with thicknesses of 1.5–6 µm. Sediment thickness and density were greater on Teflon than on AgNP-coated stents. EDXA confirmed the stability and integrity of the AgNP coating before and after in vivo animal experimentation. FTIR spectroscopy identified stent sediment components including bilirubin, cholesterol, bile acid, protein, calcium, and other substances. Conclusion AgNP-coated biliary stents resisted sediment accumulation in this canine model of obstructive jaundice caused by ligation of the CBD. PMID:27217749

Development and analysis of air quality modeling simulations for hazardous air pollutants

NASA Astrophysics Data System (ADS)

Luecken, D. J.; Hutzell, W. T.; Gipson, G. L.

The concentrations of five hazardous air pollutants were simulated using the community multi-scale air quality (CMAQ) modeling system. Annual simulations were performed over the continental United States for the entire year of 2001 to support human exposure estimates. Results are shown for formaldehyde, acetaldehyde, benzene, 1,3-butadiene and acrolein. Photochemical production in the atmosphere is predicted to dominate ambient formaldehyde and acetaldehyde concentrations, and to account for a significant fraction of ambient acrolein concentrations. Spatial and temporal variations are large throughout the domain over the year. Predicted concentrations are compared with observations for formaldehyde, acetaldehyde, benzene and 1,3-butadiene. Although the modeling results indicate an overall slight tendency towards underprediction, they reproduce episodic and seasonal behavior of pollutant concentrations at many monitors with good skill.

Chemical pollution assessment and prioritisation model for the Upper and Middle Vaal water management areas of South Africa.

PubMed

Dzwairo, B; Otieno, F A O

2014-12-01

A chemical pollution assessment and prioritisation model was developed for the Upper and Middle Vaal water management areas of South Africa in order to provide a simple and practical Pollution Index to assist with mitigation and rehabilitation activities. Historical data for 2003 to 2008 from 21 river sites were cubic-interpolated to daily values. Nine parameters were considered for this purpose, that is, ammonium, chloride, electrical conductivity, dissolved oxygen, pH, fluoride, nitrate, phosphate and sulphate. Parameter selection was based on sub-catchment pollution characteristics and availability of a consistent data range, against a harmonised guideline which provided five classes. Classes 1, 2, 3 and 4 used ideal catchment background values for Vaal Dam, Vaal Barrage, Blesbokspruit/Suikerbosrant and Klip Rivers, respectively. Class 5 represented values which fell above those for Klip River. The Pollution Index, as provided by the model, identified pollution prioritisation monitoring points on Rietspruit-W:K2, Natalspruit:K12, Blesbokspruit:B1, Rietspruit-L:R1/R2, Taaibosspruit:T1 and Leeuspruit:L1. Pre-classification indicated that pollution sources were domestic, industrial and mine effluent. It was concluded that rehabilitation and mitigation measures should prioritise points with high classes. Ability of the model to perform simple scenario building and analysis was considered to be an effective tool for acid mine drainage pollution assessment.

Modeling of land use and reservoir effects on nonpoint source pollution in a highly agricultural basin

USGS Publications Warehouse

Wu, Yiping; Liu, Shu-Guang

2012-01-01

Nonpoint source (NPS) pollution is tightly linked to land use activities that determine the sources and magnitudes of pollutant loadings to stream water. The pollutant loads may also be alleviated within reservoirs because of the physical interception resulting from changed hydrological regimes and other biochemical processes. It is important but challenging to assess the NPS pollution processes with human effects due to the measurement limitations. The objective of this study is to evaluate the effects of human activities such as land uses and reservoir operation on the hydrological and NPS pollution processes in a highly agricultural area-the Iowa River Basin-using the Soil and Water Assessment Tool (SWAT). The evaluation of model performance at multiple sites reveals that SWAT can consistently simulate the daily streamflow, and monthly/annual sediment and nutrient loads (nitrate nitrogen and mineral phosphorus) in the basin. We also used the calibrated model to estimate the trap efficiencies of sediment (~78%) and nutrients (~30%) in the Coralville Reservoir within the basin. These non-negligible effects emphasize the significance of incorporating the sediment and nutrient removal mechanisms into watershed system studies. The spatial quantification of the critical NPS pollution loads can help identify hot-spot areas that are likely locations for the best management practices.

Modeling of land use and reservoir effects on nonpoint source pollution in a highly agricultural basin.

PubMed

Wu, Yiping; Liu, Shuguang

2012-09-01

Nonpoint source (NPS) pollution is tightly linked to land use activities that determine the sources and magnitudes of pollutant loadings to stream water. The pollutant loads may also be alleviated within reservoirs because of the physical interception resulting from changed hydrological regimes and other biochemical processes. It is important but challenging to assess the NPS pollution processes with human effects due to the measurement limitations. The objective of this study is to evaluate the effects of human activities such as land uses and reservoir operation on the hydrological and NPS pollution processes in a highly agricultural area-the Iowa River Basin-using the Soil and Water Assessment Tool (SWAT). The evaluation of model performance at multiple sites reveals that SWAT can consistently simulate the daily streamflow, and monthly/annual sediment and nutrient loads (nitrate nitrogen and mineral phosphorus) in the basin. We also used the calibrated model to estimate the trap efficiencies of sediment (∼78%) and nutrients (∼30%) in the Coralville Reservoir within the basin. These non-negligible effects emphasize the significance of incorporating the sediment and nutrient removal mechanisms into watershed system studies. The spatial quantification of the critical NPS pollution loads can help identify hot-spot areas that are likely locations for the best management practices.

A model for estimating air-pollutant uptake by forests: calculation of absorption of sulfur dioxide from dispersed sources

Treesearch

C. E., Jr. Murphy; T. R. Sinclair; K. R. Knoerr

1977-01-01

The computer model presented in this paper is designed to estimate the uptake of air pollutants by forests. The model utilizes submodels to describe atmospheric diffusion immediately above and within the canopy, and into the sink areas within or on the trees. The program implementing the model is general and can be used with only minor changes for any gaseous pollutant...

Uncertainty characterization and quantification in air pollution models. Application to the CHIMERE model

NASA Astrophysics Data System (ADS)

Debry, Edouard; Mallet, Vivien; Garaud, Damien; Malherbe, Laure; Bessagnet, Bertrand; Rouïl, Laurence

2010-05-01

Prev'Air is the French operational system for air pollution forecasting. It is developed and maintained by INERIS with financial support from the French Ministry for Environment. On a daily basis it delivers forecasts up to three days ahead for ozone, nitrogene dioxide and particles over France and Europe. Maps of concentration peaks and daily averages are freely available to the general public. More accurate data can be provided to customers and modelers. Prev'Air forecasts are based on the Chemical Transport Model CHIMERE. French authorities rely more and more on this platform to alert the general public in case of high pollution events and to assess the efficiency of regulation measures when such events occur. For example the road speed limit may be reduced in given areas when the ozone level exceeds one regulatory threshold. These operational applications require INERIS to assess the quality of its forecasts and to sensitize end users about the confidence level. Indeed concentrations always remain an approximation of the true concentrations because of the high uncertainty on input data, such as meteorological fields and emissions, because of incomplete or inaccurate representation of physical processes, and because of efficiencies in numerical integration [1]. We would like to present in this communication the uncertainty analysis of the CHIMERE model led in the framework of an INERIS research project aiming, on the one hand, to assess the uncertainty of several deterministic models and, on the other hand, to propose relevant indicators describing air quality forecast and their uncertainty. There exist several methods to assess the uncertainty of one model. Under given assumptions the model may be differentiated into an adjoint model which directly provides the concentrations sensitivity to given parameters. But so far Monte Carlo methods seem to be the most widely and oftenly used [2,3] as they are relatively easy to implement. In this framework one

Modelling the photochemical pollution over the metropolitan area of Porto Alegre, Brazil

NASA Astrophysics Data System (ADS)

Borrego, C.; Monteiro, A.; Ferreira, J.; Moraes, M. R.; Carvalho, A.; Ribeiro, I.; Miranda, A. I.; Moreira, D. M.

2010-01-01

The main purpose of this study is to evaluate the photochemical pollution over the Metropolitan Area of Porto Alegre (MAPA), Brazil, where high concentrations of ozone have been registered during the past years. Due to the restricted spatial coverage of the monitoring air quality network, a numerical modelling technique was selected and applied to this assessment exercise. Two different chemistry-transport models - CAMx and CALGRID - were applied for a summer period, driven by the MM5 meteorological model. The meteorological model performance was evaluated comparing its results to available monitoring data measured at the Porto Alegre airport. Validation results point out a good model performance. It was not possible to evaluate the chemistry models performance due to the lack of adequate monitoring data. Nevertheless, the model intercomparison between CAMx and CALGRID shows a similar behaviour in what concerns the simulation of nitrogen dioxide, but some discrepancies concerning ozone. Regarding the fulfilment of the Brazilian air quality targets, the simulated ozone concentrations surpass the legislated value in specific periods, mainly outside the urban area of Porto Alegre. The ozone formation is influenced by the emission of pollutants that act as precursors (like the nitrogen oxides emitted at Porto Alegre urban area and coming from a large refinery complex) and by the meteorological conditions.

United States‐Mexican border watershed assessment: Modeling nonpoint source pollution in Ambos Nogales

USGS Publications Warehouse

Norman, Laura M.

2007-01-01

Ecological considerations need to be interwoven with economic policy and planning along the United States‐Mexican border. Non‐point source pollution can have significant implications for the availability of potable water and the continued health of borderland ecosystems in arid lands. However, environmental assessments in this region present a host of unique issues and problems. A common obstacle to the solution of these problems is the integration of data with different resolutions, naming conventions, and quality to create a consistent database across the binational study area. This report presents a simple modeling approach to predict nonpoint source pollution that can be used for border watersheds. The modeling approach links a hillslopescale erosion‐prediction model and a spatially derived sediment‐delivery model within a geographic information system to estimate erosion, sediment yield, and sediment deposition across the Ambos Nogales watershed in Sonora, Mexico, and Arizona. This paper discusses the procedures used for creating a watershed database to apply the models and presents an example of the modeling approach applied to a conservation‐planning problem.

Total maximum allocated load calculation of nitrogen pollutants by linking a 3D biogeochemical-hydrodynamic model with a programming model in Bohai Sea

NASA Astrophysics Data System (ADS)

Dai, Aiquan; Li, Keqiang; Ding, Dongsheng; Li, Yan; Liang, Shengkang; Li, Yanbin; Su, Ying; Wang, Xiulin

2015-12-01

The equal percent removal (EPR) method, in which pollutant reduction ratio was set as the same in all administrative regions, failed to satisfy the requirement for water quality improvement in the Bohai Sea. Such requirement was imposed by the developed Coastal Pollution Total Load Control Management. The total maximum allocated load (TMAL) of nitrogen pollutants in the sea-sink source regions (SSRs) around the Bohai Rim, which is the maximum pollutant load of every outlet under the limitation of water quality criteria, was estimated by optimization-simulation method (OSM) combined with loop approximation calculation. In OSM, water quality is simulated using a water quality model and pollutant load is calculated with a programming model. The effect of changes in pollutant loads on TMAL was discussed. Results showed that the TMAL of nitrogen pollutants in 34 SSRs was 1.49×105 ton/year. The highest TMAL was observed in summer, whereas the lowest in winter. TMAL was also higher in the Bohai Strait and central Bohai Sea and lower in the inner area of the Liaodong Bay, Bohai Bay and Laizhou Bay. In loop approximation calculation, the TMAL obtained was considered satisfactory for water quality criteria as fluctuation of concentration response matrix with pollutant loads was eliminated. Results of numerical experiment further showed that water quality improved faster and were more evident under TMAL input than that when using the EPR method

Organic Pollutant Penetration through Fruit Polyester Skin: A Modified Three-compartment Diffusion Model

NASA Astrophysics Data System (ADS)

Li, Yungui; Li, Qingqing; Chen, Baoliang

2016-03-01

The surface of plants is covered by a continuous but heterogeneous cuticular membrane (CM). Serving as the first protective barrier, the uptake and transport behavior of organic pollutants at this interface continue to engage the research efforts of environmental chemist. To date, the contributions of cuticular components as a defense against the organic pollutants penetration remain unresolved. In this study, the unsteady-state penetration characteristics of phenanthrene (PHE) through isolated fruit CM was investigated. PHE penetration was differentiated by three cuticular compartments: epicuticular waxes (EW), cuticle proper (CP) and cuticular layer (CL). The driving force for PHE penetration was ascribed to the sharp concentration gradient built up endogenously by cuticular compartments with different lipophilic affinities. A modified penetration model was established and verified in terms of its general suitability for the hydrophobic chemicals and CMs of various plant species (apple, tomato and potato). The new three-compartment model demonstrates much higher accuracy in characterizing the uptake and transport behavior of semivolatile chemicals with fewer limitations in terms of environmental conditions and complexity (e.g., coexisting contaminants and temperature). This model could contribute to a more comprehensive understanding on the role of polymeric lipids in the organic pollutant sorption and transport into plants.

Organic Pollutant Penetration through Fruit Polyester Skin: A Modified Three-compartment Diffusion Model.

PubMed

Li, Yungui; Li, Qingqing; Chen, Baoliang

2016-03-24

The surface of plants is covered by a continuous but heterogeneous cuticular membrane (CM). Serving as the first protective barrier, the uptake and transport behavior of organic pollutants at this interface continue to engage the research efforts of environmental chemist. To date, the contributions of cuticular components as a defense against the organic pollutants penetration remain unresolved. In this study, the unsteady-state penetration characteristics of phenanthrene (PHE) through isolated fruit CM was investigated. PHE penetration was differentiated by three cuticular compartments: epicuticular waxes (EW), cuticle proper (CP) and cuticular layer (CL). The driving force for PHE penetration was ascribed to the sharp concentration gradient built up endogenously by cuticular compartments with different lipophilic affinities. A modified penetration model was established and verified in terms of its general suitability for the hydrophobic chemicals and CMs of various plant species (apple, tomato and potato). The new three-compartment model demonstrates much higher accuracy in characterizing the uptake and transport behavior of semivolatile chemicals with fewer limitations in terms of environmental conditions and complexity (e.g., coexisting contaminants and temperature). This model could contribute to a more comprehensive understanding on the role of polymeric lipids in the organic pollutant sorption and transport into plants.

A quantitative speciation model for the adsorption of organic pollutants on activated carbon.

PubMed

Grivé, M; García, D; Domènech, C; Richard, L; Rojo, I; Martínez, X; Rovira, M

2013-01-01

Granular activated carbon (GAC) is commonly used as adsorbent in water treatment plants given its high capacity for retaining organic pollutants in aqueous phase. The current knowledge on GAC behaviour is essentially empirical, and no quantitative description of the chemical relationships between GAC surface groups and pollutants has been proposed. In this paper, we describe a quantitative model for the adsorption of atrazine onto GAC surface. The model is based on results of potentiometric titrations and three types of adsorption experiments which have been carried out in order to determine the nature and distribution of the functional groups on the GAC surface, and evaluate the adsorption characteristics of GAC towards atrazine. Potentiometric titrations have indicated the existence of at least two different families of chemical groups on the GAC surface, including phenolic- and benzoic-type surface groups. Adsorption experiments with atrazine have been satisfactorily modelled with the geochemical code PhreeqC, assuming that atrazine is sorbed onto the GAC surface in equilibrium (log Ks = 5.1 ± 0.5). Independent thermodynamic calculations suggest a possible adsorption of atrazine on a benzoic derivative. The present work opens a new approach for improving the adsorption capabilities of GAC towards organic pollutants by modifying its chemical properties.

Organic Pollutant Penetration through Fruit Polyester Skin: A Modified Three-compartment Diffusion Model

PubMed Central

Li, Yungui; Li, Qingqing; Chen, Baoliang

2016-01-01

The surface of plants is covered by a continuous but heterogeneous cuticular membrane (CM). Serving as the first protective barrier, the uptake and transport behavior of organic pollutants at this interface continue to engage the research efforts of environmental chemist. To date, the contributions of cuticular components as a defense against the organic pollutants penetration remain unresolved. In this study, the unsteady-state penetration characteristics of phenanthrene (PHE) through isolated fruit CM was investigated. PHE penetration was differentiated by three cuticular compartments: epicuticular waxes (EW), cuticle proper (CP) and cuticular layer (CL). The driving force for PHE penetration was ascribed to the sharp concentration gradient built up endogenously by cuticular compartments with different lipophilic affinities. A modified penetration model was established and verified in terms of its general suitability for the hydrophobic chemicals and CMs of various plant species (apple, tomato and potato). The new three-compartment model demonstrates much higher accuracy in characterizing the uptake and transport behavior of semivolatile chemicals with fewer limitations in terms of environmental conditions and complexity (e.g., coexisting contaminants and temperature). This model could contribute to a more comprehensive understanding on the role of polymeric lipids in the organic pollutant sorption and transport into plants. PMID:27009902

Industrial pollution and the management of river water quality: a model of Kelani River, Sri Lanka.

PubMed

Gunawardena, Asha; Wijeratne, E M S; White, Ben; Hailu, Atakelty; Pandit, Ram

2017-08-19

Water quality of the Kelani River has become a critical issue in Sri Lanka due to the high cost of maintaining drinking water standards and the market and non-market costs of deteriorating river ecosystem services. By integrating a catchment model with a river model of water quality, we developed a method to estimate the effect of pollution sources on ambient water quality. Using integrated model simulations, we estimate (1) the relative contribution from point (industrial and domestic) and non-point sources (river catchment) to river water quality and (2) pollutant transfer coefficients for zones along the lower section of the river. Transfer coefficients provide the basis for policy analyses in relation to the location of new industries and the setting of priorities for industrial pollution control. They also offer valuable information to design socially optimal economic policy to manage industrialized river catchments.

Human Exposure Assessment for Air Pollution.

