Physics and chemistry of nitrogen dioxide (NO2) adsorption on gallium nitride (GaN) surface and its interaction with the yellow-luminescence-associated surface state.

Surface states have been a longstanding and sometimes underestimated problem in gallium nitride (GaN) based devices. The instability caused by surface-charge-trapping in GaN-based transistors is practically the same problem faced by the inventors of the silicon (Si) field effect transistors more than half a century ago. Although in Si this problem was eventually solved by oxygen and hydrogen-based passivation, in GaN, such breakthrough has yet to be made. Apparently, some of this surface charge originates in molecules adsorbed on its surface. Here, it is shown that the charge density associated with the GaN yellow band desorbs upon mild heat treatment in vacuum and re-adsorbs on exposure to the air. Selective exposure of GaN to nitrogen dioxide (NO2) reproduces this surface charge to its original distribution, as does exposure to air. Residual gas analysis of the gases desorbed during heat treatment shows a large concentration of nitric oxide (NO). These observations suggest that selective adsorption of NO2 is responsible for the surface charge that deleteriously affects the electrical properties of GaN. The physics and chemistry of this NO2 adsorption, reported here, may open a new path in the search for passivation to improve GaN device reliability.

Continuous measurement of the dynamics of residential indoor and outdoor NO2 and the contributions to human exposure.

In residential environment, NO2 is an important air pollutant. Yet, the dynamics of indoor NO2 and source contributions to human exposure are not well understood. Here, we conducted a continuous NO2 measurement in and out of eight households in Guangzhou, China. Paired high time-resolution NO2 data sets indoors (kitchen, living room) and outdoors (balcony) were obtained with NO2 monitors. We summarized the indoor and outdoor NO2 levels, identified temporal variation patterns, analyzed indoor-outdoor relationships, and quantified source contributions to indoor NO2 exposure. Indoor NO2 were overall higher than outdoor NO2, and in most cases, the highest NO2 levels were observed in the kitchen. NO2 in the kitchen was characterized by multiple spikes associated with use of gas stoves, while NO2 in the living room was also elevated but the peaks were generally smaller. The indoor-outdoor correlations were stronger in winter than in summer, and were stronger in nighttime than daytime. The sources contributing to indoor NO2 were separated with a conceptual model. Overall, the outdoor NO2 source contributed 73%-76% of the NO2 in the kitchen, and 76%-85% in the living room. The source pattern was quite different: outdoor NO2 sources were present indoors all the time; by contrast, indoor NO2 sources were present sporadically but with a very high contribution. This has important implication to the exposure assessment that indoor NO2 sources lead to short-term high exposure, and deserves attention regarding acute health effects.

Ozone response to precursors changes in the Chengdu-Chongqing economic circle, China, from satellite and ground-based observations.

Ozone (O3) pollution has become a noticeable problem in the Chengdu-Chongqing Economic Circle in China. The April-September MDA8 O3 level increases significantly by 2.26 µg m-3 year-1 from 2015 to 2023, with meteorological factors occupying merely 18 % in line with multivariate linear regression. To reveal the impact of anthropogenic emissions on O3 increase, O3 production sensitivity is accurately diagnosed by deriving localized thresholds for satellite formaldehyde (HCHO) to NO2 ratio and validated by in-situ measurements and observation-based model. Tracking volatile organic compounds (VOCs) and NOx through satellite HCHO and NO2, the O3 responses to precursor changes are assessed for long-term and special cases, and appropriate precursor reduction ratios are inferred. The results present that the transition range of satellite HCHO/NO2 from VOC-limited to NOx-limited in the region ranges from 2.7 to 4.3. The VOC-limited regime is concentrated in the urban areas of Chongqing and Chengdu as well as the central of the neighboring cities such as Deyang, Mianyang, and Meishan. The relative incremental reactivity from in-situ observations and box model at three sites in August 2019 demonstrates that O3 is most sensitive to anthropogenic VOC at urban and suburban sites, consistent with satellite results. Satellite and surface NO2 decrease at an annual rate of -2.1 % and - 2.9 % between 2015 and 2023, with larger decreases in Chengdu and Chongqing. In contrast, the trend of satellite HCHO is insignificant, indicating effective reduction in NOx but no significant reduction in VOC. This inappropriate reduction results in an increase in urban O3. The three short-term cases further validate the need for synergistic NOx and VOC reductions. Based on the relationship between O3 and satellite NO2 and HCHO, the minimum and optimal reduction ratios of VOC to NOx are 0.4:1 and 2.4:1 for the entire region, with higher ratios in Chengdu and Chongqing.

