Carbon Monoxide Measurements Research Articles

Risk Assessment and Air Quality Study during Different Phases of COVID-19 Lockdown in an Urban Area of Klang Valley, Malaysia

Globally, the COVID-19 pandemic has had both positive and negative impacts on humans and the environment. In general, a positive impact can be seen on the environment, especially in regard to air quality. This positive impact on air quality around the world is a result of movement control orders (MCO) or lockdowns, which were carried out to reduce the cases of COVID-19 around the world. Nevertheless, data on the effects on air quality both during and post lockdown at local scales are still sparse. Here, we investigate changes in air quality during normal days, the MCOs (MCO 1, 2 and 3) and post MCOs, namely the Conditional Movement Control Order (CMCO) and the Recovery Movement Control Order (RMCO) in the Klang Valley region. In this study, we used the air sensor network AiRBOXSense that measures carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2) and particulate matter (PM2.5 and PM10) at Petaling Jaya South (PJS), Kelana Jaya (KJ) and Kota Damansara (KD). The results showed that the daily average concentrations of CO and NO2 mostly decreased in the order of normal days > MCO (MCO 1, 2 and 3) > CMCO > RMCO. PM10, PM2.5, SO2 and O3 showed a decrease from the MCO to RMCO. PJS showed that air pollutant concentrations decreased from normal days to the lockdown phases. This clearly shows the effects of ‘work from home’ orders at all places in the PJS city. The greatest percentage reductions in air pollutants were observed during the change from normal days to MCO 1 (24% to 64%), while during MCO 1 to MCO 2, the concentrations were slightly increased during the changes of the lockdown phase, except for SO2 and NO2 over PJS. In KJ, most of the air pollutants decreased from MCO 1 to MCO 3 except for CO. However, the percentage reduction and increments of the gas pollutants were not consistent during the different phases of lockdown, and this effect was due to the sensor location—only 20 m from the main highway (vehicle emissions). The patterns of air pollutant concentrations over the KD site were similar to the PJS site; however, the percentage reduction and increases of PM2.5, O3, SO2 and CO were not consistent. We believe that local burning was the main contribution to these unstable patterns during the lockdown period. The cause of these different changes in concentrations may be due to the relaxation phases during the lockdown at each station, where most of the common activities, such as commuting and industrial activities changed in frequency from the MCO, CMCO and RMCO. Wind direction also affected the concentrations, for example, during the CMCO and RMCO, most of the pollutants were blowing in from the Southeast region, which mostly consists of a city center and industrial areas. There was a weak correlation between air pollutants and the temperature and relative humidity at all stations. Health risk assessment analysis showed that non-carcinogenic risk health quotient (HQ) values for the pollutants at all stations were less than 1, suggesting unlikely non-carcinogenic effects, except for SO2 (HQ > 1) in KJ. The air quality information showed that reductions in air pollutants can be achieved if traffic and industry emissions are strictly controlled.

The effects of the COVID-19 lockdowns on the composition of the troposphere as seen by In-service Aircraft for a Global Observing System (IAGOS) at Frankfurt

Abstract. The European research infrastructure IAGOS (In-service Aircraft for a Global Observing System) equips commercial aircraft with a system for measuring atmospheric composition. A range of essential climate variables and air quality parameters are measured throughout the flight, from take-off to landing, giving high-resolution information in the vertical in the vicinity of international airports and in the upper troposphere–lower stratosphere during the cruise phase of the flight. Six airlines are currently involved in the programme, achieving a quasi-global coverage under normal circumstances. During the COVID-19 crisis, many airlines were forced to ground their fleets due to a fall in passenger numbers and imposed travel restrictions. Deutsche Lufthansa, a partner in IAGOS since 1994 was able to operate an IAGOS-equipped aircraft during the COVID-19 lockdown, providing regular measurements of ozone and carbon monoxide at Frankfurt Airport. The data form a snapshot of an unprecedented time in the 27-year time series. In May 2020, we see a 32 % increase in ozone near the surface with respect to a recent reference period, a magnitude similar to that of the 2003 heatwave. The anomaly in May is driven by an increase in ozone at nighttime which might be linked to the reduction in NO during the COVID-19 lockdowns. The anomaly diminishes with altitude becoming a slightly negative anomaly in the free troposphere. The ozone precursor carbon monoxide shows an 11 % reduction in MAM (March–April–May) near the surface. There is only a small reduction in CO in the free troposphere due to the impact of long-range transport on the CO from emissions in regions outside Europe. This is confirmed by data from the Infrared Atmospheric Sounding Interferometer (IASI) using retrievals performed by SOftware for a Fast Retrieval of IASI Data (SOFRID), which display a clear drop of CO at 800 hPa over Europe in March but otherwise show little change to the abundance of CO in the free troposphere.

