Log In Sign up
The largest database of trusted experimental protocols
> Chemicals & Drugs > Hazardous or Poisonous Substance > Diesel Exhaust

Diesel Exhaust

Diesel exhaust is a complex mixture of particulate matter, gases, and other compounds generated by the combustion of diesel fuel in diesel engines.
This potent mixture has been linked to various health concerns, including respiratory issues, cardiovascular disease, and cancer.
Understanding the composition and impact of diesel exhaust is crucial for developing effective mitigation strategies and protecting public health.
By leveraging PubCompare.ai's innovative AI-driven platform, researchers can optimize their diesel exhaust studies, locate the best methods from literature, pre-prints, and patents, and enhance the reproducibility and accuracy of their work.
Explore the depths of diesel exhaust research and take your studies to the next level with the help of PubCompare.ai's cutting-edge tools.

Most cited protocols related to «Diesel Exhaust»

1
Occupational Diesel Exhaust Exposure
Cited 13 times
Literature on occupational DE exposure was identified from MEDLINE, TOXLINE, NIOSHTIC, and the NIOSH Health Hazard Evaluation database using the search terms ‘diesel’, ‘diesel particulate matter’, ‘diesel exhaust’, ‘occupational’, and ‘exposure’. In addition, personal archives added literature not present in these databases. Literature from 1957 through 2007 was identified. Information on occupational DE exposure was abstracted. The information presented includes a brief description of the industry and processes and an overview of exposure measurements and reported determinants. The information is organized by on-road and off-road equipment. Off-road uses were further categorized into mining, railroad, and other applications.
The assessment of exposure to DE is complicated because no single constituent of DE is considered a unique marker of exposure(Lloyd, et al., 2001 (link)). In the past, investigators have used several non-specific components of DE as surrogates, such as respirable particulate matter (PMR), carbon monoxide (CO), nitrogen oxide (NO), or nitrogen dioxide (NO2). In the 1990s, two more specific surrogates for DE have been increasingly used: EC and submicron particulate matter (PMs) (Steenland, et al., 1998 (link)). To evaluate both current and past exposure levels, EC, PMR (including PM2.5), PMS, NO2, NO, and CO were selected for this report. For these agents, all occupational personal measurement data reported in the literature were summarized in a database. Area samples that were likely representative of personal exposures were also included. Because most of the agents are not specific for diesel exhaust, an indication of the presence of diesel engines was required for inclusion. For practical reasons, only agents with a total of 5 or more measurements on all jobs combined in a study were included. Studies that did not report sample size were included when it could be inferred from the text that at least 5 measurements were likely for an agent. Efforts were made to exclude studies reporting the same exposure data.
The abstracted information on the measurements included industry, description of job/task/location, country, sample year (when not provided publication year was used), type of sample (area or personal), number of samples, sampling duration, sampling and analytic method, and summary statistics. All sampling durations except peak measurements were included and were categorized as <1 hour, 1–4 hours, or ≥4 hours. The arithmetic mean (AM) and standard deviation (SD) and geometric mean (GM) and geometric standard deviation (GSD) were included. Summary statistics were calculated when only individual measurement results were presented. When averages for similar jobs were presented in a single publication, these were combined into broader job categories by weighting the AMs and GMs by the number of measurements. For calculations, non-detectable (ND) values or averages were substituted by the detection limit divided by √2 (Hornung, et al., 1990 ). When means were presented without specifying the number of measurements, an unweighted average was calculated. In addition, the range of SDs or GSDs across jobs is presented. When the AM was not reported, it was estimated. When the GM and GSD were reported, a lognormal distribution was assumed and the AM was estimated using the formula (Aitchison, et al., 1969 ):
AM=GM×exp[1/2×(ln(GSD))2]
If only the range was provided, the GM was estimated by squaring the midpoint of the log transformed minimum and maximum levels and the GSD was estimated by squaring the range of the log transformed values divided by four (Hein, et al., 2008 (link)). The units of EC and PM are in μg/m3, and CO, NO and NO2 units are in ppm. When units of the gases were in mass/m3, they were converted to ppm assuming standard room temperature and pressure.