Effects of different substrate ratios on the enrichment of anammox bacteria at low substrate concentration.

Anammox bacteria (AnAOB) can be easily enriched under high temperatures and high substrate concentrations, while the application of the mainstream anammox process in low substrate municipal sewage is still relatively uncommon. Therefore, this study investigated the enrichment of AnAOB under conditions of low ammonia nitrogen and nitrite concentration at 25 °C. Results showed that using inoculated aerobic sludge, four ASBRs (R1, R2, R3 and R4) were successfully initiated with different influent substrate (NO2--N/NH4+-N) ratios of 1.2, 1.32, 1.4 and 1.5, respectively, with reactor start-up times were 162, 150, 120 and 134 days, respectively. The values of ΔNO2--N/ΔNH4+-N in reactors were stable at 1.17, 1.32, 1.43 and 1.53 respectively. The increase in influent substrate ratios resulted in improved TN removal rates and accelerated consumption of chemical oxygen demand (COD) during the initial start-up stage. The maximum TN removal rates achieved in the four reactors were 76.09%, 79.24%, 82.82% and 82.63%, respectively. The color of sludge gradually changes from yellowish-brown to reddish-brown. Furthermore, the surface of sludge exhibited a porous mineral structure, with crater-like cavities. The dominant anammox species in the system was identified as Candida Brocadia (3.04%). According to qPCR, the abundance of hzsB in the system is 1.65 × 1012 copies/g VSS, confirming the effective enrichment of AnAOB.

Long-term exposure to NO2 and PM2.5 and the occurrence of chronic kidney disease among patients with type 2 diabetes in Taiwan.

BACKGROUND: Individuals diagnosed with type 2 diabetes (T2D) frequently exhibit chronic kidney disease (CKD) which may be caused by environmental hazards such as exposure to air pollutants. However, limited research has explored the effects of prolonged exposure to air pollutants on CKD development in this population. This study examines the relationship between long-term exposure to air pollutants and CKD incidence in a longitudinal cohort of individuals with type 2 diabetes in Taiwan METHODS: Between 2003 and 2005, we recruited 1316 T2D patients (693 females [52.66 %]; mean age 56.16 ± 8.97 years). Patients were followed until December 31, 2012, with at least two clinical visits. Baseline demographics, medical history, and biomarker levels were collected. The development of CKD was determined by eGFR level < 60 mL/min/1.73 m2. Monthly averages of nitrogen dioxide (NO2) and fine particulate matter [PM ≤ 2.5 µm in aerodynamic diameter (PM2.5)] were acquired from 72 ambient air monitoring stations. The kriging method was employed to estimate the exposure levels to PM2.5, NO2, temperature, and relative humidity in the participants' residential areas. Cox regression with time-dependent covariates regression was applied to assess the impact of long-term exposure to air pollutants and CKD risk. RESULTS: Of 992 patients with normal renal function at baseline, 411 (41.43 %) experienced CKD occurrence over a median follow-up period of 5.45 years. The incidence of CKD was 93.96 cases per 1000 person-years. In multivariable adjusted models, patients exposed to PM2.5 levels above the third quartile of (>33.44 µg/m3) and NO2 levels above the fourth quartile (>22.55 ppb) were found to have an increased risk of CKD occurrence compared to lower exposure levels. CONCLUSIONS: This longitudinal study highlights the increased risk of CKD in individuals with type 2 diabetes due to prolonged exposure to NO2 and PM2.5, emphasizing the need for tailored air quality management strategies for this high-risk population.

Single ZnO Nanowire for Electrical and Optical NO2 Gas Sensing: Origin of Reversible and Irreversible Gas Effects Investigated by Photoluminescence Spectroscopy.