PubMed

Han, Bin; Hu, Li-Wen; Bai, Zhipeng

2017-01-01

Assessment of human exposure to air pollution is a fundamental part of the more general process of health risk assessment. The measurement methods for exposure assessment now include personal exposure monitoring, indoor-outdoor sampling, mobile monitoring, and exposure assessment modeling (such as proximity models, interpolation model, air dispersion models, and land-use regression (LUR) models). Among these methods, personal exposure measurement is considered to be the most accurate method of pollutant exposure assessment until now, since it can better quantify observed differences and better reflect exposure among smaller groups of people at ground level. And since the great differences of geographical environment, source distribution, pollution characteristics, economic conditions, and living habits, there is a wide range of differences between indoor, outdoor, and individual air pollution exposure in different regions of China. In general, the indoor particles in most Chinese families comprise infiltrated outdoor particles, particles generated indoors, and a few secondary organic aerosol particles, and in most cases, outdoor particle pollution concentrations are a major contributor to indoor concentrations in China. Furthermore, since the time, energy, and expense are limited, it is difficult to measure the concentration of pollutants for each individual. In recent years, obtaining the concentration of air pollutants by using a variety of exposure assessment models is becoming a main method which could solve the problem of the increasing number of individuals in epidemiology studies.

Collaborative Emission Reduction Model Based on Multi-Objective Optimization for Greenhouse Gases and Air Pollutants.

PubMed

Meng, Qing-chun; Rong, Xiao-xia; Zhang, Yi-min; Wan, Xiao-le; Liu, Yuan-yuan; Wang, Yu-zhi

2016-01-01

CO2 emission influences not only global climate change but also international economic and political situations. Thus, reducing the emission of CO2, a major greenhouse gas, has become a major issue in China and around the world as regards preserving the environmental ecology. Energy consumption from coal, oil, and natural gas is primarily responsible for the production of greenhouse gases and air pollutants such as SO2 and NOX, which are the main air pollutants in China. In this study, a mathematical multi-objective optimization method was adopted to analyze the collaborative emission reduction of three kinds of gases on the basis of their common restraints in different ways of energy consumption to develop an economic, clean, and efficient scheme for energy distribution. The first part introduces the background research, the collaborative emission reduction for three kinds of gases, the multi-objective optimization, the main mathematical modeling, and the optimization method. The second part discusses the four mathematical tools utilized in this study, which include the Granger causality test to analyze the causality between air quality and pollutant emission, a function analysis to determine the quantitative relation between energy consumption and pollutant emission, a multi-objective optimization to set up the collaborative optimization model that considers energy consumption, and an optimality condition analysis for the multi-objective optimization model to design the optimal-pole algorithm and obtain an efficient collaborative reduction scheme. In the empirical analysis, the data of pollutant emission and final consumption of energies of Tianjin in 1996-2012 was employed to verify the effectiveness of the model and analyze the efficient solution and the corresponding dominant set. In the last part, several suggestions for collaborative reduction are recommended and the drawn conclusions are stated.

Collaborative Emission Reduction Model Based on Multi-Objective Optimization for Greenhouse Gases and Air Pollutants

PubMed Central

Zhang, Yi-min; Wan, Xiao-le; Liu, Yuan-yuan; Wang, Yu-zhi

2016-01-01

CO2 emission influences not only global climate change but also international economic and political situations. Thus, reducing the emission of CO2, a major greenhouse gas, has become a major issue in China and around the world as regards preserving the environmental ecology. Energy consumption from coal, oil, and natural gas is primarily responsible for the production of greenhouse gases and air pollutants such as SO2 and NOX, which are the main air pollutants in China. In this study, a mathematical multi-objective optimization method was adopted to analyze the collaborative emission reduction of three kinds of gases on the basis of their common restraints in different ways of energy consumption to develop an economic, clean, and efficient scheme for energy distribution. The first part introduces the background research, the collaborative emission reduction for three kinds of gases, the multi-objective optimization, the main mathematical modeling, and the optimization method. The second part discusses the four mathematical tools utilized in this study, which include the Granger causality test to analyze the causality between air quality and pollutant emission, a function analysis to determine the quantitative relation between energy consumption and pollutant emission, a multi-objective optimization to set up the collaborative optimization model that considers energy consumption, and an optimality condition analysis for the multi-objective optimization model to design the optimal-pole algorithm and obtain an efficient collaborative reduction scheme. In the empirical analysis, the data of pollutant emission and final consumption of energies of Tianjin in 1996–2012 was employed to verify the effectiveness of the model and analyze the efficient solution and the corresponding dominant set. In the last part, several suggestions for collaborative reduction are recommended and the drawn conclusions are stated. PMID:27010658

Development of an on-line source-tagged model for sulfate, nitrate and ammonium: A modeling study for highly polluted periods in Shanghai, China.

PubMed

Wu, Jian-Bin; Wang, Zifa; Wang, Qian; Li, Jie; Xu, Jianming; Chen, HuanSheng; Ge, Baozhu; Zhou, Guangqiang; Chang, Luyu

2017-02-01

An on-line source-tagged model coupled with an air quality model (Nested Air Quality Prediction Model System, NAQPMS) was applied to estimate source contributions of primary and secondary sulfate, nitrate and ammonium (SNA) during a representative winter period in Shanghai. This source-tagged model system could simultaneously track spatial and temporal sources of SNA, which were apportioned to their respective primary precursors in a simulation run. The results indicate that in the study period, local emissions in Shanghai accounted for over 20% of SNA contributions and that Jiangsu and Shandong were the two major non-local sources. In particular, non-local emissions had higher contributions during recorded pollution periods. This suggests that the transportation of pollutants plays a key role in air pollution in Shanghai. The temporal contributions show that the emissions from the "current day" (emission contribution from the current day during which the model was simulating) contributed 60%-70% of the sulfate and ammonium concentrations but only 10%-20% of the nitrate concentration, while the previous days' contributions increased during the recorded pollution periods. Emissions that were released within three days contributed over 85% averagely for SNA in January 2013. To evaluate the source-tagged model system, the results were compared by sensitivity analysis (emission perturbation of -30%) and backward trajectory analysis. The consistency of the comparison results indicated that the source-tagged model system can track sources of SNA with reasonable accuracy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Estimation of contribution ratios of pollutant sources to a specific section based on an enhanced water quality model.

PubMed

Cao, Bibo; Li, Chuan; Liu, Yan; Zhao, Yue; Sha, Jian; Wang, Yuqiu

2015-05-01

Because water quality monitoring sections or sites could reflect the water quality status of rivers, surface water quality management based on water quality monitoring sections or sites would be effective. For the purpose of improving water quality of rivers, quantifying the contribution ratios of pollutant resources to a specific section is necessary. Because physical and chemical processes of nutrient pollutants are complex in water bodies, it is difficult to quantitatively compute the contribution ratios. However, water quality models have proved to be effective tools to estimate surface water quality. In this project, an enhanced QUAL2Kw model with an added module was applied to the Xin'anjiang Watershed, to obtain water quality information along the river and to assess the contribution ratios of each pollutant source to a certain section (the Jiekou state-controlled section). Model validation indicated that the results were reliable. Then, contribution ratios were analyzed through the added module. Results show that among the pollutant sources, the Lianjiang tributary contributes the largest part of total nitrogen (50.43%), total phosphorus (45.60%), ammonia nitrogen (32.90%), nitrate (nitrite + nitrate) nitrogen (47.73%), and organic nitrogen (37.87%). Furthermore, contribution ratios in different reaches varied along the river. Compared with pollutant loads ratios of different sources in the watershed, an analysis of contribution ratios of pollutant sources for each specific section, which takes the localized chemical and physical processes into consideration, was more suitable for local-regional water quality management. In summary, this method of analyzing the contribution ratios of pollutant sources to a specific section based on the QUAL2Kw model was found to support the improvement of the local environment.

A Global Land Use Regression Model for Nitrogen Dioxide Air Pollution

PubMed Central

Larkin, Andrew; Geddes, Jeffrey A.; Martin, Randall V.; Xiao, Qingyang; Liu, Yang; Marshall, Julian D.; Brauer, Michael; Hystad, Perry

2017-01-01

Nitrogen dioxide is a common air pollutant with growing evidence of health impacts independent of other common pollutants such as ozone and particulate matter. However, the global distribution of NO2 exposure and associated impacts on global health is still largely uncertain. To advance global exposure estimates we created a global nitrogen dioxide (NO2) land use regression model for 2011 using annual measurements from 5,220 air monitors in 58 countries. The model captured 54% of global NO2 variation, with a mean absolute error of 3.7 ppb. Regional performance varied from R2 = 0.42 (Africa) to 0.67 (South America). Repeated 10% cross-validation using bootstrap sampling (n=10,000) demonstrated robust performance with respect to air monitor sampling in North America, Europe, and Asia (adjusted R2 within 2%) but not for Africa and Oceania (adjusted R2 within 11%) where NO2 monitoring data are sparse. The final model included 10 variables that captured both between and within-city spatial gradients in NO2 concentrations. Variable contributions differed between continental regions but major roads within 100m and satellite-derived NO2 were consistently the strongest predictors. The resulting model will be made available and can be used for global risk assessments and health studies, particularly in countries without existing NO2 monitoring data or models. PMID:28520422

Improving Air Pollution Modeling Over The Po Valley Using Saharan Dust Transport Forecasts

NASA Astrophysics Data System (ADS)

Kishcha, P.; Carnevale, C.; Finzi, G.; Pisoni, E.; Volta, M.; Nickovic, S.; Alpert, P.

2012-04-01

Our study shows that Saharan dust can contribute significantly to PM10 concentrations in the Po Valley. This dust contribution should be taken into account when estimating the exceedance of pollution limits. The DREAM dust model has been used for several years for producing operational dust forecasts at Tel-Aviv University, Israel. DREAM has been producing daily forecasts of 3-D distribution of dust concentrations over the Mediterranean region, Middle East, Europe, and over the Atlantic Ocean (http://wind.tau.ac.il/dust8/dust.html). In the current study, DREAM dust forecasts were used to give better model estimates of the contribution of Saharan dust to PM10 concentration over the Po Valley, in Northern Italy. This was carried out by the integration of daily Saharan dust forecasts into a mesoscale Transport Chemical Aerosol Model (TCAM). The Po Valley in Northern Italy is frequently affected by high PM10 concentrations, where both natural and anthropogenic sources play a significant role. Our study of TCAM and DREAM integration was carried out for the period May 15 - June 30, 2007, when four significant dust events were observed. The integrated TCAM-DREAM model performance was evaluated by comparing PM10 measurements with modeled PM10 concentrations. First, Saharan dust impact on TCAM performance was analyzed at eleven remote PM10 sites which had the lowest level of air pollution (PM10 ≤ 14 μg/m3) over the period under consideration. For those remote sites, the observed high PM10 concentrations during dust events stood prominently on the background of low PM10 concentrations. At the remote sites, such a strong deviation from the background level can not be attributed to anthropogenic aerosol emissions because of their distance from anthropogenic sources. The observed maxima in PM10 concentration during dust events is evidence of dust aerosol near the surface in Northern Italy. During all dust events under consideration, the integrated TCAM-DREAM model produced

Modeling Ballasted Tracks for Pollutants

DOT National Transportation Integrated Search

2012-08-01

In this study, the Regional Transportation Districts (RTDs) light rail operations were examined for pollutant production and runoff. To : accomplish this, a laboratory study utilizing a rainfall-runoff facility was conducted. Input to this labo...

Spreadsheet WATERSHED modeling for nonpoint-source pollution management in a Wisconsin basin

USGS Publications Warehouse

Walker, J.F.; Pickard, S.A.; Sonzogni, W.C.

1989-01-01

Although several sophisticated nonpoint pollution models exist, few are available that are easy to use, cover a variety of conditions, and integrate a wide range of information to allow managers and planners to assess different control strategies. Here, a straightforward pollutant input accounting approach is presented in the form of an existing model (WATERSHED) that has been adapted to run on modern electronic spreadsheets. As an application, WATERSHED is used to assess options to improve the quality of highly eutrophic Delavan Lake in Wisconsin. WATERSHED is flexible in that several techniques, such as the Universal Soil Loss Equation or unit-area loadings, can be used to estimate nonpoint-source inputs. Once the model parameters are determined (and calibrated, if possible), the spreadsheet features can be used to conduct a sensitivity analysis of management options. In the case of Delavan Lake, it was concluded that, although some nonpoint controls were cost-effective, the overall reduction in phosphorus would be insufficient to measurably improve water quality.A straightforward pollutant input accounting approach is presented in the form of an existing model (WATERSHED) that has been adapted to run on modern electronic spreadsheets. As an application, WATERSHED is used to assess options to improve the quality of highly eutrophic Delavan Lake in Wisconsin. WATERSHED is flexible in that several techniques, such as the Universal Soil Loss Equation or unit-area loadings, can be used to estimate nonpoint-source inputs. Once the model parameters are determined (and calibrated, if possible), the spreadsheet features can be used to conduct a sensitivity analysis of management options. In the case of Delavan Lake, it was concluded that, although some nonpoint controls were cost-effective, the overall reduction in phosphorus would be insufficient to measurably improve water quality.

Investigation of the air pollutant distribution over Northeast Asia using Models-3/CMAQ

NASA Astrophysics Data System (ADS)

Kim, J. Y.; Ghim, Y. S.; Won, J.-G.; Yoon, S.-C.; Woo, J.-H.

2003-04-01

Northeast Asia is one of the most densely populated areas in the world. Huge amount of air pollutants emitted in the area is transported to the east along with prevailing westerlies. In spring of Northeast Asia, migratory anticyclones are frequent. Transport and distribution of air pollutants can be substantially altered according to the locations of anticyclones. In this work, two different synoptic meteorological conditions associated with different locations of anticyclones in May 1999 were identified. The distributions of gaseous and particulate pollutants in these meteorological conditions were predicted and compared. Models-3/CMAQ (USEPA Models-3/Community Multi-scale Air Quality) and MM5 (PSU/NCAR Mesoscale Modeling System) were used to predict air quality and meteorology, respectively. The modeling domain was 5,184 km x 3,456 km centering on the Korean Peninsula (130o N, 40o E). The grid size was 108 km x 108 km and the number of grids was 48 in the west-east direction and 32 in the south-north direction. The number of layers in the vertical direction was six to the height of 500 hPa. Emission data were taken from the Center for Global and Regional Environmental Research, University of Iowa for anthropogenic emissions and from GEIA (Global Emissions Inventory Activity) for biogenic emissions. The GDAPS (Global Data Assimilation and Prediction System) data of six-hour intervals were used for initial and boundary conditions of MM5.

Data-driven nonlinear optimisation of a simple air pollution dispersion model generating high resolution spatiotemporal exposure

NASA Astrophysics Data System (ADS)

Yuval; Bekhor, Shlomo; Broday, David M.

2013-11-01

Spatially detailed estimation of exposure to air pollutants in the urban environment is needed for many air pollution epidemiological studies. To benefit studies of acute effects of air pollution such exposure maps are required at high temporal resolution. This study introduces nonlinear optimisation framework that produces high resolution spatiotemporal exposure maps. An extensive traffic model output, serving as proxy for traffic emissions, is fitted via a nonlinear model embodying basic dispersion properties, to high temporal resolution routine observations of traffic-related air pollutant. An optimisation problem is formulated and solved at each time point to recover the unknown model parameters. These parameters are then used to produce a detailed concentration map of the pollutant for the whole area covered by the traffic model. Repeating the process for multiple time points results in the spatiotemporal concentration field. The exposure at any location and for any span of time can then be computed by temporal integration of the concentration time series at selected receptor locations for the durations of desired periods. The methodology is demonstrated for NO2 exposure using the output of a traffic model for the greater Tel Aviv area, Israel, and the half-hourly monitoring and meteorological data from the local air quality network. A leave-one-out cross-validation resulted in simulated half-hourly concentrations that are almost unbiased compared to the observations, with a mean error (ME) of 5.2 ppb, normalised mean error (NME) of 32%, 78% of the simulated values are within a factor of two (FAC2) of the observations, and the coefficient of determination (R2) is 0.6. The whole study period integrated exposure estimations are also unbiased compared with their corresponding observations, with ME of 2.5 ppb, NME of 18%, FAC2 of 100% and R2 that equals 0.62.

Conceptual model for assessing criteria air pollutants in a multipollutant context: A modified adverse outcome pathway approach.

PubMed

Buckley, Barbara; Farraj, Aimen

2015-09-01

Air pollution consists of a complex mixture of particulate and gaseous components. Individual criteria and other hazardous air pollutants have been linked to adverse respiratory and cardiovascular health outcomes. However, assessing risk of air pollutant mixtures is difficult since components are present in different combinations and concentrations in ambient air. Recent mechanistic studies have limited utility because of the inability to link measured changes to adverse outcomes that are relevant to risk assessment. New approaches are needed to address this challenge. The purpose of this manuscript is to describe a conceptual model, based on the adverse outcome pathway approach, which connects initiating events at the cellular and molecular level to population-wide impacts. This may facilitate hazard assessment of air pollution mixtures. In the case reports presented here, airway hyperresponsiveness and endothelial dysfunction are measurable endpoints that serve to integrate the effects of individual criteria air pollutants found in inhaled mixtures. This approach incorporates information from experimental and observational studies into a sequential series of higher order effects. The proposed model has the potential to facilitate multipollutant risk assessment by providing a framework that can be used to converge the effects of air pollutants in light of common underlying mechanisms. This approach may provide a ready-to-use tool to facilitate evaluation of health effects resulting from exposure to air pollution mixtures. Published by Elsevier Ireland Ltd.

DEVELOPMENT AND ANALYSIS OF AIR QUALITY MODELING SIMULATIONS FOR HAZARDOUS AIR POLLUTANTS

EPA Science Inventory

The concentrations of five hazardous air pollutants were simulated using the Community Multi Scale Air Quality (CMAQ) modeling system. Annual simulations were performed over the continental United States for the entire year of 2001 to support human exposure estimates. Results a...

ON THE USE OF NEXRAD STAGE IV DATA IN THE MULTIMEDIA MODELING OF POLLUTANT TRANSPORT

EPA Science Inventory

The Environmental Protection Agency (EPA) is designing the Multimedia Integrated Modeling System (MIMS) to model the cycling of pollutants and nutrients between the atmosphere and the earth's surface, including water bodies and groundwater. Our ability to accurately model both ...

Spherical LDH-Ag°-montmorillonite heterocoagulated system with a pH-dependent sol-gel structure for controlled accessibility of AgNPs immobilized on the clay lamellae.