Determinants of exposure are described that were either explicitly identified or implicitly identified by contrasting scenarios. Explicitly identified determinants for area measurements not representative of personal exposure, and measurements of other DE surrogates not selected for the measurement summary herein are also presented. When provided by the original paper, the exposure levels for the contrasting scenarios are given in the text. Statistical significance is indicated when reported by the original study investigators.
Pronk A., Coble J, & Stewart P. (2009). Occupational exposure to diesel engine exhaust: A literature review. Journal of exposure science & environmental epidemiology, 19(5), 443-457.
Publication 2009
Diesel Exhaust Gases Monoxide, Carbon Nitrogen Dioxide Nitrogen Oxides Occupational Exposure Pressure
2
Occupational Wood Dust Exposure and Lung Cancer
Cited 7 times
Unconditional logistic regression [27 ] was used to estimate odds ratios (ORs) and their 95% confidence intervals (CIs) for the association between each occupational factor and lung cancer, adjusting for the following a priori potential confounders: age, median income in the census tract of residence and individual schooling level as markers of socioeconomic status, ethnic-cultural background (French, Anglo, other), respondent status (self, proxy), ever occupational exposure to asbestos, diesel engine exhaust, formaldehyde, cadmium, chromium IV compounds, nickel compounds, silica dust, and tobacco smoking. After comparison of several parameterizations of the smoking variables in our data sets, we selected the comprehensive smoking index (CSI), which proved to most accurately fit the data and integrates duration, intensity and time since quitting smoking [28 (link)]. This index best captures the confounding nature of smoking history since it takes into account the timing of smoking exposure, and not just the duration and intensity.
There is an ongoing debate as to whether it is appropriate to adjust for markers of socioeconomic status (SES) in occupational studies [29 (link)–31 (link)], with some arguing that SES is a confounder to be adjusted for and others that it is a collider to be omitted from statistical models. It may also be debated whether the inclusion in the models of other occupational carcinogens may constitute a form of over-adjustment. To examine whether inclusion of SES or other occupational carcinogens has the potential to bias the association between wood dust and lung cancer, we conducted a sensitivity analysis in which we compared results on wood dust exposure from four models: i) without adjustment for SES nor for other occupational carcinogens, ii) adjustment for SES but not other occupational carcinogens, iii) adjustment for other occupational carcinogens but not SES, and iv) adjustment for both SES and other occupational carcinogens. The other core covariates remained in all models.
Occupational exposure indices were based on four dimensions of information that were available whenever the experts assigned an exposure to a subject: probability that the exposure took place, concentration, frequency, and years of beginning and ending exposure. Using these dimensions, an a priori cumulative exposure index was calculated with the following categories: ‘no exposure’ consisted of never exposed subjects and those for whom the degree of confidence that the exposure actually occurred was coded as just ‘possible’ by the hygienists; the remaining subjects, whose exposure to wood dust was rated as probable or definite, were considered as ‘exposed’ for these analyses. We further subdivided those ‘exposed’ into two exposure groups: ‘substantial exposure’ was assigned to subjects who had been exposed to medium or high concentrations, during more than 5% of their work week, and for 5 years or more, whereas ‘non-substantial exposure’ was assigned to the remaining exposed subjects. Exposures having occurred less than five years previous to the index date were discounted on latency grounds. Other cumulative exposure indices were calculated using different combinations of weights to the exposure dimensions frequency, concentration, duration and latency. None of these indices showed better goodness-of-fit than the simple categories described above so they are not presented here.
