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Nitrogen Dioxide

Nitrogen dioxide (NO2) is a highly reactive and toxic gas that plays a crucial role in atmospheric chemistry and environmental studies.
It is a byproduct of fossil fuel combustion and a key contributor to air pollution.
PubCompare.ai's innovative platform helps researchers optimize their nitrogen dioxide research by locating the best protocols from literature, pre-prints, and patents.
With AI-driven comparisons, the tool enhances reproducibility and accuracy, empowering researchers to make informed decisions and take their nitrogen dioxide studies to new heights.
Explore PubCompare.ai's cutting-edge platform and discover new insights into this important environmental pollutant.

Most cited protocols related to «Nitrogen Dioxide»

1
Exposure Assessment in Air Pollution Study
Cited 18 times
Exposure to air pollution for each cohort member was assigned by three different approaches, two based on the regulatory monitoring network and one based on dedicated sampling campaigns. The regulatory monitoring network was operated by the British Columbia Ministry of Environment and Metro Vancouver and includes daily measurements at 24 monitors for ozone, 22 for nitric oxide/ nitrogen dioxide, 14 for sulfur dioxide, 19 for carbon monoxide, 19 for particulate matter < 10 μm in aerodynamic diameter (PM10), and 7 for PM < 2.5 μm in aerodynamic diameter (PM2.5). The monitoring data were assigned to individuals at their 6-digit postal code of residence. The 6-digit postal code typically corresponds to one block-face in urban areas; areas may be considerably larger in rural areas with low population density.
Concentrations were assigned to postal codes by nearest monitor and inverse-distance weighting (IDW) approaches. This approach provided high temporal resolution (daily measures for most days) with less precise spatial resolution than land use regression estimates. For the nearest monitor assignment, we assigned for each day a concentration from the operational monitor closest to the postal code of interest and within 10 km. We then computed monthly averages for each individual for the full duration of their pregnancy. For the IDW approach we used an inverse-distance (1/distance) weighted average of the three closest monitors within 50 km to compute a monthly mean concentration. For both approaches, a month was considered missing if there was a gap of > 5 consecutive days in air monitoring data or if there were > 10 missing days in a given month. Using the monthly averages, we then computed mean exposures for each mother for the full duration of pregnancy, the first and last 30 days of pregnancy, and the first and last 3 months of pregnancy. Exposures were updated with change in postal code of residence and weighted by time spent in multiple residences. Postal code information for mothers was obtained from the provincial health registration and health care contact records.
Brauer M., Lencar C., Tamburic L., Koehoorn M., Demers P, & Karr C. (2008). A Cohort Study of Traffic-Related Air Pollution Impacts on Birth Outcomes. Environmental Health Perspectives, 116(5), 680-686.
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Publication 2008
Air Pollution Face Fingers Maternal Exposure Monoxide, Carbon Mothers Nitrogen Dioxide Oxide, Nitric Ozone Pregnancy Residency Sulfur Dioxide
2
Ambient Air Pollution Exposure Assessment
Cited 14 times
California air pollutant data was obtained from the U.S. Environmental Protection Agency’s (EPA) Air Quality System (AQS) database.21 Data were available for nitrogen dioxide (NO2, ppb), ozone (O3, ppb), particulate matter with diameter < 10 μm (PM10, μg/m3) and 2.5 μm (PM2.5, μg/m3). Hourly measurements were summarized as 24-hour averages for NO2, PM10, and PM2.5 and average 8-hour daily maximum for O3. Monthly average concentrations were spatially interpolated to residence locations from the up to 4 closest air quality monitoring stations within a 50 km radius using the well-established method of inverse distance weighting,22 ,23 (link) with the decay parameter equal to the inverse of the square of the distance of the residence from each monitoring site. Interpolation performance is summarized in eTable 1. We excluded exposure assignments when the nearest monitor was located > 25 km away or a geocode match was unavailable. Residential ambient air pollution exposure assignments were calculated as the average of the patient-level interpolated monthly concentrations from the date of diagnosis to the date of last follow-up or death. PM2.5 exposure assignments were only available for patients diagnosed in 1998 and later because routine monitoring did not start until 1998. Our primary goal was to evaluate associations with large-scale, regional variation in ambient pollutants, so to account for potential confounding by local traffic, we calculated and adjusted for distance from residential address to primary interstate highways and primary US and state highways.
Eckel S.P., Cockburn M., Shu Y.H., Deng H., Lurmann F.W., Liu L, & Gilliland F.D. (2016). Air Pollution Affects Lung Cancer Survival. Thorax, 71(10), 891-898.