In this work, the gas sensing properties of a single ZnO nanowire (NW) are investigated, simultaneously in terms of photoluminescence (PL) and photocurrent (PC) response to NO2 gas, with the purpose of giving new insights on the gas sensing mechanism of a single 1D ZnO nanostructure. A single ZnO NW sensing device was fabricated, characterized, and compared with a sample made of bundles of ZnO NWs. UV near-band-edge PL emission spectroscopy was carried out at room temperature and by lowering the temperature down to 77 K, which allows detection of resolved PL peaks related to different excitonic transition regions. Surface effects were observed in PL maps, considering different nano and microstructures. Electrical and optical measurements were acquired at the same time during the NO2 gas exposure, allowing for the comparison of PL and PC response times and signal recovery. During NO2 gas desorption, irreversible behavior in the surface-related and donor-acceptor pair (DAP) regions is interpreted as the effect of an initial transient when electronic transfer from the gas molecules to the bulk occurs through the ZnO NW surface which acts as a channel. To the best of our knowledge, this is the first work which investigates the simultaneous PL optical and PC electrical response signals of a single ZnO NW to gas exposure.

Unraveling the Effect of Oxygen Vacancy on WO3 Surface for Efficient NO2 Detection at Low Temperature.

Oxygen vacancies (VO) in metal oxide semiconductors play an important role in improving gas-sensing performance of chemiresistive gas sensors. Nonetheless, there is still a lack of clear understanding of the inherent mechanism of the influence of oxygen vacancies on gas sensing due to generally focusing on the concentration of VO. Herein, oxygen vacancies were rationally modulated in WO3 nanoflower structures via an annealing process, resulting in a transformation of VO from neutral (VO0) to a doubly ionized (VO2+) state. Density functional theory (DFT) calculations indicate that VO2+ is significantly more efficient than VO0 for NO2 detection in competition with atmospheric O2. Benefiting from a high concentration of VO2+, the WO3-450 (WO3 annealed at 450 °C) sensor exhibits excellent sensing performance with an ultrahigh sensitivity (3674.1 to 5 ppm NO2), superior selectivity, and long-term stability (one month). Furthermore, the sensor with the wide range of concentration detection not only can detect NO2 gas with parts per million (ppm) but also can detect NO2 with parts per billion (ppb) level concentration, with a high sensibility reaching 2.8 to 25 ppb NO2 and over 100 to 100 ppb NO2. This study elucidates the oxygen vacancy mediated sensing mechanism toward NO2 and provides an effective strategy for the rational design of gas sensors with high sensing performance.

Assessment of tropospheric NO2 concentrations over greater Doha using Sentinel-5 TROPOspheric monitoring instrument (TROPOMI) satellite data: Temporal analysis, 2018-2023.

This study presents a temporal evaluation of the tropospheric NO2 column densities over Greater Doha using TROPOMI satellite data from May 2018 to December 2023, and an assessment of the impact of the preparations and hosting of the FIFA Football World Cup Qatar 2022, on NO2 levels before, during and after the tournament over Greater Doha. Analysis of annual NO2 levels from 2019 to 2023 showed an increase in 2022 compared to that of the previous three years and a clear decrease in 2023 post the completion of the world cup preparations and hosting. Results also showed an increase in NO2 levels during winter compared to that in summer, with wind speed being an important determining factor. Findings showed that Fridays and Saturdays (both constitute the local weekend in Qatar) were 44% and 13% lower than that of the averaged weekdays, respectively. The annual NO2 levels in the post-world cup year of 2023 were found to be 24% lower than that in 2022 and around 16% lower than that of the previous years. NO2 levels during the World Cup tournament (20 Nov to Dec 18, 2022) were found to be higher than that of the same corresponding periods in all other available years including an increase of 27% compared to that in 2023. Wind speed played an important role in determining the NO2 levels during the world cup period and accounted for >96% of their daily variability, indicating that meteorological factors substantially influenced the NO2 column during the event.

Biomass based nanofiber membrane composite with xylan derived carbon dots for fluorescence detection nitrite in food real samples.