Besides treating smoking as an a priori confounder, we explored potential effect modification by smoking. Since the number of never smokers among cases was very low, the non-smokers category was supplemented with lifetime low intensity smokers. Operationally, we defined lifetime low intensity smokers as individuals having a CSI value below the 25th percentile on this scale. Because of the way it is constructed [28 (link)], the CSI index does not translate easily onto the duration or daily amount of pack-year scale. We can illustrate the amount of smoking in these categories by showing two smoking profiles that would fall on the 25th percentile of the CSI scale, namely: a current smoker who smoked three cigarettes per day during 40 years (with lifetime cumulative exposure of 6 pack-years), or a former smoker who smoked six cigarettes a day for 30 years and quit 10 years ago (with cumulative exposure of 9.8 pack years). Smokers with CSI values above the 25th percentile were considered medium/heavy smokers. To evaluate the statistical significance of the difference in ORs between the two strata of smokers, we carried out an analysis based on all subjects including the two variables, smoking status (binary) and exposure to wood dust (binary), by testing their cross-product term. The continuous CSI variables were maintained as a covariate in the models to avoid any residual confounding within the smoking status strata.
The associations between wood dust and the most prevalent histologic types of lung cancer, namely squamous cell, adenocarcinoma, small cell and large cell, were also evaluated.
Vallières E., Pintos J., Parent M.E, & Siemiatycki J. (2015). Occupational exposure to wood dust and risk of lung cancer in two population-based case–control studies in Montreal, Canada. Environmental Health, 14, 1.
Full text: Click here
Publication 2015
Adenocarcinoma Asbestos Cadmium Carcinogens Cells Chromium Compounds Diesel Exhaust Ethnicity Formaldehyde Hygienist, Dental Hypersensitivity Lung Cancer Nickel Non-Smokers Occupational Exposure Silicon Dioxide Squamous Epithelial Cells
3
Printex 90 Nanoparticle Characterization and Instillation
Cited 6 times
The NPCB (Printex 90) was a gift from Evonik (Frankfurt, Germany). Particle preparation, characterization, and instillation procedures were described in detail previously [Jacobsen et al., 2007 (link); Saber et al., 2009 (link); Bourdon et al., 2012 (link); Boisen et al., 2013 (link)]. NPCB has a primary particle size of 14nm and the particles were composed of 99% C, 0.8% N, and 0.01% H2 [Jacobsen et al., 2007 (link)]. The total content of polycyclic aromatic hydrocarbons in Printex 90 was 0.0742 mg/g, that is, about 3000-fold less than diesel exhaust particles [Jacobsen et al., 2007 (link)]. The endotoxin level was 0.142 EU/mg Printex 90 [Jackson et al., 2011b (link)]. The specific surface area was 295–338 m2/g, corresponding to a theoretical average spherical particle size 8.1–9.5 nm [Saber et al., 2005 (link)]. NPCB particles were suspended in 0.2 µm filtered, -irradiated Nanopure Diamond UV water (Pyrogens: < 0,001 EU/ml, total organic carbon: < 3.0 ppb [Jackson et al., 2012a (link), b (link)]), and sonicated on ice, for 16 min without pause using a Branson Sonifier S-450D (Branson Ultrasonics Corp., Danbury, CT) equipped with a disruptor horn (model number 101–147-037). Two suspensions were prepared at concentrations 0.12 mg/ml (6 µg/instillation) and 3.24 mg/ml (162 µg/instillation). A suspension with a final concentration of 0.12 mg/ml was subsequently diluted 1:3 to obtain 0.04 mg/ml (2 µg/instillation) and diluted further 1:3 for the lowest dose of 0.00134 mg/ml (0.67 µg/instillation). After each dilution, suspensions were sonicated for 2 minutes. Particle suspensions were instilled in mice directly after sonication up to 1 hr to assure their homogeneity. Vehicle solution was prepared by sonication of Nanopure Diamond water in the same conditions as described above.
Kyjovska Z.O., Jacobsen N.R., Saber A.T., Bengtson S., Jackson P., Wallin H, & Vogel U. (2014). DNA Damage Following Pulmonary Exposure by Instillation to Low Doses of Carbon Black (Printex 90) Nanoparticles in Mice. Environmental and Molecular Mutagenesis, 56(1), 41-49.