Development of a system for measurement of carbon monoxide and smoke detection

Development of a system for measurement of carbon monoxide and smoke detection

Оценка качества воздуха (окись углерода) в мегаполисе Стамбул

Air pollution is one of the important environmental problems that affect people directly or indirectly socio-economically. The quality of the air we breathe affects our health, safety, comfort and sustainable life. One of the major air pollutants in city centers is carbon monoxide (CO) emission from vehicles. Inhalation of high concentrations is a health hazard. In this study CO measurement values between the hours of 2016 and 2020 were analyzed in terms of air quality in Istanbul, which is Turkey and Europe's largest in terms of population, while the 15 largest mega city in the world It was taken into consideration that the data of 19 different stations would be appropriate after the data was first passed through quality control in terms of method. Atmospheric CO varies in time and space scales depending on both the amount of emission and meteorological conditions. In order to see the change in time oscillation about city air pollution, the CO air quality data of the last 5 years, as well as human activities in some months of 2020, have changed within the framework of the Covid-19 pandemic measures, so the previous 2016- 2019 values were compared with the data of 2020. As a result of the analyzes obtained, it has been revealed that atmospheric CO values in Istanbul show significant variation in time and space scales.

Highly precise measurement of atmospheric N2O and CO using improved White cell and RF current perturbation

A highly precise dual gas sensor for measurement of atmospheric nitrous oxide (N2O) and carbon monoxide (CO) was developed and evaluated. A room temperature interband cascade laser emitting at 4.54 μm was used as a laser source to cover the absorption lines of N2O and CO simultaneously. Sensitivity and precision were enhanced by using an improved White cell with 76 m effective optical path length and radio frequency noise perturbation technique to reduce optical interference noise. A method was proposed to correct the laser frequency by calculating the correlation coefficient between the absorption signal with the reference signal, which effectively reduced the long-term drift of the absorption line center to less than 4 × 10−5 cm−1. By further precisely control the temperature and pressure of the absorption cell, a continuous 24 h measurement precision of 65 ppt N2O and 133 ppt CO at 0.1 Hz was demonstrated, with a daily drift less than 1.5 ppt. Finally, the repeatability and reliability of the sensor system were validated by real atmospheric measurements for two consecutive days.

UAS Chromatograph for Atmospheric Trace Species (UCATS) – a versatile instrument for trace gas measurements on airborne platforms

Abstract. UCATS (the UAS Chromatograph for Atmospheric Trace Species) was designed and built for observations of important atmospheric trace gases from unmanned aircraft systems (UAS) in the upper troposphere and lower stratosphere (UTLS). Initially it measured major chlorofluorocarbons (CFCs) and the stratospheric transport tracers nitrous oxide (N2O) and sulfur hexafluoride (SF6), using gas chromatography with electron capture detection. Compact commercial absorption spectrometers for ozone (O3) and water vapor (H2O) were added to enhance its capabilities on platforms with relatively small payloads. UCATS has since been reconfigured to measure methane (CH4), carbon monoxide (CO), and molecular hydrogen (H2) instead of CFCs and has undergone numerous upgrades to its subsystems. It has served as part of large payloads on stratospheric UAS missions to probe the tropical tropopause region and transport of air into the stratosphere; in piloted aircraft studies of greenhouse gases, transport, and chemistry in the troposphere; and in 2021 is scheduled to return to the study of stratospheric ozone and halogen compounds, one of its original goals. Each deployment brought different challenges, which were largely met or resolved. The design, capabilities, modifications, and some results from UCATS are shown and described here, including changes for future missions.