PubMed

Deák, Ágota; Janovák, László; Tallósy, Szabolcs Péter; Bitó, Tamás; Sebők, Dániel; Buzás, Norbert; Pálinkó, István; Dékány, Imre

2015-02-17

Aqueous suspensions of spherical ZnMgAl-layered double hydroxides [LDH(sph)] and antibacterial silver nanoparticles (AgNPs) deposited on the lamellae of montmorillonite were used for the synthesis of composites, which behave like coherent gels at low pH (≲4.5) and incoherent sols at higher pH (≳4.5). The composition of the composite was chosen as LDH(sph)/Ag°-montm. = 25:75 wt % in order to ensure a sol-gel transition that can also be characterized by viscometry. This pH-sensitive heterocoagulated system consisting of oppositely charged colloid particles was suitable for the release of antimicrobial AgNPs immobilized on the clay lamellae via a pH-controlled gel-sol transition. The heterocoagulation process was also characterized by surface charge titration measurements. Spherical LDH/Ag°-montmorillonite composite samples were identified by X-ray diffraction (XRD) measurements. The morphological properties of the composites were studied, and the presence of the heterocoagulated structure was confirmed by scanning electron microscopy (SEM). The nanoscale structure of the LDH(sph)-Ag°-montmorillonite composite obtained was also verified by small-angle X-ray scattering (SAXS), and the rheological characteristics were studied at various pH values. The viscosity and yield value of the composite decreased by an order of magnitude upon increasing the pH from 3.0 to 5.5. The sol-gel transition of the composite suspension was reversible in the previously mentioned pH range.

A spatio-temporal model for estimating the long-term effects of air pollution on respiratory hospital admissions in Greater London.

PubMed

Rushworth, Alastair; Lee, Duncan; Mitchell, Richard

2014-07-01

It has long been known that air pollution is harmful to human health, as many epidemiological studies have been conducted into its effects. Collectively, these studies have investigated both the acute and chronic effects of pollution, with the latter typically based on individual level cohort designs that can be expensive to implement. As a result of the increasing availability of small-area statistics, ecological spatio-temporal study designs are also being used, with which a key statistical problem is allowing for residual spatio-temporal autocorrelation that remains after the covariate effects have been removed. We present a new model for estimating the effects of air pollution on human health, which allows for residual spatio-temporal autocorrelation, and a study into the long-term effects of air pollution on human health in Greater London, England. The individual and joint effects of different pollutants are explored, via the use of single pollutant models and multiple pollutant indices. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Simulation of West African air pollution during the DACCIWA experiment with the GEOS-Chem West African regional model.

NASA Astrophysics Data System (ADS)

Morris, Eleanor; Evans, Mathew

2017-04-01

Pollutant emissions from West African cities are forecast to increase rapidly in future years because of extensive economic and population growth, together with poorly regulated industrialisation and urbanisation. Observational constraints in this region are few, leading to poor understanding of present-day air pollution in this region. To increase our understanding of the processes controlling air pollutants over the region, airborne observations were made from three research aircraft based out of Lomé, Togo during the DACCIWA field campaign in June-July 2016. A new 0.25x0.3125 degree West Africa regional version of the GEOS-Chem offline chemical transport model has also been developed to explore the processes controlling pollutants over the region. We evaluate the model using the aircraft data and focus on primary (CO, SO2, NOx, VOCs) and secondary pollutants (O3, aerosol). We find significant differences between the model and the measurements for certain primary compounds which is indicative of significant uncertainties in the base (EDGAR) emissions. For CO (a general tracer of pollution) we evaluate the role of different emissions sources (transport, low temperature combustion, power generation) in determining its concentration in the region. We conclude that the leading cause of uncertainty in our simulation is associated with the emissions datasets and explore the impact of using differing datasets.

Light pollution: measuring and modelling skyglow. An application in two Portuguese reserves

NASA Astrophysics Data System (ADS)

Lima, Raul Cerveira Pinto Sousa

Outdoors human-made lighting at night causes sky glow, one of the effects of light pollution. Sky glow is rising with the growth of world population. Urban inhabitants are increasingly deprived from a starry sky. However, since light propagates to regions far from where it is produced, light pollution spreads to places where few or none artificial light at night existed, disturbing the quality of the night sky. In this work we assess for the first time the sky brightness of two regions in Portugal, the Peneda-Geres National Park, and the recently created Starlight Reserve Dark Sky® Alqueva. We used a portable unit, a Unihedron Sky Quality Meter-L (SQM-L), to measure the luminance of the night sky. We also tested the SQM-L in a laboratory to a more thorough analysis of the device, and to check the effect of polarization on the unit, suggested by our observations and other users. Our results suggest that the SQM-L is not affected by any measurable effect of polarization, but some guidelines to use the SQM-L in the field are provided based on our work. The data from the field measurement was used to compare to one light pollution propagation model (Kocifaj, 2007), using VIIRS DNB satellite upwards radiance as input to the model. The results obtained from the model are favourably compared to the field measurements. We proceeded to a set of tests with the model to find the best fit. Our best results were achieved by analysing the data by night rather than the global set of data. Our first results were used to apply to the classification of the region of Alqueva to a Starlight Tourism Destination. That classification was attained during the course of this work (December 2011). A guideline on the Peneda-Geres National Park was also implemented after our first results were provided. We believe we have achieved a set of results in a set of parallel issues all related to light pollution that we hope may contribute to the current knowledge on this area of research.

A model for managing sources of groundwater pollution

USGS Publications Warehouse

Gorelick, Steven M.

1982-01-01

The waste disposal capacity of a groundwater system can be maximized while maintaining water quality at specified locations by using a groundwater pollutant source management model that is based upon linear programing and numerical simulation. The decision variables of the management model are solute waste disposal rates at various facilities distributed over space. A concentration response matrix is used in the management model to describe transient solute transport and is developed using the U.S. Geological Survey solute transport simulation model. The management model was applied to a complex hypothetical groundwater system. Large-scale management models were formulated as dual linear programing problems to reduce numerical difficulties and computation time. Linear programing problems were solved using a numerically stable, available code. Optimal solutions to problems with successively longer management time horizons indicated that disposal schedules at some sites are relatively independent of the number of disposal periods. Optimal waste disposal schedules exhibited pulsing rather than constant disposal rates. Sensitivity analysis using parametric linear programing showed that a sharp reduction in total waste disposal potential occurs if disposal rates at any site are increased beyond their optimal values.

Autoclave mediated one-pot-one-minute synthesis of AgNPs and Au-Ag nanocomposite from Melia azedarach bark extract with antimicrobial activity against food pathogens.

PubMed

Pani, Alok; Lee, Joong Hee; Yun, Soon-Ii

2016-01-01

The increasing use of nanoparticles and nanocomposite in pharmaceutical and processed food industry have increased the demand for nontoxic and inert metallic nanostructures. Chemical and physical method of synthesis of nanostructures is most popular in industrial production, despite the fact that these methods are labor intensive and/or generate toxic effluents. There has been an increasing demand for rapid, ecofriendly and relatively cheaper synthesis of nanostructures. Here, we propose a strategy, for one-minute green synthesis of AgNPs and a one-pot one-minute green synthesis of Au-Ag nanocomposite, using Melia azedarach bark aqueous extract as reducing agent. The hydrothermal mechanism of the autoclave technology has been successfully used in this study to accelerate the nucleation and growth of nano-crystals. The study also presents high antimicrobial potential of the synthesized nano solutions against common food and water born pathogens. The multistep characterization and analysis of the synthesized nanomaterial samples, using UV-visible spectroscopy, ICP-MS, FT-IR, EDX, XRD, HR-TEM and FE-SEM, also reveal the reaction dynamics of AgNO3, AuCl3 and plant extract in synthesis of the nanoparticles and nanocomposite. The antimicrobial effectiveness of the synthesized Au-Ag nanocomposite, with high gold to silver ratio, reduces the dependency on the AgNPs, which is considered to be environmentally more toxic than the gold counterpart. We hope that this new strategy will change the present course of green synthesis. The rapidity of synthesis will also help in industrial scale green production of nanostructures using Melia azedarach.

Numerical modelling of vehicular pollution dispersion: The application of computational fluid dynamics techniques, a case study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vanderheyden, M.D.; Dajka, S.C.; Sinclair, R.

1997-12-31

Numerical modelling of vehicular emissions using the United States Environmental Protection Agency`s CALINE4 and CAL3QHC dispersion models to predict air quality impacts in the vicinity of roadways is a widely accepted means of evaluating vehicular emissions impacts. The numerical models account for atmospheric dispersion in both open or suburban terrains. When assessing roadways in urban areas with numerous large buildings, however, the models are unable to account for the complex airflows and therefore do not provide satisfactory estimates of pollutant concentrations. Either Wind Tunnel Modelling or Computational Fluid Dynamics (CFD) techniques can be used to assess the impact of vehiclemore » emissions in an urban core. This paper presents a case study where CFD is used to predict worst-case air quality impacts for two development configurations: an existing roadway configuration and a proposed configuration with an elevated pedestrian walkway. In assessing these configurations, worst-case meteorology and traffic conditions are modeled to allow for the prediction of pollutant concentrations due to vehicular emissions on two major streets in Hong Kong. The CFD modelling domain is divided up into thousands of control volumes. Each of these control volumes has a central point called a node where velocities, pollutant concentration and other auxiliary variables are calculated. The region of interest, the pedestrian link and its immediate surroundings, has a denser distribution of nodes in order to give a better resolution of local flow details. Separate CFD modelling runs were undertaken for each development configuration for wind direction increments of 15 degrees. For comparison of the development scenarios, pollutant concentrations (carbon monoxide, nitrogen dioxide and particulate matter) are predicted at up to 99 receptor nodes representing sensitive locations.« less

Spatio-temporal modelling of residential exposure to particulate matter and gaseous pollutants for the Heinz Nixdorf Recall Cohort

NASA Astrophysics Data System (ADS)

Nonnemacher, Michael; Jakobs, Hermann; Viehmann, Anja; Vanberg, Irene; Kessler, Christoph; Moebus, Susanne; Möhlenkamp, Stefan; Erbel, Raimund; Hoffmann, Barbara; Memmesheimer, Michael

2014-07-01

For the simultaneous analysis of short- and long-term effects of air pollution in the Heinz Nixdorf Recall Cohort a sophisticated exposure modelling was performed. The dispersion and chemistry transport model EURAD (European Air Pollution Dispersion) was used for the estimation of hourly concentrations of a number of pollutants for a horizontal grid with a cell size of 1 km² covering the whole study area (three large adjacent cities in a highly urbanized region in Western Germany) for the years 2000-2003 and 2006-2008. For each 1 km² cell we estimated the mean concentration by calculating daily means from the hourly concentrations modelled by the EURAD process. The modelled concentrations showed an overall tendency to decrease from 2001 to 2008 whereas the trend in the single grid cells and study period was inhomogeneous. Participant-related exposure slightly increased from 2001 to 2003 followed by a decrease from 2006 to 2008. The exposure modelling enables a very flexible exposure assessment compared to conventional modelling approaches which either use central monitoring or temporally static spatial contrasts. The modelling allows the calculation of an average exposure concentration for any place and time within the study region and study period with a high spatial and temporal resolution. This is important for the assessment of short-, medium and long-term effects of air pollution on human health in epidemiological studies.

GIS model for identifying urban areas vulnerable to noise pollution: case study

NASA Astrophysics Data System (ADS)

Bilaşco, Ştefan; Govor, Corina; Roşca, Sanda; Vescan, Iuliu; Filip, Sorin; Fodorean, Ioan

2017-04-01

The unprecedented expansion of the national car ownership over the last few years has been determined by economic growth and the need for the population and economic agents to reduce travel time in progressively expanding large urban centres. This has led to an increase in the level of road noise and a stronger impact on the quality of the environment. Noise pollution generated by means of transport represents one of the most important types of pollution with negative effects on a population's health in large urban areas. As a consequence, tolerable limits of sound intensity for the comfort of inhabitants have been determined worldwide and the generation of sound maps has been made compulsory in order to identify the vulnerable zones and to make recommendations how to decrease the negative impact on humans. In this context, the present study aims at presenting a GIS spatial analysis model-based methodology for identifying and mapping zones vulnerable to noise pollution. The developed GIS model is based on the analysis of all the components influencing sound propagation, represented as vector databases (points of sound intensity measurements, buildings, lands use, transport infrastructure), raster databases (DEM), and numerical databases (wind direction and speed, sound intensity). Secondly, the hourly changes (for representative hours) were analysed to identify the hotspots characterised by major traffic flows specific to rush hours. The validated results of the model are represented by GIS databases and useful maps for the local public administration to use as a source of information and in the process of making decisions.

Air Pollution Forecasts: An Overview

PubMed Central

Bai, Lu; Wang, Jianzhou; Lu, Haiyan

2018-01-01

Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies. PMID:29673227

Air Pollution Forecasts: An Overview.

PubMed

Bai, Lu; Wang, Jianzhou; Ma, Xuejiao; Lu, Haiyan

2018-04-17

Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

Catalytic and synergistic antibacterial potential of green synthesized silver nanoparticles: Their ecotoxicological evaluation on Poecillia reticulata.

PubMed

Borase, Hemant P; Patil, Chandrashekhar D; Salunkhe, Rahul B; Suryawanshi, Rahul K; Salunke, Bipinchandra K; Patil, Satish V

2014-01-01

In the present study, stable silver nanoparticles (AgNPs) were fabricated at a rapid rate from leaf extract of medicinally important plant Alstonia macrophylla. Biosynthesized AgNPs are of spherical shape and narrow size (70 nm), exhibiting a surface plasmon resonance peak at 435 nm, and a zeta potential of -30.8 mV and have a crystalline nature. A diverse biochemical consortium of protein, terpenoids, phenolics, and flavonoids in leaf extract of A. macrophylla was found to be responsible for AgNP synthesis as evidenced from qualitative-quantitative chemical analysis and Fourier transform infrared spectroscopy studies. Nitroaromatic compounds are anthropogenic pollutants with long-lasting environmental persistence and are needed to transform into less toxic derivatives. 4-Nitrophenol and p-nitroaniline were reduced to less hazardous and commercially useful 4-aminophenol and p-phenylenediamine by phytosynthesized AgNPs. Rate constants of 0.052 and 0.040 Min(-1) were calculated for 4-nitrophenol and p-nitroaniline reduction, respectively. Thin-layer chromatography also confirms the reduction of these nitroaromatic compounds. Combinational studies could be one of the strategies to overcome microbial resistance to antibiotics. In synergistic antibacterial assay, the highest increase in a fold area of 3.84 was reported against Staphylococcus aureus using a combination of AgNPs with penicillin. Biosynthesized AgNPs were found to be less toxic (LC50 = 9.13 ppm) than chemically synthesized AgNPs having a LC50 value of 2.86 ppm against nontarget fish Poecillia reticulata. Our green nanosynthesis method offers a faster rate of formation of stable AgNPs having antibacterial and catalytic potential with lower environmental toxicity. © 2013 International Union of Biochemistry and Molecular Biology, Inc.

Linking environmental effects to health impacts: a computer modelling approach for air pollution

PubMed Central

Mindell, J.; Barrowcliffe, R.

2005-01-01

Study objective and Setting: To develop a computer model, using a geographical information system (GIS), to quantify potential health effects of air pollution from a new energy from waste facility on the surrounding urban population. Design: Health impacts were included where evidence of causality is sufficiently convincing. The evidence for no threshold means that annual average increases in concentration can be used to model changes in outcome. The study combined the "contours" of additional pollutant concentrations for the new source generated by a dispersion model with a population database within a GIS, which is set up to calculate the product of the concentration increase with numbers of people exposed within each enumeration district exposure response coefficients, and the background rates of mortality and hospital admissions for several causes. Main results: The magnitude of health effects might result from the increased PM10 exposure is small—about 0.03 deaths each year in a population of 3 500 000, with 0.04 extra hospital admissions for respiratory disease. Long term exposure might bring forward 1.8–7.8 deaths in 30 years. Conclusions: This computer model is a feasible approach to estimating impacts on human health from environmental effects but sensitivity analyses are recommended. Relevance to clinical or professional practice: The availability of GIS and dispersion models on personal computers enables quantification of health effects resulting from the additional air pollution new industrial development might cause. This approach could also be used in environmental impact assessment. Care must be taken in presenting results to emphasise methodological limitations and uncertainties in the numbers. PMID:16286501

Evaluation of agricultural nonpoint source pollution potential risk over China with a Transformed-Agricultural Nonpoint Pollution Potential Index method.

PubMed

Yang, Fei; Xu, Zhencheng; Zhu, Yunqiang; He, Chansheng; Wu, Genyi; Qiu, Jin Rong; Fu, Qiang; Liu, Qingsong

2013-01-01

Agricultural nonpoint source (NPS) pollution has been the most important threat to water environment quality. Understanding the spatial distribution of NPS pollution potential risk is important for taking effective measures to control and reduce NPS pollution. A Transformed-Agricultural Nonpoint Pollution Potential Index (T-APPI) model was constructed for evaluating the national NPS pollution potential risk in this study; it was also combined with remote sensing and geographic information system techniques for evaluation on the large scale and at 1 km2 spatial resolution. This model considers many factors contributing to the NPS pollution as the original APPI model, summarized as four indicators of the runoff, sediment production, chemical use and the people and animal load. These four indicators were analysed in detail at 1 km2 spatial resolution throughout China. The T-APPI model distinguished the four indicators into pollution source factors and transport process factors; it also took their relationship into consideration. The studied results showed that T-APPI is a credible and convenient method for NPS pollution potential risk evaluation. The results also indicated that the highest NPS pollution potential risk is distributed in the middle-southern Jiangsu province. Several other regions, including the North China Plain, Chengdu Basin Plain, Jianghan Plain, cultivated lands in Guangdong and Guangxi provinces, also showed serious NPS pollution potential. This study can provide a scientific reference for predicting the future NPS pollution risk throughout China and may be helpful for taking reasonable and effective measures for preventing and controlling NPS pollution.

Comparison of modeled traffic exposure zones using on-road air pollution measurements

EPA Science Inventory

Modeled traffic data were used to develop traffic exposure zones (TEZs) such as traffic delay, high volume, and transit routes in the Research Triangle area of North Carolina (USA). On-road air pollution measurements of nitrogen dioxide (NO2), carbon monoxide (CO), carbon dioxid...