In our latest research endeavor, we are proud to present an innovative approach to the synthesis of carbon dots (CDs) derived from the biomass xylan, which we have termed P-CDs. These P-CDs are meticulously integrated with a state-of-the-art biomass nanofiber membrane composed of polycaprolactone (PCL) and polylactic acid (PLA), resulting in the creation of a novel solid-state fluorescent sensor, designated as NFP-CDs. This cutting-edge sensor has been meticulously engineered for the highly sensitive and specific detection of nitrite ions (NO2-), a critical parameter in various fields. The NFP-CDs sensor stands out for its user-friendly design, cost-effective production, and portable nature, making it an ideal choice for rapid and visible nitrite ion detection. It exhibits an extraordinary response time of less than 1 s, which is a testament to its high sensitivity. Furthermore, the sensor demonstrates exceptional selectivity and specificity, with a remarkably low detection threshold of 0.36 µM. This is achieved through a sophisticated dual detection mechanism that synergistically combines colorimetric and spectral analyses, ensuring accurate and reliable results. In addition to its impressive technical specifications, the NFP-CDs sensor has been rigorously tested and validated for its efficacy in detecting nitrite ions in real-world samples. These samples include a diverse range of food products such as rock sugar, preserved mustard, kimchi, and canned fish. The sensor has demonstrated a remarkable recovery rate, which varies from 99 % to 106 %, highlighting its potential for practical application in nitrite ion detection. This research not only offers a robust and effective strategy for the detection of nitrite ions but also carries profound implications for enhancing food safety and bolstering environmental monitoring efforts. The development of the NFP-CDs sensor represents a significant step forward in the field of sensor technology, providing a powerful tool for the detection of nitrite ions and contributing to the broader goals of public health and environmental stewardship.

Prototype Alarm Integrating Pulse-Driven Nitrogen Dioxide Sensor Based on Holey Graphene Oxide/In2O3.

NO2 seriously threatens human health and the ecological environment. However, the fabrication of highly sensitive NO2 sensors with rapid response/recovery rates, low detection limits, and ease of integration remains a challenge. Herein, benefiting from the fast carrier transfer and rich active sites, holey graphene oxide (HGO) was adopted to functionalize the In2O3 nanosheet to construct NO2 gas sensors. Characterization and theoretical calculations established the merits of HGO decoration in the NO2 sensing. The optimal sample, 0.5 wt % HGO/In2O3-sheet, exhibited superior sensing properties, resulting in a 1.37-fold improvement in response to 1 ppm of NO2 compared to the GO/In2O3 counterpart. Gas-sensing kinetics analysis revealed its lower activation energy and higher kinetic rate constants. Importantly, pulsed-temperature modulation was employed to decouple the gas adsorption from surface activation processes, achieving an ultrahigh response of 2776 to 1 ppm of NO2 for the 0.5 wt % HGO/In2O3-sheet sensor. Compared to the isothermal mode, this strategy enhanced the response value by 1.6 times, reduced the response/recovery time by 33%/70%, and enabled the detection of NO2 concentrations as low as 1 ppb. Finally, an NO2 monitoring alarm system based on the 0.5 wt % HGO/In2O3-sheet sensor with pulsed-temperature modulation was demonstrated for hazard warnings.

Novel Electrolytic Regeneration Method for Cyclic Regeneration of Ozone Decomposition MnOx Catalysts.

The deactivation of ozone decomposition catalysts has been a bottleneck in their industrial application. As an efficient catalyst regeneration method, the liquid-phase method has attracted wide attention due to its operability and universality. However, the amount of waste liquid generated by the used regeneration liquid is a major drawback of its application. Therefore, we propose an electrolytic regeneration method for cyclic regeneration of MnOx ozone decomposition catalysts by combining the advantages of the electrolytic process. In this method, NaNO2 solution is used to react with O22- to efficiently regenerate the inactivated MnOx catalysts, while NO2- is oxidized to NO3-, and then the oxidized NO3- can be efficiently reduced to NO2- through the electrolysis process at the cathode with an 88% Faraday efficiency, ultimately realizing the recycling of the NO2-/NO3- regeneration solution. By this method, the regeneration of inactivated MnOx ozone catalysts can be realized only using electricity.

Greater exposure to PM2.5 and PM10 was associated with lower corneal nerve measures: the Maastricht study - a cross-sectional study.