Publication 2014
Carbon Diamond Diesel Exhaust Endotoxins Horns Mice, House Polycyclic Hydrocarbons, Aromatic Pyrogens Technique, Dilution Ultrasonics
4
Gasoline and Diesel Exhaust Exposure in Mice
Cited 5 times
Twelve-week-old male Apo E−/− mice (strain B6.129P2-Apoetm1Unc N11, on a C57Bl6 background, backcrossed for 10 generations; Taconic, Oxnard, CA) were placed on a high fat diet (TD88137 Custom Research Diet, Harlan Teklad, Madison, WI; 21.2% fat content by weight, 1.5 g/kg cholesterol content) beginning 30 days prior to initiation of exposure protocol or normal rodent chow. Mice were then randomly grouped to be exposed by whole-body inhalation to a mixture of whole gasoline engine exhaust and diesel engine exhaust (MVE: 30 μg PM/m3 gasoline engine emissions + 70 μg PM/m3 diesel engine, n = 20) or filtered-air (controls, n = 20) for 6 h/d for a period of 30 days. In a separate study, 12-week old male C57Bl6 wildtype mice (Jackson Labs, Bar Harbor, Maine) fed a standard mouse chow diet, were exposed by the same methods to either filtered air (n = 8) or MVE (n = 8). MVE was created by combining exhaust from a 1996 GM gasoline engine and a Yanmar diesel generator system, as previously reported [42 (link),59 (link),60 (link)]. Mice were housed in standard shoebox cages within an Association for Assessment and Accreditation of Laboratory Animal Care International-approved rodent housing facility (2 m3 exposure chambers) for the entirety of the study, which maintained constant temperature (20–24°C) and humidity (30–60% relative humidity). Mice had access to chow and water ad libitum throughout the study period, except during daily exposures when chow was removed. All procedures were approved by the Lovelace Respiratory Research Institute’s Animal Care and Use Committee and conform to the Guide for the Care and Use of Laboratory Animals published by the US National Institutes of Health (NIH Publication No. 85–23, revised 1996).
Oppenheim H.A., Lucero J., Guyot A.C., Herbert L.M., McDonald J.D., Mabondzo A, & Lund A.K. (2013). Exposure to vehicle emissions results in altered blood brain barrier permeability and expression of matrix metalloproteinases and tight junction proteins in mice. Particle and Fibre Toxicology, 10, 62.
Full text: Click here
Publication 2013
Animals Animals, Laboratory Apolipoproteins E Cholesterol Diesel Exhaust Diet, High-Fat Engine Exhaust Human Body Humidity Inhalation Males Mice, House Respiratory Rate Rodent Therapy, Diet
5
PM2.5 Speciation and Mortality Associations
Cited 5 times
We obtained PM2.5 speciation data for the 4-year period 2000 through 2003 from the CARB (CARB 2004 ). The speciation monitors were part of the State and Local Air Monitoring Stations network, and were filter-based Met One Speciation Air Sampling Systems (Met One Instruments Inc., Grants Pass, OR). We included only counties with ≥ 180 days of observations with PM2.5 species data to ensure sufficient statistical power. Thus, our study of PM2.5 components was limited to deaths occurring in six California counties, which included approximately 8.7 million people, or 25% of the state’s population. Each of the six counties had two monitors measuring PM2.5 components and mass. In three counties (Fresno, Kern, and Riverside), the two monitors were located within four meters of each other in the cities of Fresno, Bakersfield, and Rubidoux, respectively. In the other counties (Sacramento, San Diego, and Santa Clara) the monitors were not co-located. Fresno, Kern, Riverside, and Sacramento Counties reported data every third day, whereas San Diego and Santa Clara Counties reported data every sixth day. For the speciation analyses, the number of observation days available ranged from 243 (San Diego County) to 395 (Sacramento County). The following constituents of PM2.5 were measured as 24-hr averages: EC, OC, nitrates (NO3), sulfates (SO4), aluminum, bromine, calcium, chlorine, copper, iron, potassium, manganese, nickel, lead, sulfur, silicon, titanium, vanadium, and zinc. These PM2.5 components represent multiple sources of PM2.5, including gasoline combustion, diesel exhaust, wood smoke, crustal material, and secondary pollutants, among others.