Publication 2016
Air Pollutants Air Pollution Environmental Pollutants Nitrogen Dioxide Ozone Patients Radius
3
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
4
Global Air Pollution Mortality Data
Cited 11 times
We obtained health and environmental data from the MCC database, which has been described previously.10 (link),12 (link) The current analysis was limited to locations that had available data on air pollution (652 urban areas in 24 countries or regions, with the data covering the period from 1986 through 2015) (Table S1 in the Supplementary Appendix, available with the full text of this article at NEJM.org). Data on mortality were obtained from local authorities within each country. Causes of death were classified according to codes in the International Classification of Diseases, 9th Revision (ICD-9) or 10th Revision (ICD-10), whichever was available. In each location, mortality was represented by daily counts of either death from nonexternal causes (ICD-9 codes 0 to 799 and ICD-10 codes A0 to R99) or, when such data were unavailable, daily counts of death from any cause. We also collected mortality data for two main causes of death: cardiovascular disease (ICD-10 codes I00 to I99) and respiratory disease (ICD-10 codes J00 to J99).13 We obtained daily data on PM10 in 598 cities and on PM2.5 in 499 cities. Data on both pollutants were available in 445 cities in 16 countries or regions. The geographic distributions of the cities that had data on PM10 and PM2.5, as well as the annual mean PM concentrations over the period studied for each city, are provided in Figure 1 and Figure 2, respectively (also see the interactive map, available at NEJM.org). Daily data on gaseous pollutants (ozone, nitrogen dioxide, sulfur dioxide, and carbon monoxide) were obtained where available. We also collected data on the daily mean temperature and daily mean relative humidity. To avoid potential consequences of including outlying values of exposure data, we used trimmed data, in which the highest 5% and lowest 5% of PM10 and PM2.5 measurements were excluded.14 (link)
Liu C., Chen R., Sera F., Vicedo-Cabrera A.M., Guo Y., Tong S., Coelho M.S., Saldiva P.H., Lavigne E., Matus P., Ortega N.V., Garcia S.O., Pascal M., Stafoggia M., Scortichini M., Hashizume M., Honda Y., Hurtado-Díaz M., Cruz J., Nunes B., Teixeira J.P., Kim H., Tobias A., Íñiguez C., Forsberg B., Åström C., Ragettli M.S., Guo Y.L., Chen B.Y., Bell M.L., Wright C.Y., Scovronick N., Garland R.M., Milojevic A., Kyselý J., Urban A., Orru H., Indermitte E., Jaakkola J.J., Ryti N.R., Katsouyanni K., Analitis A., Zanobetti A., Schwartz J., Chen J., Wu T., Cohen A., Gasparrini A, & Kan H. (2019). Ambient Particulate Air Pollution and Daily Mortality in 652 Cities. The New England journal of medicine, 381(8), 705-715.
Publication 2019
Air Pollution Cardiovascular Diseases Environmental Pollutants Gases Humidity Monoxide, Carbon Nitrogen Dioxide Ozone Respiration Disorders Sulfur Dioxide
5
Comprehensive Environmental Exposure Assessment
Cited 10 times
Environmental factors are manifold and complicated. In order to evaluate exposure to a wide range of environmental factors, the following four approaches are employed:
1. Questionnaires
A part of each questionnaire is designated to collect information about chemical exposure, e.g. the use of organic solvents, kerosene, pesticides, disinfectants, heavy metals, antineoplastic drugs, narcotics, paints, hair dyes, and printer inks. Exposure to noise, vibration, high/low temperature, and dusts is also asked in the questionnaires.
2. Chemical analysis of bio-specimens
Chemical substances or their metabolites are measured in peripheral blood, cord blood, breast milk, urine, and hair. Target compounds are shown in Table 1.
3. Environmental measurements
In the same sub-cohort as the one described above, indoor air pollutants, including volatile organic compounds (VOCs), aldehydes, nitrogen oxides, and fine particulate matters (PM2.5), will be measured during home visits. Noise levels and other physical parameters such as temperature and humidity will also be assessed.
4. Atmospheric simulation from ambient air quality monitoring
There are about 1,500 ambient air quality monitoring stations and about 500 roadside air quality monitoring stations across Japan, where levels of the five classical air pollutants, i.e., carbon monoxide (CO), suspended particulate matter (SPM), sulfur dioxide (SO2), nitrogen dioxide (NO2), and photochemical oxidants are monitored continuously. Twenty other hazardous air pollutants are also monitored at over 300 sites. Exposure to classical and hazardous air pollutants will be estimated from the monitoring station data using atmospheric simulation models.