BACKGROUND: Epidemiological and toxicological studies indicate that increased exposure to air pollutants can lead to neurodegenerative diseases. To further confirm this relationship, we evaluated the association between exposure to ambient air pollutants and corneal nerve measures as a surrogate for neurodegeneration, using corneal confocal microscopy. METHODS: We used population-based observational cross-sectional data from The Maastricht Study including N = 3635 participants (mean age 59.3 years, 51.6% were women, and 19.9% had type 2 diabetes) living in the Maastricht area. Using the Geoscience and hEalth Cohort COnsortium (GECCO) data we linked the yearly average exposure levels of ambient air pollutants at home address-level [particulate matter with diameters of ≤ 2.5 µm (PM2.5), and ≤ 10.0 µm (PM10), nitrogen dioxide (NO2), and elemental carbon (EC)]. We used linear regression analysis to study the associations between Z-score for ambient air pollutants concentrations (PM2.5, PM10, NO2, and EC) and Z-score for individual corneal nerve measures (corneal nerve bifurcation density, corneal nerve density, corneal nerve length, and fractal dimension). RESULTS: After adjustment for potential confounders (age, sex, level of education, glucose metabolism status, corneal confocal microscopy lag time, inclusion year of participants, smoking status, and alcohol consumption), higher Z-scores for PM2.5 and PM10 were associated with lower Z-scores for corneal nerve bifurcation density, nerve density, nerve length, and nerve fractal dimension [stß (95% CI): PM2.5 -0.10 (-0.14; -0.05), -0.04 (-0.09; 0.01), -0.11 (-0.16; -0.06), -0.20 (-0.24; -0.15); and PM10 -0.08 (-0.13; -0.03), -0.04 (-0.09; 0.01), -0.08 (-0.13; -0.04), -0.17 (-0.21; -0.12)], respectively. No associations were found between NO2 and EC and corneal nerve measures. CONCLUSIONS: Our population-based study demonstrated that exposure to higher levels of PM2.5 and PM10 are associated with higher levels of corneal neurodegeneration, estimated from lower corneal nerve measures. Our results suggest that air pollution may be a determinant for neurodegeneration assessed in the cornea and may impact the ocular surface health as well.

Challenging unverified assumptions in causal claims: Do gas stoves increase risk of pediatric asthma?

The use of unverified models for risk estimates and policy recommendations can be highly misleading, as their predictions may not reflect real-world health impacts. For example, a recent article states that NO2 from gas stoves "likely causes ∼50,000 cases of current pediatric asthma from long-term NO2 exposure alone" annually in the United States. This explicitly causal claim, which is contrary to several methodology and review articles published in this journal, among others, reflects both (a) An unverified modeling assumption that pediatric asthma burden is approximately proportional to NO2; and (b) An unverified causal assumption that the assumed proportionality between exposure and response is causal. The article is devoid of any causal analysis showing that these assumptions are likely to be true. It does not show that reducing NO2 exposure from gas stoves would reduce pediatric asthma risk. Its key references report no significant associations - let alone causation - between NO2 and pediatric asthma. Thus, the underlying data suggests that the number of pediatric asthma cases caused by gas stoves in the United States is indistinguishable from zero. This highlights the need to rigorously validate modeling assumptions and causal claims in public health risk assessments to ensure scientifically sound foundations for policy decisions.

Dark NO2 Reduction on a Graphene Surface with Implications for Soot Aging and HONO Formation.

Soot, primarily composed of elemental carbon (EC) and organic carbon (OC), is ubiquitous in PM2.5. In the atmosphere, the heterogeneous interaction between NO2 and soot is not only an important pathway driving soot aging but also of central importance to nitrous acid (HONO) formation. It is commonly believed that the surface redox reaction between reductive OC and NO2 dominates the night aging of soot and the conversion of NO2 to HONO. However, completely differing from the currently popular explanation, we find here that the redox reaction between EC and NO2 can also drive the conversion of NO2 to HONO during soot aging. By combining in situ experiments with density functional theory (DFT) calculations, we proposed that the surface carbon vacancy defects on graphite/graphene-like EC should be a type of potential primary adsorption and reactive sites inducing the heterogeneous reduction of NO2. We suggested a new mechanism that NO2 is reduced to form HONO on surface vacancy defects through the splitting of H2O molecules, and the carbon atoms adjacent to surface vacancy are simultaneously oxidized to form hydroxyl-functionalized EC. This novel finding provides insights into the chemical mechanism driving the NO2-to-HONO conversion and rapid soot aging, which expands our knowledge of the heterogeneous chemistry of soot in the atmosphere.