Modeling ephemeral gully erosion from unpaved roads: Equifinality and implications for scenario analysis

USDA-ARS?s Scientific Manuscript database

Modeling gully erosion in urban areas is challenging due to difficulties with equifinality and parameter identification, which complicates quantification of management impacts on runoff and sediment production. We calibrated a model (AnnAGNPS) of an ephemeral gully network that formed on unpaved ro...

Spatial variability of the effect of air pollution on term birth weight: evaluating influential factors using Bayesian hierarchical models.

PubMed

Li, Lianfa; Laurent, Olivier; Wu, Jun

2016-02-05

Epidemiological studies suggest that air pollution is adversely associated with pregnancy outcomes. Such associations may be modified by spatially-varying factors including socio-demographic characteristics, land-use patterns and unaccounted exposures. Yet, few studies have systematically investigated the impact of these factors on spatial variability of the air pollution's effects. This study aimed to examine spatial variability of the effects of air pollution on term birth weight across Census tracts and the influence of tract-level factors on such variability. We obtained over 900,000 birth records from 2001 to 2008 in Los Angeles County, California, USA. Air pollution exposure was modeled at individual level for nitrogen dioxide (NO2) and nitrogen oxides (NOx) using spatiotemporal models. Two-stage Bayesian hierarchical non-linear models were developed to (1) quantify the associations between air pollution exposure and term birth weight within each tract; and (2) examine the socio-demographic, land-use, and exposure-related factors contributing to the between-tract variability of the associations between air pollution and term birth weight. Higher air pollution exposure was associated with lower term birth weight (average posterior effects: -14.7 (95 % CI: -19.8, -9.7) g per 10 ppb increment in NO2 and -6.9 (95 % CI: -12.9, -0.9) g per 10 ppb increment in NOx). The variation of the association across Census tracts was significantly influenced by the tract-level socio-demographic, exposure-related and land-use factors. Our models captured the complex non-linear relationship between these factors and the associations between air pollution and term birth weight: we observed the thresholds from which the influence of the tract-level factors was markedly exacerbated or attenuated. Exacerbating factors might reflect additional exposure to environmental insults or lower socio-economic status with higher vulnerability, whereas attenuating factors might indicate reduced

An analytical model for non-conservative pollutants mixing in the surf zone.

PubMed

Ki, Seo Jin; Hwang, Jin Hwan; Kang, Joo-Hyon; Kim, Joon Ha

2009-01-01

Accurate simulation of the surf zone is a prerequisite to improve beach management as well as to understand the fundamentals of fate and transport of contaminants. In the present study, a diagnostic model modified from a classic solute model is provided to illuminate non-conservative pollutants behavior in the surf zone. To readily understand controlling processes in the surf zone, a new dimensionless quantity is employed with index of kappa number (K, a ratio of inactivation rate to transport rate of microbial pollutant in the surf zone), which was then evaluated under different environmental frames during a week simulation period. The sensitivity analysis showed that hydrodynamics and concentration gradients in the surf zone mostly depend on n (number of rip currents), indicating that n should be carefully adjusted in the model. The simulation results reveal, furthermore, that large deviation typically occurs in the daytime, signifying inactivation of fecal indicator bacteria is the main process to control surf zone water quality during the day. Overall, the analytical model shows a good agreement between predicted and synthetic data (R(2) = 0.51 and 0.67 for FC and ENT, respectively) for the simulated period, amplifying its potential use in the surf zone modelling. It is recommended that when the dimensionless index is much larger than 0.5, the present modified model can predict better than the conventional model, but if index is smaller than 0.5, the conventional model is more efficient with respect to time and cost.

Meteorological and air pollution modeling for an urban airport

NASA Technical Reports Server (NTRS)

Swan, P. R.; Lee, I. Y.

1980-01-01

Results are presented of numerical experiments modeling meteorology, multiple pollutant sources, and nonlinear photochemical reactions for the case of an airport in a large urban area with complex terrain. A planetary boundary-layer model which predicts the mixing depth and generates wind, moisture, and temperature fields was used; it utilizes only surface and synoptic boundary conditions as input data. A version of the Hecht-Seinfeld-Dodge chemical kinetics model is integrated with a new, rapid numerical technique; both the San Francisco Bay Area Air Quality Management District source inventory and the San Jose Airport aircraft inventory are utilized. The air quality model results are presented in contour plots; the combined results illustrate that the highly nonlinear interactions which are present require that the chemistry and meteorology be considered simultaneously to make a valid assessment of the effects of individual sources on regional air quality.

A GIS-based multi-source and multi-box modeling approach (GMSMB) for air pollution assessment--a North American case study.

PubMed

Wang, Bao-Zhen; Chen, Zhi

2013-01-01

This article presents a GIS-based multi-source and multi-box modeling approach (GMSMB) to predict the spatial concentration distributions of airborne pollutant on local and regional scales. In this method, an extended multi-box model combined with a multi-source and multi-grid Gaussian model are developed within the GIS framework to examine the contributions from both point- and area-source emissions. By using GIS, a large amount of data including emission sources, air quality monitoring, meteorological data, and spatial location information required for air quality modeling are brought into an integrated modeling environment. It helps more details of spatial variation in source distribution and meteorological condition to be quantitatively analyzed. The developed modeling approach has been examined to predict the spatial concentration distribution of four air pollutants (CO, NO(2), SO(2) and PM(2.5)) for the State of California. The modeling results are compared with the monitoring data. Good agreement is acquired which demonstrated that the developed modeling approach could deliver an effective air pollution assessment on both regional and local scales to support air pollution control and management planning.

Effects of laser ablated silver nanoparticles on Lemna minor.

PubMed

Üçüncü, Esra; Özkan, Alper D; Kurşungöz, Canan; Ülger, Zeynep E; Ölmez, Tolga T; Tekinay, Turgay; Ortaç, Bülend; Tunca, Evren

2014-08-01

The present study investigates and models the effect of laser ablated silver nanoparticles (AgNPs) on the development of the aquatic macrophyte Lemna minor. Toxic effects of five different AgNP concentrations (8, 16, 32, 96 and 128 μg L(-1)) on L. minor were recorded over seven days under simulated natural conditions. Biosorption of AgNPs by L. minor was modeled using four sorption isotherms, and the sorption behavior was found to agree most closely with the Langmuir-Freundlich model (R(2)=0.997). While toxic effects of AgNPs could be observed in all models and concentrations, the greatest increase in toxicity was in the 8-32 μg L(-1) range. Dry weight- and frond number-based inhibition experiments suggest that growth inhibition does not necessarily scale with AgNP concentration, and that slight fluctuations in inhibition rates exist over certain concentration ranges. Very close fits (R(2)=0.999) were obtained for all removal models, suggesting that the fluctuations are not caused by experimental variation. In addition, L. minor was found to be a successful bioremediation agent for AgNPs, and displayed higher removal rates for increasing AgNP doses. FT-IR spectroscopy suggests that carbonyl groups are involved in AgNP remediation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Air Quality Modeling in Support of the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS)

EPA Science Inventory

A major challenge in traffic-related air pollution exposure studies is the lack of information regarding pollutant exposure characterization. Air quality modeling can provide spatially and temporally varying exposure estimates for examining relationships between traffic-related a...

Modeling short-term concentration fluctuations of semi-volatile pollutants in the soil-plant-atmosphere system.

PubMed

Bao, Zhongwen; Haberer, Christina M; Maier, Uli; Beckingham, Barbara; Amos, Richard T; Grathwohl, Peter

2016-11-01

Temperature changes can drive cycling of semi-volatile pollutants between different environmental compartments (e.g. atmosphere, soil, plants). To evaluate the impact of daily temperature changes on atmospheric concentration fluctuations we employed a physically based model coupling soil, plants and the atmosphere, which accounts for heat transport, effective gas diffusion, sorption and biodegradation in the soil as well as eddy diffusion and photochemical oxidation in the atmospheric boundary layer of varying heights. The model results suggest that temperature-driven re-volatilization and uptake in soils cannot fully explain significant diurnal concentration fluctuations of atmospheric pollutants as for example observed for polychlorinated biphenyls (PCBs). This holds even for relatively low water contents (high gas diffusivity) and high sorption capacity of the topsoil (high organic carbon content and high pollutant concentration in the topsoil). Observed concentration fluctuations, however, can be easily matched if a rapidly-exchanging environmental compartment, such as a plant layer, is introduced. At elevated temperatures, plants release organic pollutants, which are rapidly distributed in the atmosphere by eddy diffusion. For photosensitive compounds, e.g. some polycyclic aromatic hydrocarbons (PAHs), decreasing atmospheric concentrations would be expected during daytime for the bare soil scenario. This decline is buffered by a plant layer, which acts as a ground-level reservoir. The modeling results emphasize the importance of a rapidly-exchanging compartment above ground to explain short-term atmospheric concentration fluctuations. Copyright © 2016 Elsevier B.V. All rights reserved.

Validity of a traffic air pollutant dispersion model to assess exposure to fine particles.

PubMed

Kostrzewa, Aude; Reungoat, Patrice; Raherison, Chantal

2009-08-01

Fine particles (PM(2.5)) are an important component of air pollution. Epidemiological studies have shown health effects due to ambient air particles, particularly allergies in children. Since the main difficulty is to determine exposure to such pollution, traffic air pollutant (TAP) dispersions models have been developed to improve the estimation of individual exposure levels. One such model, the ExTra index, has been validated for nitrogen oxide concentrations but not for other pollutants. The purpose of this study was to assess the validity of the ExTra index to assess PM(2.5) exposure. We compared PM(2.5) concentrations calculated by the ExTra index to reference measures (passive samplers situated under the covered part of the playground), in 15 schools in Bordeaux, in 2000. First, we collected the input data required by the ExTra index: background and local pollution depending on traffic, meteorology and topography. Second, the ExTra index was calculated for each school. Statistical analysis consisted of a graphic description; then, we calculated an intraclass correlation coefficient. Concentrations calculated with the ExTra index and the reference method were similar. The ExTra index underestimated exposure by 2.2 microg m(-3) on average compared to the reference method. The intraclass correlation coefficient was 0.85 and its 95% confidence interval was [0.62; 0.95]. The results suggest that the ExTra index provides an assessment of PM(2.5) exposure similar to that of the reference method. Although caution is required in interpreting these results owing to the small number of sites, the ExTra index could be a useful epidemiological tool for reconstructing individual exposure, an important challenge in epidemiology.

Framing air pollution epidemiology in terms of population interventions, with applications to multipollutant modeling.

PubMed

Snowden, Jonathan M; Reid, Colleen E; Tager, Ira B

2015-03-01

Air pollution epidemiology continues moving toward the study of mixtures and multipollutant modeling. Simultaneously, there is a movement in epidemiology to estimate policy-relevant health effects that can be understood in reference to specific interventions. Scaling regression coefficients from a regression model by an interquartile range (IQR) is one common approach to presenting multipollutant health effect estimates. We are unaware of guidance on how to interpret these effect estimates as an intervention. To illustrate the issues of interpretability of IQR-scaled air pollution health effects, we analyzed how daily concentration changes in 2 air pollutants (nitrogen dioxide and particulate matter with aerodynamic diameter ≤ 2.5 μm) related to one another within 2 seasons (summer and winter), within 3 cities with distinct air pollution profiles (Burbank, California; Houston, Texas; and Pittsburgh, Pennsylvania). In each city season, we examined how realistically IQR scaling in multipollutant lag-1 time-series studies reflects a hypothetical intervention that is possible given the observed data. We proposed 2 causal conditions to explicitly link IQR-scaled effects to a clearly defined hypothetical intervention. Condition 1 specified that the index pollutant had to experience a daily concentration change of greater than 1 IQR, reflecting the notion that the IQR is an appropriate measure of variability between consecutive days. Condition 2 specified that the copollutant had to remain relatively constant. We found that in some city seasons, there were very few instances in which these conditions were satisfied (eg, 1 day in Pittsburgh during summer). We discuss the practical implications of IQR scaling and suggest alternative approaches to presenting multipollutant effects that are supported by empirical data.

An enhanced export coefficient based optimization model for supporting agricultural nonpoint source pollution mitigation under uncertainty.

PubMed

Rong, Qiangqiang; Cai, Yanpeng; Chen, Bing; Yue, Wencong; Yin, Xin'an; Tan, Qian

2017-02-15

In this research, an export coefficient based dual inexact two-stage stochastic credibility constrained programming (ECDITSCCP) model was developed through integrating an improved export coefficient model (ECM), interval linear programming (ILP), fuzzy credibility constrained programming (FCCP) and a fuzzy expected value equation within a general two stage programming (TSP) framework. The proposed ECDITSCCP model can effectively address multiple uncertainties expressed as random variables, fuzzy numbers, pure and dual intervals. Also, the model can provide a direct linkage between pre-regulated management policies and the associated economic implications. Moreover, the solutions under multiple credibility levels can be obtained for providing potential decision alternatives for decision makers. The proposed model was then applied to identify optimal land use structures for agricultural NPS pollution mitigation in a representative upstream subcatchment of the Miyun Reservoir watershed in north China. Optimal solutions of the model were successfully obtained, indicating desired land use patterns and nutrient discharge schemes to get a maximum agricultural system benefits under a limited discharge permit. Also, numerous results under multiple credibility levels could provide policy makers with several options, which could help get an appropriate balance between system benefits and pollution mitigation. The developed ECDITSCCP model can be effectively applied to addressing the uncertain information in agricultural systems and shows great applicability to the land use adjustment for agricultural NPS pollution mitigation. Copyright © 2016 Elsevier B.V. All rights reserved.

A mathematical model for jet engine combustor pollutant emissions

NASA Technical Reports Server (NTRS)

Boccio, J. L.; Weilerstein, G.; Edelman, R. B.

1973-01-01

Mathematical modeling for the description of the origin and disposition of combustion-generated pollutants in gas turbines is presented. A unified model in modular form is proposed which includes kinetics, recirculation, turbulent mixing, multiphase flow effects, swirl and secondary air injection. Subelements of the overall model were applied to data relevant to laboratory reactors and practical combustor configurations. Comparisons between the theory and available data show excellent agreement for basic CO/H2/Air chemical systems. For hydrocarbons the trends are predicted well including higher-than-equilibrium NO levels within the fuel rich regime. Although the need for improved accuracy in fuel rich combustion is indicated, comparisons with actual jet engine data in terms of the effect of combustor-inlet temperature is excellent. In addition, excellent agreement with data is obtained regarding reduced NO emissions with water droplet and steam injection.

A numerical model simulation of the regional air pollution meteorology of the greater Chesapeake Bay area - Summer day case study

NASA Technical Reports Server (NTRS)

Segal, M.; Pielke, R. A.; Mcnider, R. T.; Mcdougal, D. S.

1982-01-01

The mesoscale numerical model of the University of Virginia (UVMM), has been applied to the greater Chesapeake Bay area in order to provide a detailed description of the air pollution meteorology during a typical summer day. This model provides state of the art simulations for land-sea thermally induced circulations. The model-predicted results agree favorably with available observed data. The effects of synoptic flow and sea breeze coupling on air pollution meteorological characteristics in this region, are demonstrated by a spatial and temporal presentation of various model predicted fields. A transport analysis based on predicted wind velocities indicated possible recirculation of pollutants back onto the Atlantic coast due to the sea breeze circulation.

A review of methods for predicting air pollution dispersion

NASA Technical Reports Server (NTRS)

Mathis, J. J., Jr.; Grose, W. L.

1973-01-01

Air pollution modeling, and problem areas in air pollution dispersion modeling were surveyed. Emission source inventory, meteorological data, and turbulent diffusion are discussed in terms of developing a dispersion model. Existing mathematical models of urban air pollution, and highway and airport models are discussed along with their limitations. Recommendations for improving modeling capabilities are included.

Numerical modeling of flows and pollutant dispersion within and above urban street canyons under unstable thermal stratification by large-eddy simulation

NASA Astrophysics Data System (ADS)

Chan, Ming-Chung; Liu, Chun-Ho

2013-04-01

Recently, with the ever increasing urban areas in developing countries, the problem of air pollution due to vehicular exhaust arouses the concern of different groups of people. Understanding how different factors, such as urban morphology, meteorological conditions and human activities, affect the characteristics of street canyon ventilation, pollutant dispersion above urban areas and pollutant re-entrainment from the shear layer can help us improve air pollution control strategies. Among the factors mentioned above, thermal stratification is a significant one determining the pollutant transport behaviors in certain situation, e.g. when the urban surface is heated by strong solar radiation, which, however, is still not widely explored. The objective of this study is to gain an in-depth understanding of the effects of unstable thermal stratification on the flows and pollutant dispersion within and above urban street canyons through numerical modeling using large-eddy simulation (LES). In this study, LES equipped with one-equation subgrid-scale (SGS) model is employed to model the flows and pollutant dispersion within and above two-dimensional (2D) urban street canyons (flanked by idealized buildings, which are square solid bars in these models) under different intensities of unstable thermal stratifications. Three building-height-to-street-width (aspect) ratios, 0.5, 1 and 2, are included in this study as a representation of different building densities. The prevailing wind flow above the urban canopy is driven by background pressure gradient, which is perpendicular to the street axis, while the condition of unstable thermal stratification is induced by applying a higher uniform temperature on the no-slip urban surface. The relative importance between stratification and background wind is characterized by the Richardson number, with zero value as a neutral case and negative value as an unstable case. The buoyancy force is modeled by Boussinesq approximation and the

Application of Model Project Based Learning on Integrated Science in Water Pollution

NASA Astrophysics Data System (ADS)

Yamin, Y.; Permanasari, A.; Redjeki, S.; Sopandi, W.