Specific risk factors profile and abstinence rate of female smokers at high cardiovascular risk from the nationwide smoking cessation services cohort CDT-net

Abstract Background In women, smoking is particularly harmful to the cardiovascular (CV) system, and smoking cessation (SC) is a key issue for CV prevention. Objectives From a large nationwide database on subjects who visited SC services between 2001 and 2018, we aimed to describe the profile and abstinence rate among female smokers at high CV risk. Methods Observational study from the French CS services cohort CDT-net. Inclusion criteria were age ≥18 years, and ≥1 CV risk factor (i.e. body mass index ≥25 kg/m2, hypercholesterolemia, diabetes, hypertension, history of stroke, myocardial infarction or angina pectoris. Abstinence (≥28 consecutive days) was self-reported, and confirmed by measurement of exhaled carbon monoxide <10 ppm. Results Among 37,949 smokers, 16,492 (43.5%) were women. Compared to men, women were 3-y younger (48 vs 51 y, p<0.001) and more educated (≥ Bachelor degree: 55 vs 45%, p<0.001). The burden of CV risk factors was high in women and men: hypercholesterolemia (30% vs 33% p<0.001), hypertension (23% vs 26%, p<0.001) and diabetes (10 vs 13%, p<0.001). Compared to men, women suffered more often from obesity (27 vs 20%, p<0.001), respiratory diseases (COPD: 24% vs 21%, p<0.001; asthma: 16 vs 9%, p<0.001) and anxio-depressive symptoms (37.5 vs 26.5%, p<0.001). Although women were less nicotine dependent than men, their abstinence rate was lower (52 vs 55%, p<0.001). Conclusion Female smokers who visited SC services not only presented very high CV risk profile, but also elevated rates of lung diseases and anxio-depressive symptoms. Our findings highlight the need to strengthen CV prevention strategies, through comprehensive gender-tailored SC interventions. Funding Acknowledgement Type of funding sources: Public Institution(s). Main funding source(s): IReSP and INCa through a call for doctoral grants launched in 2019

QCL-Based Open-Path, Single-Pass Measurement of Ambient Carbon Monoxide Using R 1f /ΔI₁ WMS

This letter outlines a new robust wavelength modulation spectroscopy technique to achieve calibration-free measurements. The technique normalizes the magnitude of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1^{st}$ </tex-math></inline-formula> harmonic signal by the amplitude of the laser’s linear intensity modulation, and uses the fact that the ratio of the intensity to the amplitude of the linear intensity modulation remains invariant at every point within a system and over time despite significant and unpredictable variations in the individual quantities. The technique is demonstrated using a mid-infrared quantum cascade laser for open-path measurements of ambient carbon monoxide with a single-pass detection limit of 12 ppb-m. The method is simple to implement and performs robustly for long durations of outdoor measurements.

Household air pollution and personal CO:PM2.5 relationships during cooking in the GRAPHS cohort: important covariates include wearing compliance