We also analyzed PM2.5 mass using a larger data set from 1999 through 2003 using all available monitors (including those that did not collect species data) for nine California counties—the same six counties as above plus Contra Costa, Los Angeles, and Orange Counties. The nonspeciated network data were obtained from the CARB (2004) . PM2.5 monitors were filter-based samplers (model RAAS2.5–300; Thermo Andersen, Smyrna, GA). From the nonspeciated network, six counties had only one monitor each collecting daily PM2.5 data, whereas Los Angeles, San Diego, and Santa Clara Counties had three, three, and two monitors, respectively.
To allow adjustment for the effect of weather on mortality, we collected daily average temperature and humidity data at meteorologic stations in each of the counties. Hourly temperature data were obtained from the National Oceanic and Atmospheric Administration (NOAA) National Climatic Data Center (NCDC 2004 ). All daily mortality, pollutant, and meteorologic data were converted into a SAS database (SAS Institute Inc., Cary, NC) and merged by date.
Ostro B., Feng W.Y., Broadwin R., Green S, & Lipsett M. (2006). The Effects of Components of Fine Particulate Air Pollution on Mortality in California: Results from CALFINE. Environmental Health Perspectives, 115(1), 13-19.
Full text: Click here
Publication 2006
Aluminum Bromine Calcium, Dietary Chlorine Climate Copper Diesel Exhaust Environmental Pollutants Humidity Iron Manganese Nickel Nitrates Potassium Ribs Silicon Smoke Sulfates, Inorganic Sulfur Titanium Vanadium Zinc

Most recents protocols related to «Diesel Exhaust»

1
Investigating Diesel Exhaust and Particulate Matter Exposure in Mice
Cited 1 time
Diesel exhaust particles (DEP; NIST 1650b, pH 6.6–6.8) or particulate matter (PM; NIST 1649b) dissolved in sterile PBS (Cat# D8537, Sigma), or PBS alone as control, were administered either to the lung by intratracheal instillation or to the gut by gavage starting at 5–6 weeks of age until sacrifice (for a detailed characterization of the chemical composition see embedded link). Intratracheal instillation was performed as previously described [57 (link)]. Suspension characteristics of the dissolved particles see Additional file 1: Table S2.
For gavage, mice received daily 12 µg DEP or PM (or 60 µg; dose escalation experiment, see Additional file 1: Figure S1) suspended in 200 µL sterile PBS or PBS as control. In the “prestressed” condition, 20 µg DEP daily were used. The rationale for the slightly higher dose in the “prestressed” setting was that we hypothesized that the time frame to develop glucose intolerance would be shorter in a “prestressed” setting induced by HFD/STZ. We therefore assumed a shorter exposure period and chose a slightly higher weekly exposure dose to approximate the total deposition dose of the standard diet model. While gavage was performed 5 days a week, intratracheal instillation was conducted only twice weekly. To keep both models comparable, the same weekly dose of total 60 µg or 100 µg (in case of diabetic mice) DEP or PM, respectively were instilled. The lower dose represents an average daily dose of 8.6 µg/mouse and approximately equates a daily inhalation exposure of about 160 µg/m3 (calculated by the daily exposure divided by the daily inhaled air volume).