2017-09-01

The function of this research was to analyze the influence model Project Based Learning (PjBl) on integrated science about the concept mastery for junior high school students. Method used for this research constitutes the quasi of experiment method. Population and sample for this research are the students junior high school in Bandung as many as two classes to be experiment and control class. The instrument that used for this research is the test concept mastery, assessment questionnaire of product and the questionnaire responses of the student about learning integrated science. Based on the result of this research get some data that with accomplishment the model of PjBl. Learning authority of integrated science can increase the concept mastery for junior high school students. The highest increase in the theme of pollution water is in the concept of mixtures and the separation method. The students give a positive response in learning of integrated science for the theme of pollution of the water used model PjBL with questionnaire of the opinion aspect in amount of 83.5%, the anxiety of the students in amount of 95.5%, the profit learning model of PjBL in amount of 96.25% and profit learning of integrated science in amount of 95.75%.

Impact of surface coating and environmental conditions on the fate and transport of silver nanoparticles in the aquatic environment.

PubMed

Ellis, Laura-Jayne A; Valsami-Jones, Eugenia; Lead, Jamie R; Baalousha, Mohammed

2016-10-15

The role of surface coating (polyvinylpyrrolidone (PVP) and citrate) and water chemistry on the fate and behavior of AgNPs in aquatic microcosms is reported in this study. The migration and transformation of the AgNPs was examined in low (ultrapure water-UPW) and high ionic strength (moderately hard water - MHW) preparations, and in the presence of modeled natural organic matter (NOM) of Suwannee River Fulvic Acid (SRFA). The migration and fate of the AgNPs in the microcosms was validated using a sedimentation-diffusion model and the aggregation behavior was monitored by UV-visible spectrometry (UV-vis). Dissolved and particulate Ag concentrations (% Ag) were analyzed by ultrafiltration methods. Imaging of the AgNPs was captured using transmission electron microscopy (TEM). Results indicate that PVP-coated AgNPs (PVP-AgNPs) remained stable for 28days with similarly distributed concentrations of the PVP-AgNPs throughout the columns in each of the water conditions after approximately 96h (4days). The sedimentation-diffusion model confirmed PVP-AgNP stability in each condition, by showing diffusion dominated transport by using the original unaltered AgNP sizes to fit the parameters. In comparison, citrate AgNPs were largely unstable in the more complex water preparations (MHW). In MHW, aggregation dominated behavior followed by sedimentation/dissolution controlled transport was observed. The addition of SRFA to MHW resulted in small stabilizing effects, to the citrate coated AgNPs, producing smaller sized AgNPs (TEM) and mixed sedimentation and diffusion migration compared the studies absent of SRFA. The results suggest that surface coating and solution chemistry has a major impact on AgNP stability, furthermore the corresponding modeling will support the experimental understanding of the overall fate of AgNPs in the environment. Copyright © 2016 Elsevier B.V. All rights reserved.

Bayesian model averaging method for evaluating associations between air pollution and respiratory mortality: a time-series study.

PubMed

Fang, Xin; Li, Runkui; Kan, Haidong; Bottai, Matteo; Fang, Fang; Cao, Yang

2016-08-16

To demonstrate an application of Bayesian model averaging (BMA) with generalised additive mixed models (GAMM) and provide a novel modelling technique to assess the association between inhalable coarse particles (PM10) and respiratory mortality in time-series studies. A time-series study using regional death registry between 2009 and 2010. 8 districts in a large metropolitan area in Northern China. 9559 permanent residents of the 8 districts who died of respiratory diseases between 2009 and 2010. Per cent increase in daily respiratory mortality rate (MR) per interquartile range (IQR) increase of PM10 concentration and corresponding 95% confidence interval (CI) in single-pollutant and multipollutant (including NOx, CO) models. The Bayesian model averaged GAMM (GAMM+BMA) and the optimal GAMM of PM10, multipollutants and principal components (PCs) of multipollutants showed comparable results for the effect of PM10 on daily respiratory MR, that is, one IQR increase in PM10 concentration corresponded to 1.38% vs 1.39%, 1.81% vs 1.83% and 0.87% vs 0.88% increase, respectively, in daily respiratory MR. However, GAMM+BMA gave slightly but noticeable wider CIs for the single-pollutant model (-1.09 to 4.28 vs -1.08 to 3.93) and the PCs-based model (-2.23 to 4.07 vs -2.03 vs 3.88). The CIs of the multiple-pollutant model from two methods are similar, that is, -1.12 to 4.85 versus -1.11 versus 4.83. The BMA method may represent a useful tool for modelling uncertainty in time-series studies when evaluating the effect of air pollution on fatal health outcomes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Bayesian model averaging method for evaluating associations between air pollution and respiratory mortality: a time-series study

PubMed Central

Fang, Xin; Li, Runkui; Kan, Haidong; Bottai, Matteo; Fang, Fang

2016-01-01

Objective To demonstrate an application of Bayesian model averaging (BMA) with generalised additive mixed models (GAMM) and provide a novel modelling technique to assess the association between inhalable coarse particles (PM10) and respiratory mortality in time-series studies. Design A time-series study using regional death registry between 2009 and 2010. Setting 8 districts in a large metropolitan area in Northern China. Participants 9559 permanent residents of the 8 districts who died of respiratory diseases between 2009 and 2010. Main outcome measures Per cent increase in daily respiratory mortality rate (MR) per interquartile range (IQR) increase of PM10 concentration and corresponding 95% confidence interval (CI) in single-pollutant and multipollutant (including NOx, CO) models. Results The Bayesian model averaged GAMM (GAMM+BMA) and the optimal GAMM of PM10, multipollutants and principal components (PCs) of multipollutants showed comparable results for the effect of PM10 on daily respiratory MR, that is, one IQR increase in PM10 concentration corresponded to 1.38% vs 1.39%, 1.81% vs 1.83% and 0.87% vs 0.88% increase, respectively, in daily respiratory MR. However, GAMM+BMA gave slightly but noticeable wider CIs for the single-pollutant model (−1.09 to 4.28 vs −1.08 to 3.93) and the PCs-based model (−2.23 to 4.07 vs −2.03 vs 3.88). The CIs of the multiple-pollutant model from two methods are similar, that is, −1.12 to 4.85 versus −1.11 versus 4.83. Conclusions The BMA method may represent a useful tool for modelling uncertainty in time-series studies when evaluating the effect of air pollution on fatal health outcomes. PMID:27531727

Modeling Air Pollution Exposure Metrics for the Diabetes and Environment Panel Study (DEPS)

EPA Science Inventory

Air pollution health studies of fine particulate matter (PM) often use outdoor concentrations as exposure surrogates. To improve exposure assessments, we developed and evaluated an exposure model for individuals (EMI), which predicts five tiers of individual-level exposure metric...

POPULATION-BASED EXPOSURE MODELING FOR AIR POLLUTANTS AT EPA'S NATIONAL EXPOSURE RESEARCH LABORATORY

EPA Science Inventory

The US EPA's National Exposure Research Laboratory (NERL) has been developing, applying, and evaluating population-based exposure models to improve our understanding of the variability in personal exposure to air pollutants. Estimates of population variability are needed for E...

Modeling the contribution of point sources and non-point sources to Thachin River water pollution.

PubMed

Schaffner, Monika; Bader, Hans-Peter; Scheidegger, Ruth

2009-08-15

Major rivers in developing and emerging countries suffer increasingly of severe degradation of water quality. The current study uses a mathematical Material Flow Analysis (MMFA) as a complementary approach to address the degradation of river water quality due to nutrient pollution in the Thachin River Basin in Central Thailand. This paper gives an overview of the origins and flow paths of the various point- and non-point pollution sources in the Thachin River Basin (in terms of nitrogen and phosphorus) and quantifies their relative importance within the system. The key parameters influencing the main nutrient flows are determined and possible mitigation measures discussed. The results show that aquaculture (as a point source) and rice farming (as a non-point source) are the key nutrient sources in the Thachin River Basin. Other point sources such as pig farms, households and industries, which were previously cited as the most relevant pollution sources in terms of organic pollution, play less significant roles in comparison. This order of importance shifts when considering the model results for the provincial level. Crosschecks with secondary data and field studies confirm the plausibility of our simulations. Specific nutrient loads for the pollution sources are derived; these can be used for a first broad quantification of nutrient pollution in comparable river basins. Based on an identification of the sensitive model parameters, possible mitigation scenarios are determined and their potential to reduce the nutrient load evaluated. A comparison of simulated nutrient loads with measured nutrient concentrations shows that nutrient retention in the river system may be significant. Sedimentation in the slow flowing surface water network as well as nitrogen emission to the air from the warm oxygen deficient waters are certainly partly responsible, but also wetlands along the river banks could play an important role as nutrient sinks.

Impact of intercontinental pollution transport on North American ozone air pollution: an HTAP phase 2 multi-model study

NASA Astrophysics Data System (ADS)

Huang, Min; Carmichael, Gregory R.; Pierce, R. Bradley; Jo, Duseong S.; Park, Rokjin J.; Flemming, Johannes; Emmons, Louisa K.; Bowman, Kevin W.; Henze, Daven K.; Davila, Yanko; Sudo, Kengo; Eiof Jonson, Jan; Tronstad Lund, Marianne; Janssens-Maenhout, Greet; Dentener, Frank J.; Keating, Terry J.; Oetjen, Hilke; Payne, Vivienne H.

2017-05-01

The recent update on the US National Ambient Air Quality Standards (NAAQS) of the ground-level ozone (O3) can benefit from a better understanding of its source contributions in different US regions during recent years. In the Hemispheric Transport of Air Pollution experiment phase 1 (HTAP1), various global models were used to determine the O3 source-receptor (SR) relationships among three continents in the Northern Hemisphere in 2001. In support of the HTAP phase 2 (HTAP2) experiment that studies more recent years and involves higher-resolution global models and regional models' participation, we conduct a number of regional-scale Sulfur Transport and dEposition Model (STEM) air quality base and sensitivity simulations over North America during May-June 2010. STEM's top and lateral chemical boundary conditions were downscaled from three global chemical transport models' (i.e., GEOS-Chem, RAQMS, and ECMWF C-IFS) base and sensitivity simulations in which the East Asian (EAS) anthropogenic emissions were reduced by 20 %. The mean differences between STEM surface O3 sensitivities to the emission changes and its corresponding boundary condition model's are smaller than those among its boundary condition models, in terms of the regional/period-mean (< 10 %) and the spatial distributions. An additional STEM simulation was performed in which the boundary conditions were downscaled from a RAQMS (Realtime Air Quality Modeling System) simulation without EAS anthropogenic emissions. The scalability of O3 sensitivities to the size of the emission perturbation is spatially varying, and the full (i.e., based on a 100 % emission reduction) source contribution obtained from linearly scaling the North American mean O3 sensitivities to a 20 % reduction in the EAS anthropogenic emissions may be underestimated by at least 10 %. The three boundary condition models' mean O3 sensitivities to the 20 % EAS emission perturbations are ˜ 8 % (May-June 2010)/˜ 11 % (2010 annual) lower than

Impact of intercontinental pollution transport on North American ozone air pollution: an HTAP phase 2 multi-model study.

PubMed

Huang, Min; Carmichael, Gregory R; Pierce, R Bradley; Jo, Duseong S; Park, Rokjin J; Flemming, Johannes; Emmons, Louisa K; Bowman, Kevin W; Henze, Daven K; Davila, Yanko; Sudo, Kengo; Jonson, Jan Eiof; Lund, Marianne Tronstad; Janssens-Maenhout, Greet; Dentener, Frank J; Keating, Terry J; Oetjen, Hilke; Payne, Vivienne H

2017-05-08

The recent update on the US National Ambient Air Quality Standards (NAAQS) of the ground-level ozone (O 3 / can benefit from a better understanding of its source contributions in different US regions during recent years. In the Hemispheric Transport of Air Pollution experiment phase 1 (HTAP1), various global models were used to determine the O 3 source-receptor (SR) relationships among three continents in the Northern Hemisphere in 2001. In support of the HTAP phase 2 (HTAP2) experiment that studies more recent years and involves higher-resolution global models and regional models' participation, we conduct a number of regional-scale Sulfur Transport and dEposition Model (STEM) air quality base and sensitivity simulations over North America during May-June 2010. STEM's top and lateral chemical boundary conditions were downscaled from three global chemical transport models' (i.e., GEOS-Chem, RAQMS, and ECMWF C-IFS) base and sensitivity simulations in which the East Asian (EAS) anthropogenic emissions were reduced by 20 %. The mean differences between STEM surface O 3 sensitivities to the emission changes and its corresponding boundary condition model's are smaller than those among its boundary condition models, in terms of the regional/period-mean (<10 %) and the spatial distributions. An additional STEM simulation was performed in which the boundary conditions were downscaled from a RAQMS (Realtime Air Quality Modeling System) simulation without EAS anthropogenic emissions. The scalability of O 3 sensitivities to the size of the emission perturbation is spatially varying, and the full (i.e., based on a 100% emission reduction) source contribution obtained from linearly scaling the North American mean O 3 sensitivities to a 20% reduction in the EAS anthropogenic emissions may be underestimated by at least 10 %. The three boundary condition models' mean O 3 sensitivities to the 20% EAS emission perturbations are ~8% (May-June 2010)/~11% (2010 annual) lower than those

Model calculated global, regional and megacity premature mortality due to air pollution

NASA Astrophysics Data System (ADS)

Lelieveld, J.; Barlas, C.; Giannadaki, D.; Pozzer, A.

2013-03-01

Air pollution by fine particulate matter (PM2.5) and ozone (O3) has increased strongly with industrialization and urbanization. We estimated the premature mortality rates and the years of human life lost (YLL) caused by anthropogenic PM2.5 and O3 in 2005 for epidemiological regions defined by the World Health Organization. We carried out high-resolution global model calculations to resolve urban and industrial regions in greater detail compared to previous work. We applied a health impact function to estimate premature mortality for people of 30 yr and older, using parameters derived from epidemiological cohort studies. Our results suggest that especially in large countries with extensive suburban and rural populations, air pollution-induced mortality rates have previously been underestimated. We calculate a global respiratory mortality of about 773 thousand yr-1 (YLL ≈ 5.2 million yr-1), 186 thousand yr-1 by lung cancer (YLL ≈ 1.7 million yr-1) and 2.0 million yr-1 by cardiovascular disease (YLL ≈ 14.3 million yr-1). The global mean per capita mortality caused by air pollution is about 0.1 % yr-1. The highest premature mortality rates are found in the Southeast Asia and Western Pacific regions (about 25% and 46% of the global rate, respectively) where more than a dozen of the most highly polluted megacities are located.

Fertilizer Induced Nitrate Pollution in RCW: Calibration of the DNDC Model

NASA Astrophysics Data System (ADS)

El Hailouch, E.; Hornberger, G.; Crane, J. W.

2012-12-01

Fertilizer is widely used among urban and suburban households due to the socially driven attention of homeowners to lawn appearance. With high nitrogen content, fertilizer considerably impacts the environment through the emission of the highly potent greenhouse gas nitrous oxide and the leaching of nitrate. Nitrate leaching is significantly important because fertilizer sourced nitrate that is partially leached into soil causes groundwater pollution. In an effort to model the effect of fertilizer application on the environment, the geochemical DeNitrification-DeComposition model (DNDC) was previously developed to quantitatively measure the effects of fertilizer use. The purpose of this study is to use this model more effectively on a large scale through a measurement based calibration. For this reason, leaching was measured and studied on 12 sites in the Richland Creek Watershed (RCW). Information about the fertilization and irrigation regimes of these sites was collected, along with lysimeter readings that gave nitrate fluxes in the soil. A study of the amount and variation in nitrate leaching with respect to the varying geographical locations, time of the year, and fertilization and irrigation regimes has lead to a better understanding of the driving forces behind nitrate leaching. Quantifying the influence of each of these parameters allows for a more accurate calibration of the model thus permitting use that extends beyond the RCW. Measurement of nitrate leaching on a statewide or nationwide level in turn will help guide efforts in the reduction of groundwater pollution caused by fertilizer.

Attribution of future US ozone pollution to regional emissions, climate change, long-range transport, and model deficiency

NASA Astrophysics Data System (ADS)

He, H.; Liang, X.-Z.; Lei, H.; Wuebbles, D. J.

2014-10-01

A regional chemical transport model (CTM) is used to quantify the relative contributions of future US ozone pollution from regional emissions, climate change, long-range transport (LRT) of pollutants, and model deficiency. After incorporating dynamic lateral boundary conditions (LBCs) from a global CTM, the representation of present-day US ozone pollution is notably improved. This nested system projects substantial surface ozone trends for 2050's: 6-10 ppbv decreases under the "clean" A1B scenario and ~15 ppbv increases under the "dirty" A1Fi scenario. Among the total trends, regional emissions changes dominate, contributing negative 20-50% in A1B and positive 20-40% in A1Fi, while LRT effects through chemical LBCs and climate changes account for respectively 15-50% and 10-30% in both scenarios. The projection uncertainty due to model biases is region dependent, ranging from -10 to 50%. It is shown that model biases of present-day simulations can propagate into future projections systematically but nonlinearly, and the accurate specification of LBCs is essential for US ozone projections.

Fractional kalman filter to estimate the concentration of air pollution

NASA Astrophysics Data System (ADS)

Vita Oktaviana, Yessy; Apriliani, Erna; Khusnul Arif, Didik

2018-04-01

Air pollution problem gives important effect in quality environment and quality of human’s life. Air pollution can be caused by nature sources or human activities. Pollutant for example Ozone, a harmful gas formed by NOx and volatile organic compounds (VOCs) emitted from various sources. The air pollution problem can be modeled by TAPM-CTM (The Air Pollution Model with Chemical Transport Model). The model shows concentration of pollutant in the air. Therefore, it is important to estimate concentration of air pollutant. Estimation method can be used for forecast pollutant concentration in future and keep stability of air quality. In this research, an algorithm is developed, based on Fractional Kalman Filter to solve the model of air pollution’s problem. The model will be discretized first and then it will be estimated by the method. The result shows that estimation of Fractional Kalman Filter has better accuracy than estimation of Kalman Filter. The accuracy was tested by applying RMSE (Root Mean Square Error).

Hybrid Modeling Approach to Estimate Exposures of Hazardous Air Pollutants (HAPs) for the National Air Toxics Assessment (NATA).