BACKGROUND AND AIM: Prior household air pollution studies have seen conflicting results using carbon monoxide (CO) measurements as predictors of personal PM₂.₅ exposures. We evaluated CO:PM₂.₅ relationships in the large Ghana Randomized Air Pollution and Health Study (GRAPHS). METHODS: 1,414 expecting mothers were enrolled into the study in rural communities in central Ghana. Participants tended to cook outdoors in dry weather and in semi-enclosed kitchens in wet weather. At baseline all cooking was done on traditional biomass and charcoal cookstoves. Personal exposure was assessed for seven 72-hour periods on each adult participant. CO was measured using Lascar EL-CO-USB devices. PM₂.₅ was also assessed during 2 of the 7 sessions in ~60% of the mothers using RTI MicroPEMs, which measured both real time and integrated PM, and included a motion sensor. We developed regression models to predict PM₂.₅ concentrations based on CO and other covariates. We built linear prediction models using a dataset of 2,118 validated exposure sessions of 24-hour, estimating average exposures in two ways: 1) during cooking hours (6-10 am and 4-8 pm); 2) for 24-hour periods. We conducted a forward stepwise variable selection process, successively adding covariates to the base model. RESULTS:The base model for the cooking period had an R² of 0.17, which was higher than the model based on 24-hour averages (R² =0.05). Adding four covariates, month, day, compliance and community, to both models moderately improved statistics (R² = 0.34 to 0.31). When we restricted data to sessions with higher wearing compliance (based on the motion sensor), predictive ability improved (R² = 0.54 - 0.51). CONCLUSIONS:In general we found limited ability to predict PM₂.₅ from CO and covariates in both 24-hour and 8-hour cooking periods. Poor wearing compliance can weaken associations between personal CO and PM₂.₅. KEYWORDS: Air pollution, Particulate matter, Modeling, Exposures

A Clinical Trial to Assess the Role of Repetitive Transcranial Magnetic Stimulation in Smoking Cessation in an Egyptian Sample

Objective: The objective of this study was to assess whether repetitive transcranial magnetic stimulation (rTMS) increases the likelihood of smoking cessation after 6 months of treatment Methods: A randomized, double-blind controlled clinical trial is conducted by enrolling 54 tobacco users divided into 2 equal groups; one group receiving active rTMS and the other group receiving a sham rTMS. Both groups were followed up for 24 weeks after treatment for abstinence using the Nicotine Use Inventory, cigarette consumption, cravings by Arabic Tobacco Craving Questionnaire-12. Results: Fifty-four subjects received the full intervention and were analyzed. Carbon monoxide was significantly less in the study group after the last treatment session. At week 24, the percentage of point prevalence abstinent subjects was 25.9% in the active group and 18.5% in the sham group, however, the difference was not statistically significant. Arabic Tobacco Craving Questionnaire-12 measures at different time points showed a statistically significant decrease in emotionality, expectancy, and purposefulness measures. However, this appears to be due to the effect of time, not treatment. Treatment response was higher in the study group, yet the difference was statistically insignificant. Conclusions: In a study that simulates real-life conditions in Egyptian smokers, 6 sessions of high-frequency active rTMS over the left dorsolateral prefrontal cortex did not produce a statistically significant increase in abstinence over sham rTMS at the same site. However, an effect on carbon monoxide measures and treatment response warrants further research.

Carbon monoxide exposures in wildland firefighters in the United States and targets for exposure reduction.

Background:Every year thousands of wildland firefighters (WFFs) work to suppress wildfires to protect public safety, health, and property. Although much effort has been put toward mitigating air pollutant exposures for the public and WFFs, the current burden in this worker population is unclear as are the most effective exposure reduction strategies.Objective:Quantify fireline carbon monoxide (CO) exposures in WFFs and identify predictors of exposures.Methods:We collected one-minute breathing zone CO measurements on 246 WFFs assigned to fires between 2015 and 2017. We used generalized estimating equations to evaluate predictors of CO exposure.Results:Approximately 5 percent of WFFs had fireline CO exposure means exceeding the National Wildfire Coordinating Group’s (NWCG) occupational exposure limit of 16 ppm. Relative to operational breaks, direct suppression-related job tasks were associated with 56% (95% CI: 47%, 65%) higher geometric mean CO concentrations, adjusted for incident type, crew type, and fire location. WFF perception of smoke exposure was a strong predictor of measured CO exposure.Significance:Specific job tasks related to direct suppression and WFF perceptions of smoke exposure are potential opportunities for targeted interventions aimed at minimizing exposure to smoke.