The calculation of the daily inhaled air volume was based on a minute volume-to-body weight ratio of 1.491 (L/(min*kg)): 1.491Lmin∗kg∗0.025kg∗60min∗24h=53Lday=0.053m3day
Bosch A.J., Rohm T.V., AlAsfoor S., Low A.J., Keller L., Baumann Z., Parayil N., Stawiski M., Rachid L., Dervos T., Mitrovic S., Meier D.T, & Cavelti-Weder C. (2023). Lung versus gut exposure to air pollution particles differentially affect metabolic health in mice. Particle and Fibre Toxicology, 20, 7.
Full text: Click here
Publication 2023
Body Weight Diesel Exhaust Diet Inhalation Exposure Intolerances, Glucose Lung Mus Reading Frames Sterility, Reproductive Tube Feeding
2
Soot Combustion Catalysis by CeMn
The catalytic activity of cerium manganese catalyst for soot combustion was measured by means of TGA/DSC thermogravimetric analyzer (METTLER, Swiss) with Printex-U (Degussa, Germany) used as the model of diesel soot. The soot and the catalyst (weight ratio was 1:10) were carefully ground in a mortar for 10 min to achieve the “tight contact” condition. In order to make the evaluation condition similar to the actual condition, the catalyst and soot were mixed with shovel for 5 min to achieve the “loose contact” condition. The reaction test was carried out with 10% O2/N2 which was close to the oxygen concentration in diesel exhaust. Activity tests were carried out from 30 to 600 °C under a gas flow rate of 30 ml/min, and the heating rate was maintained at 10 °C/min. Tm represents the temperature corresponding to the maximum heat release during soot combustion in the DSC diagram and the peak value of the DTG curve (They're the same). The lower the Tm, the easier the combustion of soot and the better the activity of the catalyst. TPO-MS was used to detect the CO2, CO and H2O produced during the heating process (Supporting information).
Zhu Y., Chen Z., Li H., Wang Q., Liu X., Hu Y., Su C., Duan R., Chen S, & Lan L. (2023). Effect of oxygen vacancy and highly dispersed MnOx on soot combustion in cerium manganese catalyst. Scientific Reports, 13, 3386.
Full text: Click here
Publication 2023
Cerium Diesel Exhaust enzyme activity Manganese Oxygen Soot
3
Prenatal Exposure to Diesel Exhaust Particles
Diesel exhaust particles (DEP) were obtained from Dr. Ian Gilmour at the Environmental Protection Agency and exposures were conducted in accordance with Bolton et al., 201331 (link). Multiparous C57Bl/6J females were time mated. A vaginal plug was taken as an indication of pregnancy and set as embryonic day (E)0. Females were then pair-housed based on embryonic day until E13. Instillations occurred every 3 days throughout pregnancy, beginning on E2, totaling 6 instillations. Briefly, females were weighed, anesthetized with 2% isoflurane, and administered either 50 μg/50 μL of DEP in vehicle (0.05% Tween20 in PBS; dose previously validated/published19 (link),31 (link),32 (link)), or vehicle (CON) via oropharyngeal instillation during which females are suspended by their incisors from a plastic wire and the instillation is administered over the course of 30 sec. Females were monitored until they were awake before returning to their home cages.
Bilbo S., Smith C., Rendina D., Kingsbury M., Malacon K., Nguyen D., Tran J., Devlin B., Raju R., Clark M., Burgett L., Zhang J., Cetinbas M., Sadreyev R., Chen K, & Iyer M. (2023). Microbial modulation prevents the effects of pervasive environmental stressors on microglia and social behavior, but not the dopamine system. Research Square.