Kawamoto T., Nitta H., Murata K., Toda E., Tsukamoto N., Hasegawa M., Yamagata Z., Kayama F., Kishi R., Ohya Y., Saito H., Sago H., Okuyama M., Ogata T., Yokoya S., Koresawa Y., Shibata Y., Nakayama S., Michikawa T., Takeuchi A, & Satoh H. (2014). Rationale and study design of the Japan environment and children’s study (JECS). BMC Public Health, 14, 25.
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Publication 2014
Air Pollutants Aldehydes Antineoplastic Agents BLOOD Environmental Exposure Fever Hair Hair Dyes Humidity Kerosene Metals, Heavy Milk, Human Monoxide, Carbon Narcotics Nitrogen Dioxide Nitrogen Oxides Oxidants, Photochemical Pesticides Physical Examination Solvents Umbilical Cord Blood Urine Vibration Visit, Home Volatile Organic Compounds

Most recents protocols related to «Nitrogen Dioxide»

1
COVID-19 Impacts on Air Quality and Meteorology
Meteorological data such as net short wave radiation flux, temperature, relative humidity, wind speed, and pressure were gathered from the Global Land Data Assimilation System (GLDAS). The GLDAS meteorological data is hosted in Google Earth Engine (GEE) platform (Rodell et al., 2004 (link)). The climatological data were downloaded using Javascript language from the gridded images for the study of the Western Anatolia and Western Black Sea regions.
The data on air quality parameters were acquired from the Ministry of Environment and Urbanization (Ministry of Environment and Urbanization, 2021 ). Air quality parameters such as particulate matter (PM10) having an aerodynamic diameter of less than or equal to 10 m (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), nitrogen oxides (NOx), and ground-level ozone pollution (O3). The data on confirmed cases and new hospitalizations on COVID-19 were obtained from the COVID-19 information page of the Republic of Turkey Ministry of Health on December 12, 2020 (https://covid19.saglik.gov.tr/). The daily data were collected from June 29, 2020, to November 23, 2020, for the meteorological data and air quality parameters which are equal to the available data on the number of COVID-19 cases
Ulutaş K., Abujayyab S.K., Abu Amr S.S., Alkarkhi A.F, & Duman S. (2023). The effect of air quality parameters on new COVID-19 cases between two different climatic and geographical regions in Turkey. Theoretical and Applied Climatology, 152(1-2), 801-812.
Publication 2023
COVID 19 Ground Level Ozone Hospitalization Humidity Monoxide, Carbon Nitrogen Dioxide Nitrogen Oxides Pressure Radiation Short Waves Urbanization Wind
2
Fluorite-Structured Nd2-2xLa2xCe2O7 Synthesis
Fluorite structure can be synthesized using various chemical routes, for instance, the hydrothermal method, solid-state method, and sol–gel auto-combustion method. However, here we used sol–gel auto-combustion approach to synthesize a series of Nd2−2xLa2xCe2O7 with (x = 0.0, 0.2, 0.4, 0.6, 0.8, and 1.0) because it is simple to execute, inexpensive, and ensures crystalline phase in a quick time. To proceed, La(NO3)3·6H2O [purity > 99%], Nd(NO3)3·6H2O [purity > 99%], and Ce(NO3)3·6H2O [purity > 99%] were utilized as precursors along with fuel agents such as urea (CH4N2O) and glycine (C2H5NO2). All the chemicals were purchased from Sigma Aldrich. The metal nitrates to fuel agent's ratio was maintained as 1 : 2. The stoichiometric amounts of all the precursors were weighed using a precise digital balance and dissolved separately into deionized water. The individual transparent solutions were combined into a beaker. The beaker was then placed on the hot plate with a magnetic stirrer inside it. The hotplate temperature was set at 95 °C, and stirred magnetically at 320 rpm. The solution thickened over time as a result of the continuous elimination of fumes. The solution was kept on the hot plate till stirring became difficult. Then, the stirring was stopped, magnetic stirrer was taken out, and in a few moments, frothing started that converted viscous liquid into gel. To eliminate the nitrogenous gases from the gel and to trigger the auto-combustion process, the hot plate's temperature was gradually increased up to 310 °C.23 (link) At this temperature urea and glycine catch fire and causes auto-combustion. This combustion yields the CO2, NO2, and water vapors according to the following balanced chemical equations:
The hitting of this temperature gave birth to the flame inside the beaker, which instantly burnt all the gel and converted it into ash. As a result of this combustion, the temperature inside the beaker promptly increased which lead to the following reaction for parent composition to occur:
The molecular oxygen (O2) and nitrogen dioxide (NO2) were evolved as a byproduct in this reaction. For subsequent samples, the stoichiometric amount of La(NO3)3·6H2O was substituted at Nd(NO3)3·6H2O site. After that, the ash was put into an Agate mortar and pestle for grinding and converted into fine powder. The synthesized powder was then placed into ceramic cups and calcined at 800 °C for 3 h in a Nabertherm furnace to develop a pure phase.24 (link) This calcined powder was pressed using an Apex hydraulic press to make cylindrical pellets of 7 mm diameter and ∼1 mm thickness by applying a force of 30 kN. All the pellets were then sintered at 350 °C for 1 h to make them hard.25 (link) The pictorial representation of this whole synthesis process is shown in Fig. 1.