PubMed

Scheffe, Richard D; Strum, Madeleine; Phillips, Sharon B; Thurman, James; Eyth, Alison; Fudge, Steve; Morris, Mark; Palma, Ted; Cook, Richard

2016-11-15

A hybrid air quality model has been developed and applied to estimate annual concentrations of 40 hazardous air pollutants (HAPs) across the continental United States (CONUS) to support the 2011 calendar year National Air Toxics Assessment (NATA). By combining a chemical transport model (CTM) with a Gaussian dispersion model, both reactive and nonreactive HAPs are accommodated across local to regional spatial scales, through a multiplicative technique designed to improve mass conservation relative to previous additive methods. The broad scope of multiple pollutants capturing regional to local spatial scale patterns across a vast spatial domain is precedent setting within the air toxics community. The hybrid design exhibits improved performance relative to the stand alone CTM and dispersion model. However, model performance varies widely across pollutant categories and quantifiably definitive performance assessments are hampered by a limited observation base and challenged by the multiple physical and chemical attributes of HAPs. Formaldehyde and acetaldehyde are the dominant HAP concentration and cancer risk drivers, characterized by strong regional signals associated with naturally emitted carbonyl precursors enhanced in urban transport corridors with strong mobile source sector emissions. The multiple pollutant emission characteristics of combustion dominated source sectors creates largely similar concentration patterns across the majority of HAPs. However, reactive carbonyls exhibit significantly less spatial variability relative to nonreactive HAPs across the CONUS.

Impact of two chemistry mechanisms fully coupled with mesoscale model on the atmospheric pollutants distribution

NASA Astrophysics Data System (ADS)

Arteta, J.; Cautenet, S.; Taghavi, M.; Audiffren, N.

Air quality models (AQM) consist of many modules (meteorology, emission, chemistry, deposition), and in some conditions such as: vicinity of clouds or aerosols plumes, complex local circulations (mountains, sea breezes), fully coupled models (online method) are necessary. In order to study the impact of lumped chemical mechanisms in AQM simulations, we examine the ability of both different chemical mechanisms: (i) simplified: Condensed Version of the MOdèle de Chimie Atmosphérique 2.2 (CV-MOCA2.2), and (ii) reference: Regional Atmospheric Chemistry Model (RACM), which are coupled online with the Regional Atmospheric Modeling Systems (RAMS) model, on the distribution of pollutants. During the ESCOMPTE experiment (Expérience sur Site pour COntraindre les Modèles de Pollution et de Transport d'Emissions) conducted over Southern France (including urban and industrial zones), Intensive observation periods (IOP) characterized by various meteorological and mixed chemical conditions are simulated. For both configurations of modeling, numerical results are compared with surface measurements (75 stations) for primary (NO x) and secondary (O 3) species. We point out the impact of the two different chemical mechanisms on the production of species involved in the oxidizing capacity such as ozone and radicals within urban and industrial areas. We highlight that both chemical mechanisms produce very similar results for the main pollutants (NO x and O 3) in three-dimensional (3D) distribution, despite large discrepancies in 0D modeling. For ozone concentration, we found sometimes small differences (5-10 ppb) between the mechanisms under study according to the cases (polluted or not). The relative difference between the two mechanisms over the whole domain is only -7% for ozone from CV-MOCA 2.2 versus RACM. When the order of magnitude is needed rather than an accurate estimate, a reduced mechanism is satisfactory. It has the advantage of running faster (four times less than CPU

An integrated approach to model the biomagnification of organic pollutants in aquatic food webs of the Yangtze Three Gorges Reservoir ecosystem using adapted pollution scenarios.

PubMed

Scholz-Starke, Björn; Ottermanns, Richard; Rings, Ursula; Floehr, Tilman; Hollert, Henner; Hou, Junli; Li, Bo; Wu, Ling Ling; Yuan, Xingzhong; Strauch, Katrin; Wei, Hu; Norra, Stefan; Holbach, Andreas; Westrich, Bernhard; Schäffer, Andreas; Roß-Nickoll, Martina

2013-10-01

The impounding of the Three Gorges Reservoir (TGR) at the Yangtze River caused large flooding of urban, industrial, and agricultural areas, and profound land use changes took place. Consequently, substantial amounts of organic and inorganic pollutants were released into the reservoir. Additionally, contaminants and nutrients are entering the reservoir by drift, drainage, and runoff from adjacent agricultural areas as well as from sewage of industry, aquacultures, and households. The main aim of the presented research project is a deeper understanding of the processes that determines the bioaccumulation and biomagnification of organic pollutants, i.e., mainly pesticides, in aquatic food webs under the newly developing conditions of the TGR. The project is part of the Yangtze-Hydro environmental program, financed by the German Ministry of Education and Science. In order to test combinations of environmental factors like nutrients and pollution, we use an integrated modeling approach to study the potential accumulation and biomagnification. We describe the integrative modeling approach and the consecutive adaption of the AQUATOX model, used as modeling framework for ecological risk assessment. As a starting point, pre-calibrated simulations were adapted to Yangtze-specific conditions (regionalization). Two exemplary food webs were developed by a thorough review of the pertinent literature. The first typical for the flowing conditions of the original Yangtze River and the Daning River near the city of Wushan, and the second for the stagnant reservoir characteristics of the aforementioned region that is marked by an intermediate between lake and large river communities of aquatic organisms. In close cooperation with German and Chinese partners of the Yangtze-Hydro Research Association, other site-specific parameters were estimated. The MINIBAT project contributed to the calibration of physicochemical and bathymetric parameters, and the TRANSMIC project delivered

Leachate breakthrough mechanism and key pollutant indicator of municipal solid waste landfill barrier systems: Centrifuge and numerical modeling approach.

PubMed

Shu, Shi; Zhu, Wei; Wang, Shengwei; Ng, Charles Wang Wai; Chen, Yunmin; Chiu, Abraham Chung Fai

2018-01-15

Groundwater pollution by leachate leakage is one of the most common environmental hazards associated with municipal solid waste (MSW) landfill sites. However, landfill leachate contains a large variety of pollutants with widely different concentrations and biotoxicity. Thus, selecting leachate pollutant indicators and levels for identifying breakthrough of barrier systems are key factors in assessing their breakthrough times. This study investigated the transport behavior of leachate pollutants through landfill barrier systems using centrifuge tests and numerical modeling. The overall objective of this study is to investigate breakthrough mechanism to facilitate the establishment of a consistent pollutant threshold concentration for use as a groundwater pollution alert. The specific objective of the study is to identify which pollutant and breakthrough threshold concentration should be used as an indicator in the transport of multiple pollutants through a landfill barrier system. The threshold concentration from the Chinese groundwater quality standards was used in the analysis of the properties of leachates from many landfill sites in China. The time for the chemical oxygen demand (COD) to reach the breakthrough threshold concentration at the bottom of a 2m compacted clay liner was 1.51years according to centrifuge tests, and 1.81years according to numerical modeling. The COD breakthrough times for single and double composite liners were within the range of 16 and 36.58years. Of all the pollutants, COD was found to consistently reach the breakthrough threshold first. Therefore, COD can be selected as the key indicator for pollution alerts and used to assess the environmental risk posed by MSW landfill sites. Copyright © 2017. Published by Elsevier B.V.

Assessment of Health-Cost Externalities of Air Pollution at the National Level using the EVA Model System

NASA Astrophysics Data System (ADS)

Brandt, Jørgen; Silver, Jeremy David; Heile Christensen, Jesper; Skou Andersen, Mikael; Geels, Camilla; Gross, Allan; Buus Hansen, Ayoe; Mantzius Hansen, Kaj; Brandt Hedegaard, Gitte; Ambelas Skjøth, Carsten

2010-05-01

Air pollution has significant negative impacts on human health and well-being, which entail substantial economic consequences. We have developed an integrated model system, EVA (External Valuation of Air pollution), to assess health-related economic externalities of air pollution resulting from specific emission sources/sectors. The EVA system was initially developed to assess externalities from power production, but in this study it is extended to evaluate costs at the national level. The EVA system integrates a regional-scale atmospheric chemistry transport model (DEHM), address-level population data, exposure-response functions and monetary values applicable for Danish/European conditions. Traditionally, systems that assess economic costs of health impacts from air pollution assume linear approximations in the source-receptor relationships. However, atmospheric chemistry is non-linear and therefore the uncertainty involved in the linear assumption can be large. The EVA system has been developed to take into account the non-linear processes by using a comprehensive, state-of-the-art chemical transport model when calculating how specific changes to emissions affect air pollution levels and the subsequent impacts on human health and cost. Furthermore, we present a new "tagging" method, developed to examine how specific emission sources influence air pollution levels without assuming linearity of the non-linear behaviour of atmospheric chemistry. This method is more precise than the traditional approach based on taking the difference between two concentration fields. Using the EVA system, we have estimated the total external costs from the main emission sectors in Denmark, representing the ten major SNAP codes. Finally, we assess the impacts and external costs of emissions from international ship traffic around Denmark, since there is a high volume of ship traffic in the region.

Ultra-rapid catalytic degradation of 4-nitrophenol with ionic liquid recoverable and reusable ibuprofen derived silver nanoparticles.

PubMed

Hassan, Syeda Sara; Carlson, Krista; Mohanty, Swomitra Kumar; Sirajuddin; Canlier, Ali

2018-06-01

This study reports a one-pot and eco-friendly method for the synthesis of spherical ibuprofen derived silver nanoparticles (IBU-AgNPs) in aqueous media using ibuprofen analgesics drug as capping as well as reducing agent. Formation of AgNPs occurred within a few min (less than 5 min) at room temperature without resorting to any harsh conditions and hazardous organic solvents. Synthesized AgNPs were characterized with common analytical techniques. Transmission electron microscope (TEM) images confirmed the formation of spherical particles having a size distribution in the range of 12.5 ± 1.5 nm. Employment of IBU analgesic aided the control of better size distribution and prevented agglomeration of particles. Such AgNPs solution was highly stable for more than two months when stored at ambient temperature. The IBU-AgNPs solution showed excellent ultra-rapid catalytic activity for the complete degradation of toxic 4-nitrophenol (4-NPh) into non-toxic 4-aminophenol (4-APh) within 40 s. AgNPs were recovered with the help of water insoluble-room temperature ionic liquid and reused with enhanced catalytic potential. This method provides a novel, rapid and economical alternative for the treatment of toxic organic pollutants to maintain water quality and environmental safety against water pollution. It is extendable for the control of other reducible contaminants in water as well. Furthermore, this catalytic activity for an effective degradation of organic toxins is expected to play a crucial role for achieving the Sustainable Development Goal 6 set by United Nations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Simulation of gaseous pollutant dispersion around an isolated building using the k-ω SST (shear stress transport) turbulence model.

PubMed

Yu, Hesheng; Thé, Jesse

2017-05-01

The dispersion of gaseous pollutant around buildings is complex due to complex turbulence features such as flow detachment and zones of high shear. Computational fluid dynamics (CFD) models are one of the most promising tools to describe the pollutant distribution in the near field of buildings. Reynolds-averaged Navier-Stokes (RANS) models are the most commonly used CFD techniques to address turbulence transport of the pollutant. This research work studies the use of [Formula: see text] closure model for the gas dispersion around a building by fully resolving the viscous sublayer for the first time. The performance of standard [Formula: see text] model is also included for comparison, along with results of an extensively validated Gaussian dispersion model, the U.S. Environmental Protection Agency (EPA) AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model). This study's CFD models apply the standard [Formula: see text] and the [Formula: see text] turbulence models to obtain wind flow field. A passive concentration transport equation is then calculated based on the resolved flow field to simulate the distribution of pollutant concentrations. The resultant simulation of both wind flow and concentration fields are validated rigorously by extensive data using multiple validation metrics. The wind flow field can be acceptably modeled by the [Formula: see text] model. However, the [Formula: see text] model fails to simulate the gas dispersion. The [Formula: see text] model outperforms [Formula: see text] in both flow and dispersion simulations, with higher hit rates for dimensionless velocity components and higher "factor of 2" of observations (FAC2) for normalized concentration. All these validation metrics of [Formula: see text] model pass the quality assurance criteria recommended by The Association of German Engineers (Verein Deutscher Ingenieure, VDI) guideline. Furthermore, these metrics are better than or the same as those

Joint Effects of Ambient Air Pollutants on Pediatric Asthma ...

EPA Pesticide Factsheets

Background: Because ambient air pollution exposure occurs in the form of mixtures, consideration of joint effects of multiple pollutants may advance our understanding of air pollution health effects. Methods: We assessed the joint effect of selected ambient air pollutant combinations (groups of oxidant, secondary, traffic, power plant, and criteria pollutants constructed using combinations of criteria gases, fine particulate matter (PM2.5) and PM2.5 components) on warm season pediatric asthma emergency department (ED) visits in Atlanta during 1998-2004. Joint effects were assessed using multi-pollutant Poisson generalized linear models controlling for time trends, meteorology and daily non-asthma respiratory ED visit counts. Rate ratios (RR) were calculated for the combined effect of an interquartile-range increment in the concentration of each pollutant. Results: Increases in all of the selected pollutant combinations were associated with increases in pediatric asthma ED visits [e.g., joint effect rate ratio=1.13 (95% confidence interval 1.06-1.21) for criteria pollutants (including ozone, carbon monoxide, nitrogen dioxide, sulfur dioxide, and PM2.5)]. Joint effect estimates were smaller than estimates calculated based on summing results from single-pollutant models, due to control for confounding. Compared with models without interactions, joint effect estimates from models including first-order pollutant interactions were similar for oxidant a

Transport and dispersion of pollutants in surface impoundments: a finite difference model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yeh, G.T.

1980-07-01

A surface impoundment model by finite-difference (SIMFD) has been developed. SIMFD computes the flow rate, velocity field, and the concentration distribution of pollutants in surface impoundments with any number of islands located within the region of interest. Theoretical derivations and numerical algorithm are described in detail. Instructions for the application of SIMFD and listings of the FORTRAN IV source program are provided. Two sample problems are given to illustrate the application and validity of the model.

Modelling Regional Hotspots of Water Pollution Induced by Salinization

NASA Astrophysics Data System (ADS)

Malsy, M.; Floerke, M.

2014-12-01

Insufficient water quality is one of the main global topics causing risk to human health, biodiversity, and food security. At this, salinization of water and land resources is widely spread especially in arid to semi-arid climates, where salinization, often induced by irrigation agriculture, is a fundamental aspect of land degradation. High salinity is crucial to water use for drinking, irrigation, and industrial purposes, and therefore poses a risk to human health and ecosystem status. However, salinization is also an economic problem, in particular in those regions where agriculture makes a significant contribution to the economy and/or where agriculture is mainly based on irrigation. Agricultural production is exposed to high salinity of irrigation water resulting in lower yields. Hence, not only the quantity of irrigation water is of importance for growing cops but also its quality, which may further reduce the available resources. Thereby a major concern for food production and security persists, as irrigated agriculture accounts for over 30% of the total agricultural production. In this study, the large scale water quality model WorldQual was applied to simulate recent total dissolved solids (TDS) loadings and in-stream concentrations from point and diffuse sources to get an insight on potential environmental impacts as well as risks to food security. Regional focus in this study is on developing countries, as these are most threatened by water pollution. Furthermore, insufficient water quality for irrigation and therefore restrictions in irrigation water use were examined, indicating limitations to crop production. For this purpose, model simulations were conducted for the year 2010 to show the recent status of surface water quality and to identify hotspots and main causes of pollution. Our results show that salinity hotspots mainly occur in peak irrigation regions as irrigated agriculture is by far the dominant sector contributing to water abstractions as

Tannic acid-modified silver nanoparticles for wound healing: the importance of size

PubMed Central

Orlowski, Piotr; Zmigrodzka, Magdalena; Tomaszewska, Emilia; Ranoszek-Soliwoda, Katarzyna; Czupryn, Monika; Antos-Bielska, Malgorzata; Szemraj, Janusz; Celichowski, Grzegorz; Grobelny, Jaroslaw

2018-01-01

Introduction Silver nanoparticles (AgNPs) have been shown to promote wound healing and to exhibit antimicrobial properties against a broad range of bacteria. In our previous study, we prepared tannic acid (TA)-modified AgNPs showing a good toxicological profile and immunomodulatory properties useful for potential dermal applications. Methods In this study, in vitro scratch assay, antimicrobial tests, modified lymph node assay as well as a mouse splint wound model were used to access the wound healing potential of TA-modified and unmodified AgNPs. Results TA-modified but not unmodified AgNPs exhibited effective antibacterial activity against Pseudomonas aeruginosa, Staphylococcus aureus and Escherichia coli and stimulated migration of keratinocytes in vitro. The tests using the mouse splint wound model showed that TA-modified 33 and 46 nm AgNPs promoted better wound closure, epithelialization, angiogenesis and formation of the granulation tissue. Additionally, AgNPs elicited expression of VEGF-α, PDGF-β and TGF-β1 cytokines involved in wound healing more efficiently in comparison to control and TA-treated wounds. However, both the lymph node assay and the wound model showed that TA-modified AgNPs sized 13 nm can elicit strong inflammatory response not only during wound healing but also when applied to the damaged skin. Conclusion TA-modified AgNPs sized >26 nm promote wound healing better than TA-modified or unmodified AgNPs. These findings suggest that TA-modified AgNPs sized >26 nm may have a promising application in wound management. PMID:29497293

Modeling analysis of secondary inorganic aerosols over China: pollution characteristics, and meteorological and dust impacts.

PubMed

Fu, Xiao; Wang, Shuxiao; Chang, Xing; Cai, Siyi; Xing, Jia; Hao, Jiming

2016-10-26

Secondary inorganic aerosols (SIA) are the predominant components of fine particulate matter (PM 2.5 ) and have significant impacts on air quality, human health, and climate change. In this study, the Community Multiscale Air Quality modeling system (CMAQ) was modified to incorporate SO 2 heterogeneous reactions on the surface of dust particles. The revised model was then used to simulate the spatiotemporal characteristics of SIA over China and analyze the impacts of meteorological factors and dust on SIA formation. Including the effects of dust improved model performance for the simulation of SIA concentrations, particularly for sulfate. The simulated annual SIA concentration in China was approximately 10.1 μg/m 3 on domain average, with strong seasonal variation: highest in winter and lowest in summer. High SIA concentrations were concentrated in developed regions with high precursor emissions, such as the North China Plain, Yangtze River Delta, Sichuan Basin, and Pearl River Delta. Strong correlations between meteorological factors and SIA pollution levels suggested that heterogeneous reactions under high humidity played an important role on SIA formation, particularly during severe haze pollution periods. Acting as surfaces for heterogeneous reactions, dust particles significantly affected sulfate formation, suggesting the importance of reducing dust emissions for controlling SIA and PM 2.5 pollution.