Ionic liquid-assisted synthesis of In2O3 nanoparticles for ppb-level NO2 sensing at low temperature.

Highly sensitive detection of nitric dioxide (NO2) has recently attracted much attention due to its harmful to the human health even at a low concentration of 0.1 parts per million (ppm). Herein, In2O3 nanoparticles (NPs) were prepared via a facile ionic liquid (IL) assisted solvothermal method with subsequent calcination and then were analyzed through the characterization of X-ray diffractometer (XRD), scanning electron microscope (SEM), transmission electron microscope (TEM), X-ray photoelectron spectroscopy (XPS) and nitrogen adsorption-desorption techniques. Morphological characterization demonstrated that the resultant compounds were In2O3 NPs with a diameter ranging from 20 to 30 nm. The gas sensor based on the In2O3 NPs prepared with IL exhibited excellent NO2-sensing properties in terms of fast response/recovery speed (26.6/10.0 s), high response (310.0), good repeatability and long-term stability to 10 ppm NO2 gas at low working temperature of 92 °C. The gas-sensing mechanism of In2O3 NPs to NO2 was represented to the surface adsorption control model and the possibilities relating to the improved NO2 sensing performance of the In2O3 NPs synthesized with IL-assisted were also discussed in detail.

Solution-processed NO2 gas sensor based on poly(3-hexylthiophene)-doped PbS quantum dots operable at room temperature.

The global industrial development and increase in the number of transportation vehicles, such as automobiles and ships, have led to a steady increase in the issues related to greenhouse gas emissions. NO2 is a greenhouse gas emitted in large quantities from automobiles and factories, and its emission is unavoidable in the modern world. Therefore, a sensor capable of precise detection of NO2 is required. The most commonly reported types of NO2 sensors are those based on metal oxides. However, their operation at room temperature is impossible owing to their high-temperature operating characteristics, and therefore, a heater must be designed inside or installed outside the sensor for heating. Meanwhile, NO2 sensors based on PbS quantum dots (QDs) are advantageous as they can operate at room temperature and can be easily manufactured through a solution process rather than a complicated semiconductor process. Herein, a NO2 sensor was fabricated by doping PbS QDs with poly(3-hexylthiophene) (P3HT). The as-developed sensor exhibited high responsivity to 100-0.4-ppm NO2 gas with a resolution of 200 ppb owing to the stability of the thin film and high hole mobility of P3HT.

W18O49 Nanofibers Functionalized with Graphene as a Selective Sensing of NO2 Gas at Room Temperature.

Recent trends in two-dimensional (2D) graphene have demonstrated significant potential for gas-sensing applications with significantly enhanced sensitivity even at room temperature. Herein, this study presents fabrication of distinctive gas sensor based on one-dimensional (1D) W18O49 nanofibers decorated 2D graphene, specifically coated on copper (Cu)-based interdigitated electrodes formed by DC sputtering, which can selectively detect NO2 gas at room temperature. The sensor device fabricated using W18O49/Gr1.5% (i.e., W18O49 nanofibers hybrid nanocomposite with 1.5 wt % graphene) displays excellent overall sensing performance at 27 °C (room temperature) with high response (∼150-160 times) to NO2 gas. The W18O49/Gr1.5%-based sensor device reflects the highly selective detection toward NO2 gas among various gases with quick response time of 3 s and speedy recovery in 6 s. The limit of detection of ∼0.3 ppm with excellent reproducibility and stability for 3 months in all weather conditions (tested in humidity conditions 20-97%) are superior features of the device under test. However, W18O49/Gr3% displayed higher selectivity for NO2 but resulted with comparatively reduced sensitivity than W18O49/Gr1.5% sensor. The enhanced sensing performance could be attributed to the graphene content to decorate the nanofibers on it, oxygen vacancies/defects, and the contacts between the sensing material and Cu. This favorable synthesis and properties of self-assembled hybrid composite materials provide a potential utilization for detecting NO2 gas in environmental safety inspection.

Enhanced Room-Temperature NO2 Sensing through Deep Functional Group Hybridization in Nitrogen-Doped Monolayer Ti3C2Tx.