An advanced Bruker D8 X-ray diffractometer (XRD) was used to analyze the crystalline phase of the synthesized series. A Nova NanoSEM-450 field emission scanning electron microscope (FESEM) was utilized to investigate the morphology and elemental composition. A Radiant's Technologies Inc., USA precision multiferroic tester was used to probe ferroelectric properties. Magnetic properties of synthesized series have been carried out by Cryogenic vibrating samples magnetometer (VSM).
Quader A., Mustafa G.M., Ramay S.M, & Atiq S. (2023). Gateway toward efficient and miniaturized A2B2O7-type fluorite structure-based energy storage devices. RSC Advances, 13(11), 7453-7463.
Publication 2023
Anabolism Burns Childbirth Fingers Gases Glycine Hot Temperature Metals Nitrates Nitrogen Nitrogen Dioxide Parent Pellets, Drug Powder Precipitating Factors Radiography Scanning Electron Microscopy Urea Viscosity Water Vapor
3
Long-term Air Pollution Exposure Assessment
Long-term exposure to PM2.5, particulate matter with diameter ≤10 μm (PM10), black carbon (BC), nitrogen dioxide (NO2) and nitrogen oxides (NOx) at the individual address level was estimated using a Gaussian air quality dispersion model and a wind model, both part of the Airviro air quality management system (https://www.airviro.com/airviro/). The Gaussian model calculates the horizontal distribution of air pollution concentrations 2 m above ground level. In densely populated areas, the calculations represent concentrations 2 m above roof level. The calculations use a variable grid size, between 35 × 35 m and 500 × 500 m, with the smallest grid size in the urban areas. In addition, a street canyon contribution was calculated for addresses located on busy inner-city streets flanked by contiguous high buildings using the Airviro street canyon model (until the year 2012; https://www.airviro.com/airviro/modules/) and the Operational Street Pollution Model, OSPM (from 2013 onwards; www.au.dk/OSPM). Meteorological data (climatological wind and temperature profiles) for the wind model were taken from a 50-m mast in southern Stockholm. As input to the dispersion modelling, emission inventories for the years 1990, 1995, 2000, 2011, 2015 and 2020 were used. For years in between, linear interpolation was used. The emission inventories include local emissions from road traffic (exhaust and non-exhaust), residential wood combustion, energy production, industrial processes, and other sources (eg, off-road machinery and agriculture) in Stockholm and Uppsala counties, described in detail elsewhere.38 In addition, annual average long-range contributions based on continuous measurements at regional background station were added to the locally modelled concentrations. More details of the dispersion modelling are provided in the eMethods of the Supplement.
Four pre-pandemic exposure time-windows were calculated: the 2019 annual average (i.e., immediately preceding the pandemic), the time-weighted average from the 16-year follow-up to the 24-year follow-up (calendar years covering 2010–2019), the time-weighted average from the 1-year to the 16-year follow-up (calendar years covering 1994–2013) and during the first year of life. The exposure estimation took into consideration time spent in different locations (home, day-care and school) up to 16 years of age as well as residential history during the time window of interest. NO2 was not used in the association analysis due to the high correlation with NOx, e.g., r = 0.99 in annual exposure 2019.
Yu Z., Ekström S., Bellander T., Ljungman P., Pershagen G., Eneroth K., Kull I., Bergström A., Georgelis A., Stafoggia M., Gruzieva O, & Melén E. (2023). Ambient air pollution exposure linked to long COVID among young adults: a nested survey in a population-based cohort in Sweden. The Lancet Regional Health - Europe, 28, 100608.