Hybrid liquid crystalline zinc phthalocyanine@Cu2O nanowires for NO2 sensor application

A novel organic-inorganic hybrid conductometric NO2 sensor has been introduced by depositing liquid-crystalline zinc oktakisalkylthiophthalocyanine [(C6S)8PcZn] on the surface of Cu2O nanowires. Cu2O nanowires were synthesized by electrochemical anodization of Cu films on glass substrates. Surface structures of bare Cu2O and (C6S)8PcZn@Cu2O nanowires hybrid structures were monitored by scanning electron microscope (SEM). UV–vis spectrophotometer measurements revealed the heterostructure formation by comparing the absorption profiles of bare Cu2O nanowires, (C6S)8PcZn thin film, and (C6S)8PcZn@Cu2O hybrid nanowires. The interdigitated transducers (IDT) were used for conductometric gas measurements. The sensing properties of all samples were investigated towards 500 ppb, 1 ppm, 2 ppm, and 5 ppm NO2 under dry airflow in 30 °C, 50 °C, 100 °C, and 150 °C. The measurements at 150 °C were repeated for (C6S)8PcZn film and hybrid sample using the same concentrations of NO2 gas under 38 % relative humidity airflow. In addition, selectivity of hybrid sensor was confirmed with carbon monoxide (CO), hydrogen (H2) and ethanol (C2H5OH) measurements. Our density functional theory calculations indicate that S atoms play a crucial role in improving the sensor response. The sensing properties and sensing mechanisms of samples were compared and discussed.

Improvement Initiative: End-Tidal Carbon Monoxide Measurement in Newborns Receiving Phototherapy

To determine, as part of our Utah Newborn Nursery Bilirubin Management Program, whether end-tidal carbon monoxide concentration (ETCOc) measurements in all newborns in our nursery receiving phototherapy were associated with outcomes related to the management of hyperbilirubinemia, including time (hours after birth) when phototherapy was initiated, total duration of phototherapy during the nursery stay, repeat phototherapy treatments, and hospital readmission for phototherapy. We performed a planned interim analysis of a component of our program in which we measured ETCOc noninvasively using CoSense on each newborn in our nursery receiving phototherapy and recorded specific outcomes related to phototherapy management. Of 1856 newborns admitted to our nursery in a 6-month period in 2020, 170 (9.8%) were treated with phototherapy. An ETCOc reading was successfully obtained in 145 of 151 attempts (96%). Higher ETCOc values were associated with earlier institution of phototherapy and longer duration of phototherapy. For every 1-ppm increase in ETCOc, phototherapy was started 9hours earlier (95% CI, 3.3-14.8; P=.002) and was administered for an additional 9.3hours (95% CI, 4.1-14.6; P<.001). Three newborns were readmitted to the hospital for intensive phototherapy; while in the nursery, all 3 had an elevated ETCOc (2.2, 2.6, and 2.9ppm). Our findings provide answers to questions raised in the 2004 American Academy of Pediatrics bilirubin guidelines. In our neonatal nursery, measuring ETCOc in all phototherapy recipients was feasible and safe, and the results were associated with multiple aspects of phototherapy management. Higher ETCOc values predicted earlier and longer phototherapy courses.

Application of Machine Learning in Pulmonary Function Assessment Where Are We Now and Where Are We Going?

Analysis of pulmonary function tests (PFTs) is an area where machine learning (ML) may benefit clinicians, researchers, and the patients. PFT measures spirometry, lung volumes, and carbon monoxide diffusion capacity of the lung (DLCO). The results are usually interpreted by the clinicians using discrete numeric data according to published guidelines. PFT interpretations by clinicians, however, are known to have inter-rater variability and the inaccuracy can impact patient care. This variability may be caused by unfamiliarity of the guidelines, lack of training, inadequate understanding of lung physiology, or simply mental lapses. A rules-based automated interpretation system can recapitulate expert’s pattern recognition capability and decrease errors. ML can also be used to analyze continuous data or the graphics, including the flow-volume loop, the DLCO and the nitrogen washout curves. These analyses can discover novel physiological biomarkers. In the era of wearables and telehealth, particularly with the COVID-19 pandemic restricting PFTs to be done in the clinical laboratories, ML can also be used to combine mobile spirometry results with an individual’s clinical profile to deliver precision medicine. There are, however, hurdles in the development and commercialization of the ML-assisted PFT interpretation programs, including the need for high quality representative data, the existence of different formats for data acquisition and sharing in PFT software by different vendors, and the need for collaboration amongst clinicians, biomedical engineers, and information technologists. Hurdles notwithstanding, the new developments would represent significant advances that could be the future of PFT, the oldest test still in use in clinical medicine.