Nitrogen dioxide (NO2) is a significant environmental and human health hazard. Current NO2 sensors often lack sensitivity and selectivity under ambient conditions. This study investigates ammonia pyrolysis modification of monolayer Ti3C2Tx MXene to enhance NO2 detection at room temperature. Nitrogen-doped Ti3C2Tx demonstrates a substantial improvement in sensitivity, with a response of 8.87% to 50 ppm of NO2 compared to 0.65% for the original sensor, representing a 13.8-fold increase. The nitrogen-doped sensor also exhibits superior selectivity and linearity for NO2 under ambient conditions. Theoretical analysis shows that nitrogen incorporation promotes enhanced interaction between Ti3C2Tx and its surface oxygen-containing functional groups through electronic hybridization, resulting in improved adsorption energy (1.80 |eV|) and electron transfer efficiency (0.67 |e|) for NO2, thereby enhancing its gas-sensing performance. This study highlights the potential of ammonia pyrolysis-treated Ti3C2Tx MXene for advancing NO2 sensor technologies with heightened performance at room temperature.

Exposure to Low-Level Air Pollution and Hyperglycemia Markers during Pregnancy: A Repeated Measure Analysis.

Epidemiologic evidence has emerged showing an association between exposure to air pollution and increased risks of gestational diabetes mellitus (GDM). This study examines the effect of low-level air pollution exposure on a subclinical biomarker of hyperglycemia (i.e., HbA1c) in pregnant people without diabetes before conception. We measured HbA1c in 577 samples repeatedly collected from 224 pregnant people in Rochester, NY, and estimated residential concentrations of PM2.5 and NO2 using high-resolution spatiotemporal models. We observed a U-shaped trajectory of HbA1c during pregnancy with average HbA1c levels of 5.13 (±0.52), 4.97 (±0.54), and 5.43 (±0.40)% in early-, mid-, and late pregnancy, respectively. After adjustment for the U-shaped trajectory and classic GDM risk factors, each interquartile range increase in 10 week NO2 concentration (8.0 ppb) was associated with 0.09% (95% CI: 0.02 to 0.16%) and 0.18% (95% CI: 0.08 to 0.28%) increases in HbA1c over the entire pregnancy and in late pregnancy, respectively. These associations remained robust among participants without GDM. Using separate distributed lag models, we identified a period between 8th and 14th gestational weeks as critical windows responsible for increased levels of HbA1c measured at 14th, 22nd, and 30th gestational weeks. Our results suggest that low-level air pollution contributes to hyperglycemia in medically low-risk pregnant people.

Do machine learning methods improve prediction of ambient air pollutants with high spatial contrast? A systematic review.

BACKGROUND & OBJECTIVE: The use of machine learning for air pollution modelling is rapidly increasing. We conducted a systematic review of studies comparing statistical and machine learning models predicting the spatiotemporal variation of ambient nitrogen dioxide (NO2), ultrafine particles (UFPs) and black carbon (BC) to determine whether and in which scenarios machine learning generates more accurate predictions. METHODS: Web of Science and Scopus were searched up to June 13, 2024. All records were screened by two independent reviewers. Differences in the coefficient of determination (R2) and Root Mean Square Error (RMSE) between best statistical and machine learning methods were compared across categories of methodological elements. RESULTS: A total of 38 studies with 46 model comparisons (30 for NO2, 8 for UFPs and 8 for BC) were included. Linear non-regularized methods and Random Forest were most frequently used. Machine learning outperformed statistical models in 34 comparisons. Mean differences (95% confidence intervals) in R2 and RMSE between best machine learning and statistical models were 0.12 (0.08, 0.17) and 20% (11%, 29%) respectively. Tree-based methods performed best in 12 of 17 multi-model comparisons. Nonlinear or regularization regression methods were used in only 12 comparisons and provided similar performance to machine learning methods. CONCLUSION: This systematic review suggests that machine learning methods, especially tree-based methods, may be superior to linear non-regularized methods for predicting ambient concentrations of NO2, UFPs and BC. Additional comparison studies using nonlinear, regularized and a wider array of machine learning methods are needed to confirm their relative performance. Future air pollution studies would also benefit from more explicit and standardized reporting of methodologies and results.