Modeling analysis of secondary inorganic aerosols over China: pollution characteristics, and meteorological and dust impacts

NASA Astrophysics Data System (ADS)

Fu, Xiao; Wang, Shuxiao; Chang, Xing; Cai, Siyi; Xing, Jia; Hao, Jiming

2016-10-01

Secondary inorganic aerosols (SIA) are the predominant components of fine particulate matter (PM2.5) and have significant impacts on air quality, human health, and climate change. In this study, the Community Multiscale Air Quality modeling system (CMAQ) was modified to incorporate SO2 heterogeneous reactions on the surface of dust particles. The revised model was then used to simulate the spatiotemporal characteristics of SIA over China and analyze the impacts of meteorological factors and dust on SIA formation. Including the effects of dust improved model performance for the simulation of SIA concentrations, particularly for sulfate. The simulated annual SIA concentration in China was approximately 10.1 μg/m3 on domain average, with strong seasonal variation: highest in winter and lowest in summer. High SIA concentrations were concentrated in developed regions with high precursor emissions, such as the North China Plain, Yangtze River Delta, Sichuan Basin, and Pearl River Delta. Strong correlations between meteorological factors and SIA pollution levels suggested that heterogeneous reactions under high humidity played an important role on SIA formation, particularly during severe haze pollution periods. Acting as surfaces for heterogeneous reactions, dust particles significantly affected sulfate formation, suggesting the importance of reducing dust emissions for controlling SIA and PM2.5 pollution.

Modeling analysis of secondary inorganic aerosols over China: pollution characteristics, and meteorological and dust impacts

PubMed Central

Fu, Xiao; Wang, Shuxiao; Chang, Xing; Cai, Siyi; Xing, Jia; Hao, Jiming

2016-01-01

Secondary inorganic aerosols (SIA) are the predominant components of fine particulate matter (PM2.5) and have significant impacts on air quality, human health, and climate change. In this study, the Community Multiscale Air Quality modeling system (CMAQ) was modified to incorporate SO2 heterogeneous reactions on the surface of dust particles. The revised model was then used to simulate the spatiotemporal characteristics of SIA over China and analyze the impacts of meteorological factors and dust on SIA formation. Including the effects of dust improved model performance for the simulation of SIA concentrations, particularly for sulfate. The simulated annual SIA concentration in China was approximately 10.1 μg/m3 on domain average, with strong seasonal variation: highest in winter and lowest in summer. High SIA concentrations were concentrated in developed regions with high precursor emissions, such as the North China Plain, Yangtze River Delta, Sichuan Basin, and Pearl River Delta. Strong correlations between meteorological factors and SIA pollution levels suggested that heterogeneous reactions under high humidity played an important role on SIA formation, particularly during severe haze pollution periods. Acting as surfaces for heterogeneous reactions, dust particles significantly affected sulfate formation, suggesting the importance of reducing dust emissions for controlling SIA and PM2.5 pollution. PMID:27782166

Efficient stochastic approaches for sensitivity studies of an Eulerian large-scale air pollution model

NASA Astrophysics Data System (ADS)

Dimov, I.; Georgieva, R.; Todorov, V.; Ostromsky, Tz.

2017-10-01

Reliability of large-scale mathematical models is an important issue when such models are used to support decision makers. Sensitivity analysis of model outputs to variation or natural uncertainties of model inputs is crucial for improving the reliability of mathematical models. A comprehensive experimental study of Monte Carlo algorithms based on Sobol sequences for multidimensional numerical integration has been done. A comparison with Latin hypercube sampling and a particular quasi-Monte Carlo lattice rule based on generalized Fibonacci numbers has been presented. The algorithms have been successfully applied to compute global Sobol sensitivity measures corresponding to the influence of several input parameters (six chemical reactions rates and four different groups of pollutants) on the concentrations of important air pollutants. The concentration values have been generated by the Unified Danish Eulerian Model. The sensitivity study has been done for the areas of several European cities with different geographical locations. The numerical tests show that the stochastic algorithms under consideration are efficient for multidimensional integration and especially for computing small by value sensitivity indices. It is a crucial element since even small indices may be important to be estimated in order to achieve a more accurate distribution of inputs influence and a more reliable interpretation of the mathematical model results.

A simulation study to determine the attenuation and bias in health risk estimates due to exposure measurement error in bi-pollutant models

EPA Science Inventory

To understand the combined health effects of exposure to ambient air pollutant mixtures, it is becoming more common to include multiple pollutants in epidemiologic models. However, the complex spatial and temporal pattern of ambient pollutant concentrations and related exposures ...

Global Modeling and Projection of Short-Lived Climate Pollutants in an Earth System Model

NASA Astrophysics Data System (ADS)

Sudo, K.; Takemura, T.; Klimont, Z.; Kurokawa, J.; Akimoto, H.

2013-12-01

In predicting and mitigating future global warming, short-lived climate pollutants (SLCPs) such as tropospheric ozone (O3), black carbon (BC), and other related components including CH4/VOCs and aerosols play crucial roles as well as long-lived species like CO2 or N2O. Several recent studies suggests that reduction of heating SLCPs (i.e., O3 and black carbon) together with CH4 can decrease and delay the expected future warming, and can be an alternative to CO2 mitigation (Shindell et al., 2012). However it should be noted that there are still large uncertainties in simulating SLCPs and their climate impacts. For instance, present global models generally have a severe tendency to underestimate BC especially in remote areas like the polar regions as shown by the recent model intercomparison project under the IPCC (ACCMIP/AeroCOM). This problem in global BC modeling, basically coming from aging and removal processes of BC, causes still a large uncertainty in the estimate of BC's atmospheric heating and climate impacts (Bond et al., 2013; Kerr et al., 2013). This study attempted to improve global simulation of BC by developing a new scheme for simulating aging process of BC and re-evaluate radiative forcing of BC in the framework of a chemistry-aerosol coupled climate model (Earth system model) MIROC-ESM-CHEM. Our improved model with the new aging scheme appears to relatively well reproduce the observed BC concentrations and seasonality in the Arctic/Antarctic region. The new model estimates radiative forcing of BC to be 0.83 W m-2 which is about two times larger than the estimate by our original model with no aging scheme (0.41 W m-2), or the model ensemble mean in the IPCC report. Using this model, future projection of SLCPs and their climate impacts is conducted following the recent IIASA emission scenarios for the year 2030 (Klimont et al., 2006; Cofala et al., 2007). Our simulation suggests that heating SLCPs components (O3, BC, and CH4) are significantly reduced

Using ensemble models to identify and apportion heavy metal pollution sources in agricultural soils on a local scale.

PubMed

Wang, Qi; Xie, Zhiyi; Li, Fangbai

2015-11-01

This study aims to identify and apportion multi-source and multi-phase heavy metal pollution from natural and anthropogenic inputs using ensemble models that include stochastic gradient boosting (SGB) and random forest (RF) in agricultural soils on the local scale. The heavy metal pollution sources were quantitatively assessed, and the results illustrated the suitability of the ensemble models for the assessment of multi-source and multi-phase heavy metal pollution in agricultural soils on the local scale. The results of SGB and RF consistently demonstrated that anthropogenic sources contributed the most to the concentrations of Pb and Cd in agricultural soils in the study region and that SGB performed better than RF. Copyright © 2015 Elsevier Ltd. All rights reserved.

4 years of PM10 pollution in Poland - observations and modelling

NASA Astrophysics Data System (ADS)

Durka, Pawel; Struzewska, Joanna; Kaminski, Jacek W.

2017-04-01

Poor air quality is a health issue in Poland, especially during winter. In central and northern part of the country, the primary source is low-level domestic emissions. In larger cities and agglomerations traffic emissions are also an issue. Quantification of the contribution of transboundary pollution sources is still an open issue. Analyses of 60 episodes for the period 2013-2016 with high PM10 concentrations were carried out under a contract from the Chief Inspectorate of Environmental Protection in Poland. Analyses of synoptic conditions and calculation of back trajectories were undertaken. A tropospheric chemistry model GEM-AQ was run at 10km resolution to calculate contributions from surface, line and point sources. We will present trajectories for different types of episodes, maps with contributions for specific emission sources and transboundary pollution. Also, mean distribution of PM10 concentrations during episodes will be shown.

Stochastic backscatter modelling for the prediction of pollutant removal from an urban street canyon: A large-eddy simulation

NASA Astrophysics Data System (ADS)

O'Neill, J. J.; Cai, X.-M.; Kinnersley, R.

2016-10-01

The large-eddy simulation (LES) approach has recently exhibited its appealing capability of capturing turbulent processes inside street canyons and the urban boundary layer aloft, and its potential for deriving the bulk parameters adopted in low-cost operational urban dispersion models. However, the thin roof-level shear layer may be under-resolved in most LES set-ups and thus sophisticated subgrid-scale (SGS) parameterisations may be required. In this paper, we consider the important case of pollutant removal from an urban street canyon of unit aspect ratio (i.e. building height equal to street width) with the external flow perpendicular to the street. We show that by employing a stochastic SGS model that explicitly accounts for backscatter (energy transfer from unresolved to resolved scales), the pollutant removal process is better simulated compared with the use of a simpler (fully dissipative) but widely-used SGS model. The backscatter induces additional mixing within the shear layer which acts to increase the rate of pollutant removal from the street canyon, giving better agreement with a recent wind-tunnel experiment. The exchange velocity, an important parameter in many operational models that determines the mass transfer between the urban canopy and the external flow, is predicted to be around 15% larger with the backscatter SGS model; consequently, the steady-state mean pollutant concentration within the street canyon is around 15% lower. A database of exchange velocities for various other urban configurations could be generated and used as improved input for operational street canyon models.

BUILDING AN ENVIRONMENTAL TRAINING MODEL, MAPCORE - A TRAINING EXERCISE FOR AIR POLLUTION CONTROL.

ERIC Educational Resources Information Center

SIEGEL, GILBERT B.; SULLIVAN, DONALD M.

NEW AIR POLLUTION CONTROL PROGRAMS HAVE RESULTED FROM THE "CLEAN AIR ACT" PASSED BY CONGRESS IN DECEMBER 1963. THE UNIVERSITY OF SOUTHERN CALIFORNIA DEVELOPED A TRAINING MODEL, CALLED "MAPCORE," WHICH PROVIDES A SEMISTRUCTURED ENVIRONMENT, IS PRACTICAL AND REALISTIC IN APPROACH, PROVIDES OPPORTUNITY FOR HIGH CREATIVITY,…

Ambient air pollution and semen quality.

PubMed

Nobles, Carrie J; Schisterman, Enrique F; Ha, Sandie; Kim, Keewan; Mumford, Sunni L; Buck Louis, Germaine M; Chen, Zhen; Liu, Danping; Sherman, Seth; Mendola, Pauline

2018-05-01

Ambient air pollution is associated with systemic increases in oxidative stress, to which sperm are particularly sensitive. Although decrements in semen quality represent a key mechanism for impaired fecundability, prior research has not established a clear association between air pollution and semen quality. To address this, we evaluated the association between ambient air pollution and semen quality among men with moderate air pollution exposure. Of 501 couples in the LIFE study, 467 male partners provided one or more semen samples. Average residential exposure to criteria air pollutants and fine particle constituents in the 72 days before ejaculation was estimated using modified Community Multiscale Air Quality models. Generalized estimating equation models estimated the association between air pollutants and semen quality parameters (volume, count, percent hypo-osmotic swollen, motility, sperm head, morphology and sperm chromatin parameters). Models adjusted for age, body mass index, smoking and season. Most associations between air pollutants and semen parameters were small. However, associations were observed for an interquartile increase in fine particulates ≤2.5 µm and decreased sperm head size, including -0.22 (95% CI -0.34, -0.11) µm 2 for area, -0.06 (95% CI -0.09, -0.03) µm for length and -0.09 (95% CI -0.19, -0.06) µm for perimeter. Fine particulates were also associated with 1.03 (95% CI 0.40, 1.66) greater percent sperm head with acrosome. Air pollution exposure was not associated with semen quality, except for sperm head parameters. Moderate levels of ambient air pollution may not be a major contributor to semen quality. Published by Elsevier Inc.

Potential impacts of silver nanoparticles on bacteria in the aquatic environment.

PubMed

Sheng, Zhiya; Liu, Yang

2017-04-15

It is inevitable that nano-silver will be released into the environment. Therefore, there is an urgent need to better understand the effects of silver nanoparticles (Ag-NPs) on microbes in natural and engineered environments. The most remarkable gap in our knowledge on this lies on the low Ag-NPs dose side. This review summarized studies on the effects of Ag-NPs on bacteria from simple to complicated aquatic systems. A hormetic model with a narrow stimulatory zone has been proposed based on both experimental phenomenon and the potential mechanisms of the observed effects. Spectrum of the stimulating zone depends on Ag-NP properties, bacterial types and environmental conditions tested. This may become a concern in terms of Ag-NP disposal, and further research is required to build a sophisticated toxicity model for Ag-NPs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mathematical numeric models for assessing the groundwater pollution from Sanitary landfills

NASA Astrophysics Data System (ADS)

Petrov, Vasil; Stoyanov, Nikolay; Sotinev, Petar

2014-05-01

Landfills are among the most common sources of pollution in ground water. Their widespread deployment, prolonged usage and the serious damage they cause to all of the elements of the environment are the reasons, which make the study of the problem particularly relevant. Most dangerous of all are the open dumps used until the middle of the twentieth century, from which large amounts of liquid emissions flowed freely (landfill infiltrate). In recent decades, the problem is solved by the construction of sanitary landfills in which they bury waste or solid residue from waste utilization plants. The bottom and the sides of the sanitary landfills are covered with a protective waterproof screen made of clay and polyethylene and the landfill infiltrate is led outside through a drainage system. This method of disposal severely limits any leakage of gas and liquid emissions into the environment and virtually eliminates the possibility of contamination. The main topic in the conducted hydrogeological study was a quantitative assessment of groundwater pollution and the environmental effects of re-landfilling of an old open dump into a new sanitary landfill, following the example of the municipal landfill of Asenovgrad, Bulgaria. The study includes: 1.A set of drilling, geophysical and hydrogeological field and laboratory studies on: -the definition and designation of the spatial limits of the main hydrogeological units; -identification of filtration parameters and migration characteristics of the main hydrogeological units; -clarifying the conditions for the sustentation and drainage of groundwater; -determininng the structure of the filtration field; -identifying and assessing the size and the extent of groundwater contamination from the old open dump . 2.Mathematical numeric models of migration and entry conditions of contaminants below the bottom of the landfill unit, with which the natural protection of the geological environment, the protective effect of the engineering

Microcomputer pollution model for civilian airports and Air Force Bases. Model application and background

DOE Office of Scientific and Technical Information (OSTI.GOV)

Segal, H.M.

1988-08-01

This is one of three reports describing the Emissions and Dispersion Modeling System (EDMS). All reports use the same main title--A MICROCOMPUTER MODEL FOR CIVILIAN AIRPORTS AND AIR FORCE BASES--but different subtitles. The subtitles are: (1) USER'S GUIDE - ISSUE 2 (FAA-EE-88-3/ESL-TR-88-54); (2) MODEL DESCRIPTION (FAA-EE-88-4/ESL-TR-88-53); (S) MODEL APPLICATION AND BACKGROUND (FAA-EE-88-5/ESL-TR-88-55). The first and second reports above describe the EDMS model and provide instructions for its use. This is the third report. IT consists of an accumulation of five key documents describing the development and use of the EDMS model. This report is prepared in accordance with discussions withmore » the EPA and requirements outlined in the March 27, 1980 Federal Register for submitting air-quality models to the EPA. Contents: Model Development and Use - Its Chronology and Reports; Monitoring Concorde EMissions; The Influence of Aircraft Operations on Air Quality at Airports; Simplex A - A simplified Atmospheric Dispersion Model for Airport Use -(User's Guide); Microcomputer Graphics in Atmospheric Dispersion Modeling; Pollution from Motor Vehicles and Aircraft at Stapleton International Airport (Abbreviated Report).« less

A model to investigate the influence of suspended sediment on the mass transport of a pollutant in open channel flow. M.S. Thesis - Old Dominion Univ.

NASA Technical Reports Server (NTRS)

Chapman, R. S.

1977-01-01

An explicit two-dimensional finite difference model, designed to investigate the influence of suspended sediment on the pollutant transport process, is presented. Specific attention is directed toward examining the role of suspended sediment in: (1) the turbulent vertical transport mechanism in a stratified flow, and (2) pollutant uptake due to sorption. Results presented indicate that suspended sediment plays a major role in the pollutant transport process, and subsequently, any meaningful attempt to model the fate of a pollutant in an alluvial channel must account for the presence of a suspended sediment concentration profile. Similarly, the vertical and longitudinal pollutant concentration distributions provided by the model may be utilized to improve upon the predictive capacities of existing water quality models.

Modelling of agricultural diffuse pollution and mitigation measures effectiveness in Wallonia (Belgium)

NASA Astrophysics Data System (ADS)

Sohier, C.; Deraedt, D.; Degré, A.