Development of Real-time IoT based Air and Noise Monitoring System

Modernization has brought the world technological advancements, but it has also brought with it a slew of problems. In today's Malaysia, air and noise pollution are becoming more of a concern, along with a rise in occupational disease. A monitoring system is needed to address these issues. This paper describes the development of a real-time IoT-based air and noise pollution monitoring system that can provide monitoring and alert the user to the pollution levels. This monitoring system was built using IoT technology, which included the use of an ESP8266 Wi-Fi Module NodeMCU as a microcontroller to communicate with the chosen IoT analytics platform, ThingSpeak. A gas sensor MQ9 was used to measure carbon monoxide concentrations, and a sound sensor LM393 was used to measure noise levels in the surrounding area. The measured values were displayed on the Arduino software's serial monitor, then sent to the ThingSpeak server and graphically displayed in real time on a screen. The results of the electronic sensors were compared to the results of the stand-alone carbon monoxide meter and digital sound level meter for validation. The proposed monitoring system produced promising results, with 91.12 % and 97.86 % accuracy for gas and sound levels shown by the gas sensor MQ9 and sound sensor LM393, respectively. The framework also provides ThingSpeak server warning messages. When the calculated conditions exceeded the user's defined cap, the server sent the user an email update with the gas and noise limit status. This has made the system more useful and convenient.

A case study of a gravity wave induced by Amazon forest orography and low level jet generation

We investigated the role of turbulent coherent structures (CS), gravity waves (GW) and low-level jet (LLJ) propagation in the flow dynamics of the Nocturnal Boundary Layer (NBL) within and above a forest canopy at the Amazon Tall Tower Observatory (ATTO), in Central Amazon. Seven levels of wind velocity and temperature measurements allowed the study of the flow structure below and above the surface layer. We analyzed one dynamically rich night in 2015, which includes three distinct periods. In the first one, the NBL is characterized by CS generated at the canopy top. In the second period, the change in wind direction triggers the onset of a orographic GW above the roughness sublayer. The wave, suppressing the propagation of CS, strongly influences the boundary layer structure, both above and below the canopy. In the third period, low turbulence intensity at the canopy top enables the development of a LLJ. As the jet shear layer propagates upward, it disrupts the wave oscillations, while LLJ dominates the flow dynamics. The wavelet analyses identified i) turbulent and non-turbulent structures with different length and time-scales; ii) coupling of the flow at different levels and the vertical propagation of turbulent and wave motions; and iii) the ability of turbulent and low frequency processes associated with the orographic GW to penetrate within the canopy. Further, scalar measurements of methane, carbon monoxide and carbon dioxide identified the LLJ nose as upward limit for how far scalars can be transported.

2019–20 Australian Bushfires and Anomalies in Carbon Monoxide Surface and Column Measurements

In Australia, bushfires are a natural part of the country’s landscape and essential for the regeneration of plant species; however, the 2019–20 bushfires were unprecedented in their extent and intensity. This paper is focused on the 2019–20 Australian bushfires and the resulting surface and column atmospheric carbon monoxide (CO) anomalies around Wollongong. Column CO data from the ground-based Total Carbon Column Observing Network (TCCON) and Network for the Detection of Atmospheric Composition Change (NDACC) site in Wollongong are used together with surface in situ measurements. A systematic comparison was performed between the surface in situ and column measurements of CO to better understand whether column measurements can be used as an estimate of the surface concentrations. If so, satellite column measurements of CO could be used to estimate the exposure of humans to CO and other fire-related pollutants. We find that the enhancements in the column measurements are not always significantly evident in the corresponding surface measurements. Topographical features play a key role in determining the surface exposures from column abundance especially in a coastal city like Wollongong. The topography at Wollongong, combined with meteorological effects, potentially exacerbates differences in the column and surface. Hence, satellite column amounts are unlikely to provide an accurate reflection of exposure at the ground during major events like the 2019–2020 bushfires.