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Publication 2023
Air Pollution Carbon Black Day Care, Medical Dietary Supplements Nitrogen Dioxide Nitrogen Oxides Pandemics Personality Inventories Wind
4
Air Pollution and Hypertension Hospitalizations
The air pollutant concentration data of Ganzhou City from January 1, 2015 to December 31, 2020 were obtained on the China Urban Air Quality Real-time Release Platform. Calculate and sort out the 24-h average concentrations of five air pollutants such as PM2.5, PM10, carbon monoxide (CO), Nitrogen dioxide (NO2), and sulfur dioxide (SO2) and the daily maximum 8-h average ozone (O3) concentration. Air pollution exposure concentrations were matched according to the patients' hospitalization dates to generate a total of 15 air pollution concentration data series including L0, L0-6, L0-13, L0-29, L0-59, L0-89, L0-119, L0-149, L0-179, L0-209, L0-239, L0-269, L0-299, L0-329, and L0-359. Where L0 is equivalent to the same day exposure concentration of the respective air pollutant and L0-6 are equivalent to the moving average exposure concentrations at a lag of 6 days between hospital admissions for patients with hypertension. Meteorological data comes from the National Climate Data Center, which collects indicators such as the daily average temperature (°C) and relative humidity (%) in Ganzhou from January 1, 2016 to December 31, 2020. The locations of air pollutant data monitoring sites and hospital admissions (two campuses) are shown in Figure 1.
Gao Y., Li C., Huang L., Huang K., Guo M., Zhou X, & Zhang X. (2023). Effects of ambient particulate exposure on blood lipid levels in hypertension inpatients. Frontiers in Public Health, 11, 1106852.
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Publication 2023
Air Pollutants Air Pollution Climate High Blood Pressures Hospitalization Humidity Monoxide, Carbon Nitrogen Dioxide Ozone Patient Admission Patients
5
Taichung Air Pollution Monitoring
The Environmental Protection Administration established five air pollution monitoring stations in Taichung, Taiwan. Concentrations of air pollutants, ambient temperature and relative humidity were measured continuously around the clock and reported hourly. Data on the mean daily levels of air pollutants, ambient temperature and relative humidity were supported and the data between 2007 and 2011 were gathered for the study. The following seven air pollutants were assessed: nitrogen dioxide (SO2), carbon monoxide (CO), particles ≤ 10 μm in diameter (PM10), particles ≤ 2.5 μm in diameter (PM2.5), nitric oxide (NO), nitric dioxide (NO2), and non-methane hydrocarbon (NMHC).
Li R.L., Wu C.T., Chen S.M., Lue K.H., Lee S.S., Tsao C.Y, & Ku M.S. (2023). Allergic rhinitis children with obesity are more vulnerable to air pollution: a cross sectional study. Scientific Reports, 13, 3658.
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Publication 2023
Air Pollutants Air Pollution Humidity Hydrocarbons Methane Monoxide, Carbon Nitrogen Dioxide Oxide, Nitric

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More about "Nitrogen Dioxide"

Nitrogen dioxide (NO2) is a highly reactive and poisonous gas that plays a crucial role in atmospheric chemistry and environmental studies.
It is a byproduct of the combustion of fossil fuels and a key contributor to air pollution.
PubCompare.ai's innovative platform helps researchers optimize their nitrogen dioxide research by locating the best protocols from literature, pre-prints, and patents.
With AI-driven comparisons, the tool enhances reproducibility and accuracy, empowering researchers to make informed decisions and take their nitrogen dioxide studies to new heights.
Nitrogen dioxide is an important environmental pollutant that can have significant impacts on human health and the ecosystem.
It is a reddish-brown gas with a pungent odor and is formed during the high-temperature combustion of fossil fuels, such as in power plants, motor vehicles, and industrial processes.
Exposure to nitrogen dioxide can cause respiratory problems, especially in individuals with pre-existing conditions like asthma.
PubCompare.ai's platform is designed to assist researchers in their nitrogen dioxide studies by providing access to a comprehensive database of protocols and methodologies.
The tool utilizes advanced AI algorithms to compare and analyze various experimental approaches, enabling researchers to identify the most effective and reproducible techniques.
This can be particularly useful when working with cell lines like RAW264.7 (mouse macrophage), HepG2 (human liver), or MCF-7 (human breast cancer), as well as when using specialized equipment like Modular incubator chambers, HOBO 8 Pro Series monitors, or Teflon filters.
Additionally, the platform can help researchers navigate the complex landscape of nitrogen dioxide research, including the use of various reagents and media, such as Mycoplasma, Albumax, MP0035, and RPMI 1640.
By providing access to the latest research and fostering collaboration, PubCompare.ai empowers researchers to make informed decisions and drive innovation in the field of nitrogen dioxide studies.
Explore PubCompare.ai's cutting-edge platform and discover new insights into this important environmental pollutant.
Enhance the reproducibility and accuracy of your nitrogen dioxide research and take your studies to new heights.