Full text: Click here
Publication Preprint 2023
Diesel Exhaust Embryo Females Incisor Isoflurane Oropharynxs Pregnancy Tween 20 Vagina
4
Receptor Models for Traffic-Originated VOCs
To derive the fraction of traffic-originated VOCs from the ambient concentrations, we based the analysis on the work by Hellén et al. (2003 (link)) focusing on measured non-methane hydrocarbons (NMHCs) in Helsinki. Using a chemical mass balance receptor model and a multivariate receptor model Unmix they have determined seasonal source contributions for measured C 2 –C 10 hydrocarbon concentrations. For details of the measurements and applied methods, we refer to Hellén et al. (2003 (link)) and references within. Based on data collected in 2001 and the receptor models, Hellén et al. (2003 (link)) have determined the total contribution from traffic (liquid gasoline, gasoline vapor, gasoline exhaust and diesel exhaust) to the measured mass of NMHCs to be 57.3% in August. The fraction of NMHCs advected by long-range transported air masses was 37%. The determined source profiles were associated with a 15% uncertainty.
To create the scenario with changed behavior and correspondingly changed emissions, we multiplied the fraction in VOC concentrations that was assumed to be traffic-originated ( 0.57· [VOC n ] for each traffic-originated VOC species n) by (1-cnon/100) .
Hulkkonen M., Kaaronen R.O., Kokkola H., Mielonen T., Clusius P., Xavier C., Hellén H., Niemi J.V, & Malila J. (2023). Modeling non-linear changes in an urban setting: From pro-environmental affordances to responses in behavior, emissions and air quality. Ambio, 52(5), 976-994.
Full text: Click here
Publication 2023
Diesel Exhaust Hydrocarbons Methane
5
Deployer Particulate Exposure Index
All study subjects completed a detailed questionnaire that elicited information on military deployment‐specific exposures including frequency and intensity of exposure to particulate matter generated from burn pits, sandstorms, and diesel exhaust. We examined weighted respiratory hazards for participating deployers using a modification of a previously published exposure matrix (Zell‐Baran et al., 2019 (link)). Each participant's particulate matter inhalational exposure index was calculated using the following formula: (Months Deployed*Frequency of Exposure to Burn Pits in days/month) + (Months Deployed*Frequency of Exposure to Sandstorms in days/month) + (Months Deployed*Frequency of Exposure to Diesel Exhaust in days/month).
Onofrei C.D., Gottschall E.B., Zell‐Baran L., Rose C.S., Kraus R., Pang K, & Krefft S.D. (2023). Unexplained dyspnea linked to mitochondrial myopathy following military deployment to Southwest Asia and Afghanistan. Physiological Reports, 11(2), e15520.
Full text: Click here
Publication 2023
Diesel Exhaust Inhalation Exposure Respiratory Rate Van der Woude syndrome

Top products related to «Diesel Exhaust»

1
Dimethyl sulfoxide (dmso) by Merck Group
Sourced in United States, Germany, United Kingdom, China, Italy, Sao Tome and Principe, France, Macao, India, Canada, Switzerland, Japan, Australia, Spain, Poland, Belgium, Brazil, Czechia, Portugal, Austria, Denmark, Israel, Sweden, Ireland, Hungary, Mexico, Netherlands, Singapore, Indonesia, Slovakia, Cameroon, Norway, Thailand, Chile, Finland, Malaysia, Latvia, New Zealand, Hong Kong, Pakistan, Uruguay, Bangladesh
DMSO is a versatile organic solvent commonly used in laboratory settings. It has a high boiling point, low viscosity, and the ability to dissolve a wide range of polar and non-polar compounds. DMSO's core function is as a solvent, allowing for the effective dissolution and handling of various chemical substances during research and experimentation.
2
Srm 2975 by Merck Group
SRM 2975 is a reference material produced by Merck Group. It is a diesel particulate matter intended for use as a calibration standard in the analysis of diesel exhaust particulate matter.
3
Zetasizer nano z by Malvern Panalytical
Sourced in United Kingdom, Germany, United States, France, Japan, China, Netherlands, Morocco, Spain, Cameroon
The Zetasizer Nano ZS is a dynamic light scattering (DLS) instrument designed to measure the size and zeta potential of particles and molecules in a sample. The instrument uses laser light to measure the Brownian motion of the particles, which is then used to calculate their size and zeta potential.