Internal consistency of the IAGOS ozone and carbon monoxide measurements for the last 25 years

Abstract. The In-service Aircraft for a Global Observing System (IAGOS) is a European research infrastructure that equips the Airbus A340/330 with a system for monitoring atmospheric composition. The IAGOS instruments have three different configurations: IAGOS-Core, IAGOS – Measurement of Ozone and Water Vapor by Airbus In Service Aircraft (IAGOS-MOZAIC) and IAGOS – Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument Container (IAGOS-CARIBIC). Since 1994, there have been a total of 17 aircraft equipped. In this study, we perform an intercomparison of about 8000 landing and takeoff profiles to compare the O3 and CO measurements performed from these different configurations. The collocated profiles used in the study met various selection criteria. The first was a maximal 1 h time difference between an ascent or descent by two different aircraft at the same airport and the second was a selection based on the similarity of air masses based on the meteorological data acquired by the aircraft. We provide here an evaluation of the internal consistency of the O3 and CO measurements since 1994. For both O3 and CO, we find no drift in the bias amongst the different instrument units (six O3 and six CO IAGOS-MOZAIC instruments, nine IAGOS-Core Package1 and the two instruments used in the IAGOS-CARIBIC aircraft). This result gives us confidence that the entire IAGOS database can be treated as one continuous program and is therefore appropriate for studies of long-term trends.

Cave Air Analysis with Gas Chromatography Mass Spectrometry

Gas chromatography (GC) is a frequently used analytical method for the determination of permanent and organic air components. The analysis usually needs two different columns in practice. The molecular sieve stationary phase can separate oxygen, nitrogen and carbon monoxide, but irreversibly adsorbs carbon dioxide and water. Porapak type columns are applicable for the measurement of carbon dioxide, however oxygen, argon, nitrogen and carbon monoxide are co-eluted. Usually these two types of columns are used in parallel for the determination. Carboxen stationary phase can separate carbon monoxide and carbon dioxide, but argon, oxygen and nitrogen are co-eluted. Thermal conductivity detector (TCD) and flame ionization detector (FID) are used commonly together for the determination of the separated components. TCD is applied for permanent gas analysis whereas FID – combined with a methanizer – is used for the detection of carbon monoxide, carbon dioxide and light hydrocarbons. Mass spectrometer (MS) is also a potential detector, because the properly chosen fragment ions can increase the selectivity.We developed a method for the determination of air components, using only one column and one detector. This method is suitable for the measurements by combining the advantages of the carboxen column with mass spectrometry. The validation parameters of the method were in the acceptable interval, so this method is able to determine the air components. The application of this technique to the analysis of cave air provided valuable information to the exploration of the Molnár János cave system.

When the earth stood still: air pollution during the Covid-19 quarantine – the case of São Paulo and Rio de Janeiro

In March 2020, the World Health Organization declared a global pandemic due to the new coronavirus (COVID-19). Several countries responded to this threat by introducing quarantine measures to reduce the transmission of COVID-19 in the community. These measures have drastically reduced human activities, causing an impact on urban air pollution due to the associated reduction in automobile use and other polluting activities. We investigated this effect with measurements of Particulate Material (PM10), Carbon Monoxide (CO), Nitrogen Dioxide (NO2) and Ozone (O3), carried out by the environmental departments of the cities of São Paulo and Rio de Janeiro, for two months in 2020. We compared them with data for the corresponding months in 2019, relating to the social isolation index, measured by the Mathematics and Statistic Institute of São Paulo (IME-USP). The results show a significant decrease in NO2 and CO and an increase in O3, and little change in Particulate Material.