2012-04-01

Implementation of European directives in the environmental field and, specially, in the water management field, generates a request from policy-makers for news tools able to evaluate impact of management measures aiming at reducing pressures on ecosystems. In Wallonia (Southern Region of Belgium), the Nitrate Directive (EEC/676/91) was transposed into the "Walloon action plan for nitrogen sustainable management in agriculture" (PGDA1) in 2002. In 2007, a second plan was launched to reinforce some topics (PGDA2). Furthermore, the goal of "good quality" of surface waters and groundwater imposed by the Water Framework Directive poses new challenges in water management. In this context, a "soil and vadose" hydrological model is used in order to evaluate diffuse pollutions and efficiency of mitigation measures. This model, called EPICgrid, has been developed at catchment scale with an original modular concept on the basis of the field scale "water-soil-plant" EPIC model (Williams J.R., Jones C.A., Dyke P.T. (1984). A modelling approach to determining the relationship between erosion and soil productivity. Transactions of the ASAE. 27, 129-144). The model estimates, for each HRU identified into a 1km2 grid, water and nutrients flows into the plant-soil-vadose zone system (Sohier C., Degré A., Dautrebande S. (2009). From root zone modelling to regional forecasting of nitrate concentration in recharge flows - The case of the Walloon Region (Belgium). Journal of Hydrology, Volume 369, Issues 3-4, 15 May 2009, Pages 350-359). The model is used to make prospective simulations in order to evaluate the impact of measures currently performed to reduce the effect of diffuse pollution on water surface quality and groundwater quality, at regional scale. Response of the soil-vadose zone to agricultural practices modification is analyzed for the deadlines of the Water Framework Directive: 2015, 2021 and 2027, taking into account two climatic scenarios. Simulations results showed

Impact of intercontinental pollution transport on North American ozone air pollution: an HTAP phase 2 multi-model study

PubMed Central

Huang, Min; Carmichael, Gregory R.; Pierce, R. Bradley; Jo, Duseong S.; Park, Rokjin J.; Flemming, Johannes; Emmons, Louisa K.; Bowman, Kevin W.; Henze, Daven K.; Davila, Yanko; Sudo, Kengo; Jonson, Jan Eiof; Lund, Marianne Tronstad; Janssens-Maenhout, Greet; Dentener, Frank J.; Keating, Terry J.; Oetjen, Hilke; Payne, Vivienne H.

2018-01-01

The recent update on the US National Ambient Air Quality Standards (NAAQS) of the ground-level ozone (O3/ can benefit from a better understanding of its source contributions in different US regions during recent years. In the Hemispheric Transport of Air Pollution experiment phase 1 (HTAP1), various global models were used to determine the O3 source–receptor (SR) relationships among three continents in the Northern Hemisphere in 2001. In support of the HTAP phase 2 (HTAP2) experiment that studies more recent years and involves higher-resolution global models and regional models’ participation, we conduct a number of regional-scale Sulfur Transport and dEposition Model (STEM) air quality base and sensitivity simulations over North America during May–June 2010. STEM’s top and lateral chemical boundary conditions were downscaled from three global chemical transport models’ (i.e., GEOS-Chem, RAQMS, and ECMWF C-IFS) base and sensitivity simulations in which the East Asian (EAS) anthropogenic emissions were reduced by 20 %. The mean differences between STEM surface O3 sensitivities to the emission changes and its corresponding boundary condition model’s are smaller than those among its boundary condition models, in terms of the regional/period-mean (<10 %) and the spatial distributions. An additional STEM simulation was performed in which the boundary conditions were downscaled from a RAQMS (Realtime Air Quality Modeling System) simulation without EAS anthropogenic emissions. The scalability of O3 sensitivities to the size of the emission perturbation is spatially varying, and the full (i.e., based on a 100% emission reduction) source contribution obtained from linearly scaling the North American mean O3 sensitivities to a 20% reduction in the EAS anthropogenic emissions may be underestimated by at least 10 %. The three boundary condition models’ mean O3 sensitivities to the 20% EAS emission perturbations are ~8% (May–June 2010)/~11% (2010 annual) lower

SYSTEMIC BIOMARKERS AND CARDIAC GENE EXPRESSION PROFILES OF RAT DISEASE MODELS EMPLOYED IN AIR POLLUTION STUDIES

EPA Science Inventory

Cardiovascular disease (CVD) models are used for identification of mechanisms of susceptibility to air pollution. We hypothesized that baseline systemic biomarkers and cardiac gene expression in CVD rat models will have influence on their ozone-induced lung inflammation. Male 12-...

A GIS-based atmospheric dispersion model for pollutants emitted by complex source areas.

PubMed

Teggi, Sergio; Costanzini, Sofia; Ghermandi, Grazia; Malagoli, Carlotta; Vinceti, Marco

2018-01-01

Gaussian dispersion models are widely used to simulate the concentrations and deposition fluxes of pollutants emitted by source areas. Very often, the calculation time limits the number of sources and receptors and the geometry of the sources must be simple and without holes. This paper presents CAREA, a new GIS-based Gaussian model for complex source areas. CAREA was coded in the Python language, and is largely based on a simplified formulation of the very popular and recognized AERMOD model. The model allows users to define in a GIS environment thousands of gridded or scattered receptors and thousands of complex sources with hundreds of vertices and holes. CAREA computes ground level, or near ground level, concentrations and dry deposition fluxes of pollutants. The input/output and the runs of the model can be completely managed in GIS environment (e.g. inside a GIS project). The paper presents the CAREA formulation and its applications to very complex test cases. The tests shows that the processing time are satisfactory and that the definition of sources and receptors and the output retrieval are quite easy in a GIS environment. CAREA and AERMOD are compared using simple and reproducible test cases. The comparison shows that CAREA satisfactorily reproduces AERMOD simulations and is considerably faster than AERMOD. Copyright © 2017 Elsevier B.V. All rights reserved.

[Bibliometrics and visualization analysis of land use regression models in ambient air pollution research].

PubMed

Zhang, Y J; Zhou, D H; Bai, Z P; Xue, F X

2018-02-10

Objective: To quantitatively analyze the current status and development trends regarding the land use regression (LUR) models on ambient air pollution studies. Methods: Relevant literature from the PubMed database before June 30, 2017 was analyzed, using the Bibliographic Items Co-occurrence Matrix Builder (BICOMB 2.0). Keywords co-occurrence networks, cluster mapping and timeline mapping were generated, using the CiteSpace 5.1.R5 software. Relevant literature identified in three Chinese databases was also reviewed. Results: Four hundred sixty four relevant papers were retrieved from the PubMed database. The number of papers published showed an annual increase, in line with the growing trend of the index. Most papers were published in the journal of Environmental Health Perspectives . Results from the Co-word cluster analysis identified five clusters: cluster#0 consisted of birth cohort studies related to the health effects of prenatal exposure to air pollution; cluster#1 referred to land use regression modeling and exposure assessment; cluster#2 was related to the epidemiology on traffic exposure; cluster#3 dealt with the exposure to ultrafine particles and related health effects; cluster#4 described the exposure to black carbon and related health effects. Data from Timeline mapping indicated that cluster#0 and#1 were the main research areas while cluster#3 and#4 were the up-coming hot areas of research. Ninety four relevant papers were retrieved from the Chinese databases with most of them related to studies on modeling. Conclusion: In order to better assess the health-related risks of ambient air pollution, and to best inform preventative public health intervention policies, application of LUR models to environmental epidemiology studies in China should be encouraged.

On The Development of One-way Nesting of Air-pollution Model Smog Into Numerical Weather Prediction Model Eta

NASA Astrophysics Data System (ADS)

Halenka, T.; Bednar, J.; Brechler, J.

The spatial distribution of air pollution on the regional scale (Bohemian region) is simulated by means of Charles University puff model SMOG. The results are used for the assessment of the concentration fields of ozone, nitrogen oxides and other ozone precursors. Current improved version of the model covers up to 16 groups of basic compounds and it is based on trajectory computation and puff interaction both by means of Gaussian diffusion mixing and chemical reactions of basic species. Gener- ally, the method used for trajectory computation is valuable mainly for episodes sim- ulation, nevertheless, climatological study can be solved as well by means of average wind rose. For the study being presented huge database of real emission sources was incorporated with all kind of sources included. Some problem with the background values of concentrations was removed. The model SMOG has been nested into the forecast model ETA to obtain appropriate meteorological data input. We can estimate air pollution characteristics both for episodes analysis and the prediction of future air quality conditions. Necessary prognostic variables from the numerical weather pre- diction model are taken for the region of the central Bohemia, where the original puff model was tested. We used mainly 850 hPa wind field for computation of prognos- tic trajectories, the influence of surface temperature as a parameter of photochemistry reactions as well as the effect of cloudness has been tested.

Modeling temporal and spatial variability of traffic-related air pollution: Hourly land use regression models for black carbon

NASA Astrophysics Data System (ADS)

Dons, Evi; Van Poppel, Martine; Kochan, Bruno; Wets, Geert; Int Panis, Luc

2013-08-01

Land use regression (LUR) modeling is a statistical technique used to determine exposure to air pollutants in epidemiological studies. Time-activity diaries can be combined with LUR models, enabling detailed exposure estimation and limiting exposure misclassification, both in shorter and longer time lags. In this study, the traffic related air pollutant black carbon was measured with μ-aethalometers on a 5-min time base at 63 locations in Flanders, Belgium. The measurements show that hourly concentrations vary between different locations, but also over the day. Furthermore the diurnal pattern is different for street and background locations. This suggests that annual LUR models are not sufficient to capture all the variation. Hourly LUR models for black carbon are developed using different strategies: by means of dummy variables, with dynamic dependent variables and/or with dynamic and static independent variables. The LUR model with 48 dummies (weekday hours and weekend hours) performs not as good as the annual model (explained variance of 0.44 compared to 0.77 in the annual model). The dataset with hourly concentrations of black carbon can be used to recalibrate the annual model, resulting in many of the original explaining variables losing their statistical significance, and certain variables having the wrong direction of effect. Building new independent hourly models, with static or dynamic covariates, is proposed as the best solution to solve these issues. R2 values for hourly LUR models are mostly smaller than the R2 of the annual model, ranging from 0.07 to 0.8. Between 6 a.m. and 10 p.m. on weekdays the R2 approximates the annual model R2. Even though models of consecutive hours are developed independently, similar variables turn out to be significant. Using dynamic covariates instead of static covariates, i.e. hourly traffic intensities and hourly population densities, did not significantly improve the models' performance.

Air Quality Modeling Technical Support Document for the Final Cross State Air Pollution Rule Update

EPA Pesticide Factsheets

In this technical support document (TSD) we describe the air quality modeling performed to support the final Cross State Air Pollution Rule for the 2008 ozone National Ambient Air Quality Standards (NAAQS).

A three-level model for binary time-series data: the effects of air pollution on school absences in the Southern California Children's Health Study.

PubMed

Rondeau, Virginie; Berhane, Kiros; Thomas, Duncan C

2005-04-15

A three-level model is proposed to simultaneously examine the effects of daily exposure to air pollution and individual risk factors on health outcomes without aggregating over subjects or time. We used a logistic transition model with random effects to take into account heterogeneity and overdispersion of the observations. A distributed lag structure for pollution has been included, assuming that the event on day t for a subject depends on the levels of air pollution for several preceding days. We illustrate this proposed model via detailed analysis of the effect of air pollution on school absenteeism based on data from the Southern California Children's Health Study.

The AGNP-TDM Expert Group Consensus Guidelines: focus on therapeutic monitoring of antidepressants

PubMed Central

Baumann, Pierre; Ulrich, Sven; Eckermann, Gabriel; Gerlach, Manfred; Kuss, Hans-Joachim; Laux, Gerd; Müller-Oerlinghausen, Bruno; Rao, Marie Luise; Riederer, Peter; Zernig, Gerald; Hiemke, Christoph

2005-01-01

Therapeutic drug monitoring (TDM) of psychotropic drugs such as antidepressants has been widely introduced for optimization of pharmacotherapy in psychiatric patients. The interdisciplinary TDM group of the Arbeitsgemeinschaft für Neuropsychopharmakologie und Pharmakopsychiatrie (AGNP) has worked out consensus guidelines with the aim of providing psychiatrists and TDM laboratories with a tool to optimize the use of TDM. Five research-based levels of recommendation were defined with regard to routine monitoring of drug plasma concentrations: (i) strongly recommended; (ii) recommended; (iii) useful; (iv) probably useful; and (v) not recommended. In addition, a list of indications that justify the use of TDM is presented, eg, control of compliance, lack of clinical response or adverse effects at recommended doses, drug interactions, pharmacovigilance programs, presence of a genetic particularity concerning drug metabolism, and children, adolescents, and elderly patients. For some drugs, studies on therapeutic ranges are lacking, but target ranges for clinically relevant plasma concentrations are presented for most drugs, based on pharmacokinetic studies reported in the literature. For many antidepressants, a thorough analysis of the literature on studies dealing with the plasma concentration–clinical effectiveness relationship allowed inclusion of therapeutic ranges of plasma concentrations. In addition, recommendations are made with regard to the combination of pharmacogenetic (phenotyping or genotyping) tests with TDM, Finally, practical instructions are given for the laboratory practitioners and the treating physicians how to use TDM: preparation of TDM, drug analysis, reporting and interpretation of results, and adequate use of information for patient treatment. TDM is a complex process that needs optimal interdisciplinary coordination of a procedure implicating patients, treating physicians, clinical pharmacologists, and clinical laboratory specialists. These

Emissions of indoor air pollutants from six user scenarios in a model room

NASA Astrophysics Data System (ADS)

Höllbacher, Eva; Ters, Thomas; Rieder-Gradinger, Cornelia; Srebotnik, Ewald

2017-02-01

In this study six common user scenarios putatively influencing indoor air quality were performed in a model room constructed according to the specifications of the European Reference Room given in the new horizontal prestandard prEN 16516 to gain further information about the influence of user activities on indoor air quality. These scenarios included the use of cleaning agent, an electric air freshener, an ethanol fireplace and cosmetics as well as cigarette smoking and peeling of oranges. Four common indoor air pollutants were monitored: volatile organic compounds (VOC), particulate matter (PM), carbonyl compounds and CO2. The development of all pollutants was determined during and after the test performance. For each measured pollutant, well-defined maximum values could be assigned to one or more of the individual user scenarios. The highest VOC concentration was measured during orange-peeling reaching a maximum value of 3547 μg m-3. Carbonyl compounds and PM were strongly elevated while cigarette smoking. Here, a maximum formaldehyde concentration of 76 μg m-3 and PM concentration of 378 μg m-3 were measured. CO2 was only slightly affected by most of the tests except the use of the ethanol fireplace where a maximum concentration of 1612 ppm was reached. Generally, the user scenarios resulted in a distinct increase of several indoor pollutants that usually decreased rapidly after the removal of the source.

Evaluating the effect of human activity patterns on air pollution exposure using an integrated field-based and agent-based modelling framework

NASA Astrophysics Data System (ADS)

Schmitz, Oliver; Beelen, Rob M. J.; de Bakker, Merijn P.; Karssenberg, Derek

2015-04-01

Constructing spatio-temporal numerical models to support risk assessment, such as assessing the exposure of humans to air pollution, often requires the integration of field-based and agent-based modelling approaches. Continuous environmental variables such as air pollution are best represented using the field-based approach which considers phenomena as continuous fields having attribute values at all locations. When calculating human exposure to such pollutants it is, however, preferable to consider the population as a set of individuals each with a particular activity pattern. This would allow to account for the spatio-temporal variation in a pollutant along the space-time paths travelled by individuals, determined, for example, by home and work locations, road network, and travel times. Modelling this activity pattern requires an agent-based or individual based modelling approach. In general, field- and agent-based models are constructed with the help of separate software tools, while both approaches should play together in an interacting way and preferably should be combined into one modelling framework, which would allow for efficient and effective implementation of models by domain specialists. To overcome this lack in integrated modelling frameworks, we aim at the development of concepts and software for an integrated field-based and agent-based modelling framework. Concepts merging field- and agent-based modelling were implemented by extending PCRaster (http://www.pcraster.eu), a field-based modelling library implemented in C++, with components for 1) representation of discrete, mobile, agents, 2) spatial networks and algorithms by integrating the NetworkX library (http://networkx.github.io), allowing therefore to calculate e.g. shortest routes or total transport costs between locations, and 3) functions for field-network interactions, allowing to assign field-based attribute values to networks (i.e. as edge weights), such as aggregated or averaged

A simulation of air pollution model parameter estimation using data from a ground-based LIDAR remote sensor

NASA Technical Reports Server (NTRS)

Kibler, J. F.; Suttles, J. T.

1977-01-01

One way to obtain estimates of the unknown parameters in a pollution dispersion model is to compare the model predictions with remotely sensed air quality data. A ground-based LIDAR sensor provides relative pollution concentration measurements as a function of space and time. The measured sensor data are compared with the dispersion model output through a numerical estimation procedure to yield parameter estimates which best fit the data. This overall process is tested in a computer simulation to study the effects of various measurement strategies. Such a simulation is useful prior to a field measurement exercise to maximize the information content in the collected data. Parametric studies of simulated data matched to a Gaussian plume dispersion model indicate the trade offs available between estimation accuracy and data acquisition strategy.

GIS-modeled indicators of traffic-related air pollutants and adverse pulmonary health among children in El Paso, Texas.

PubMed

Svendsen, Erik R; Gonzales, Melissa; Mukerjee, Shaibal; Smith, Luther; Ross, Mary; Walsh, Debra; Rhoney, Scott; Andrews, Gina; Ozkaynak, Halûk; Neas, Lucas M

2012-10-01

Investigators examined 5,654 children enrolled in the El Paso, Texas, public school district by questionnaire in 2001. Exposure measurements were first collected in the late fall of 1999. School-level and residence-level exposures to traffic-related air pollutants were estimated using a land use regression model. For 1,529 children with spirometry, overall geographic information system (GIS)-modeled residential levels of traffic-related ambient air pollution (calibrated to a 10-ppb increment in nitrogen dioxide levels) were associated with a 2.4% decrement in forced vital capacity (95% confidence interval (CI): -4.0, -0.7) after adjustment for demographic, anthropomorphic, and socioeconomic factors and spirometer/technician effects. After adjustment for these potential covariates, overall GIS-modeled residential levels of traffic-related ambient air pollution (calibrated to a 10-ppb increment in nitrogen dioxide levels) were associated with pulmonary function levels below 85% of those predicted for both forced vital capacity (odds ratio (OR) = 3.10, 95% CI: 1.65, 5.78) and forced expiratory volume in 1 second (OR = 2.35, 95% CI: 1.38, 4.01). For children attending schools at elevations above 1,170 m, a 10-ppb increment in modeled nitrogen dioxide levels was associated with current asthma (OR = 1.56, 95% CI: 1.08, 2.50) after adjustment for demographic, socioeconomic, and parental factors and random school effects. These results are consistent with previous studies in Europe and California that found adverse health outcomes in children associated with modeled traffic-related air pollutants.