4
C57bl 6 male and female mice by Jackson ImmunoResearch
Sourced in United States, Montenegro
C57BL/6 male and female mice are a commonly used inbred mouse strain. They are widely utilized in biomedical research due to their well-characterized genetic and physiological traits.
5
Rtx 5ms capillary column by Restek
Sourced in United States, Japan
The Rtx-5MS capillary column is a high-performance gas chromatography column designed for a wide range of applications. It features a 5% diphenyl and 95% dimethyl polysiloxane stationary phase, which provides excellent separation and peak shape for a variety of analytes. The column is inert, durable, and suitable for use with a wide range of solvents and sample types.
6
Printex u by Evonik
Printex-U is a carbon black product manufactured by Evonik. It is a fine powder with a high purity and specific surface area, designed for use as a laboratory and research material.
7
Ptfe syringe filter by Sartorius
Sourced in Germany
The PTFE syringe filter is a laboratory equipment designed to filter small volumes of liquid samples. It consists of a PTFE (Polytetrafluoroethylene) membrane that removes particulate matter from the sample, ensuring a clear and contaminant-free solution for further analysis or processing.
8
Printex 90 by Evonik
Sourced in Germany
Printex 90 is a high-performance carbon black product used as a reinforcing filler in various applications. It is a fine, dry powder with a high surface area and low structure. Printex 90 is a versatile material that can be used in a wide range of industries, including rubber, plastics, and coatings.
9
Tween 20 by Merck Group
Sourced in United States, Germany, United Kingdom, Italy, France, China, Spain, Australia, Japan, India, Poland, Sao Tome and Principe, Switzerland, Macao, Belgium, Canada, Denmark, Israel, Mexico, Netherlands, Singapore, Austria, Ireland, Sweden, Argentina, Romania
Tween 20 is a non-ionic detergent commonly used in biochemical applications. It is a polyoxyethylene sorbitan monolaurate, a surfactant that can be used to solubilize and stabilize proteins and other biomolecules. Tween 20 is widely used in various laboratory techniques, such as Western blotting, ELISA, and immunoprecipitation, to prevent non-specific binding and improve the efficiency of these assays.
10
Ch223191 by Merck Group
Sourced in United States, Germany, Italy
CH223191 is a laboratory equipment product. It is used for scientific research and analysis purposes. The core function of this product is to facilitate the measurement and analysis of various samples and materials in a laboratory setting. However, a detailed description of its specific features and capabilities cannot be provided while maintaining an unbiased and factual approach.

More about "Diesel Exhaust"

Diesel exhaust, a complex mixture of particulate matter, gases, and other compounds, has been extensively studied for its impact on human health.
This potent concoction, generated by the combustion of diesel fuel in diesel engines, has been linked to a variety of health concerns, including respiratory issues, cardiovascular disease, and cancer.
By tapping into this resource, scientists and health professionals can stay up-to-date with the latest findings and developments in this field.
PubCompare.ai's innovative AI-driven platform offers a powerful tool for optimizing diesel exhaust research protocols.
This cutting-edge solution allows researchers to locate the best methods from literature, pre-prints, and patents, ensuring that their studies are based on the most reliable and effective techniques.
Leveraging PubCompare.ai's AI-powered comparisons, researchers can enhance the reproducibility and accuracy of their diesel exhaust studies.
This is particularly important when working with DMSO, SRM 2975, Zetasizer Nano ZS, C57BL/6 male and female mice, Rtx-5MS capillary column, Printex-U, PTFE syringe filter, Printex 90, Tween 20, and CH223191, all of which play a crucial role in diesel exhaust research.
By exploring the depths of diesel exhaust research and utilizing PubCompare.ai's cutting-edge tools, researchers can take their studies to the next level, contributing to a better understanding of this complex and potent mixture and its impact on public health.
With the right tools and resources, the quest to mitigate the adverse effects of diesel exhaust can be advanced, ultimately leading to improved outcomes for individuals and communities.