Prenatal and Early Life Exposure to Ambient Air Pollutants Is Associated with the Fecal Metabolome in the First Two Years of Life.

Prenatal and early life air pollution exposure has been linked with several adverse health outcomes. However, the mechanisms underlying these relationships are not yet fully understood. Therefore, this study utilizes fecal metabolomics to determine if pre- and postnatal exposure to ambient air pollutants (i.e., PM10, PM2.5, and NO2) is associated with the fecal metabolome in the first 2 years of life in a Latino cohort from Southern California. The aims of this analysis were to estimate associations between (1) prenatal air pollution exposure with fecal metabolic features at 1-month of age, (2) prior month postnatal air pollution exposure with fecal metabolites from 1-month to 2 years of age, and (3) how postnatal air pollution exposure impacts the change over time of fecal metabolites in the first 2 years of life. Prenatal exposure to air pollutants was associated with several Level-1 metabolites, including those involved in vitamin B6 and tyrosine metabolism. Prior month air pollution exposure in the postnatal period was associated with Level-1 metabolites involved in histidine metabolism. Lastly, we found that pre- and postnatal ambient air pollution exposure was associated with changes in metabolic features involved in metabolic pathways including amino acid metabolism, histidine metabolism, and fatty acid metabolism.

Estimating global 0.1° scale gridded anthropogenic CO2 emissions using TROPOMI NO2 and a data-driven method.

Satellite remote sensing is a promising approach for monitoring global CO2 emissions. However, existing satellite-based CO2 observations are too coarse to meet the requirements of fine-scale global mapping. We propose a novel data-driven method to estimate global anthropogenic CO2 emissions at a 0.1° scale, which integrates emissions inventories and satellite data while bypassing the inadequate accuracy of CO2 observations. Due to the co-emitted anthropogenic emissions of nitrogen oxides (NOx = NO + NO2) and CO2, high-resolution NO2 measurements from the TROPOspheric Monitoring Instrument (TROPOMI) are employed to map the global anthropogenic emissions at a global 0.1° scale. We construct the driving features from NO2 data and also incorporate gridded CO2/NOx emission ratios and NOx/NO2 conversion ratios as driving data to describe co-emissions. Both ratios are predicted using a long short-term memory (LSTM) neural network (with an R2 of 0.984 for the CO2/NOx emission ratio and an R2 of 0.980 for the NOx/NO2 conversion ratio). The data-driven model for estimating anthropogenic CO2 emissions is implemented by random forest regression (RFR) and trained using the Emissions Database for Global Atmospheric Research (EDGAR). The satellite-based anthropogenic CO2 emission dataset at a global 0.1° scale agrees well with the national CO2 emission inventories (an R2 of 0.998 with Global Carbon Budget (GCB) and an R2 of 0.996 with EDGAR) and consistent with city-level emission estimates from Carbon Monitor Cities (CMC) with the R2 of 0.824. This data-driven method based on satellite-observed NO2 provides a new perspective for fine-resolution anthropogenic CO2 emissions estimation.

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.

Visible Light-Activated Room Temperature NO2 Gas Sensing Based on the In2O3@ZnO Heterostructure with a Hollow Microtube Structure.

The persistent challenge of poor recovery characteristics of NO2 sensors operated at room temperature remains significant. However, the development of In2O3-based gas sensing materials provides a promising approach to accelerate response and recovery for sub-ppm of NO2 detection at room temperature. Herein, we propose a simple two-step method to synthesize a one-dimensional (1D) In2O3@ZnO heterostructure material with hollow microtubes, by coupling metal-organic frameworks (MOFs) (MIL-68 (In)) and zinc ions. Meanwhile, the In2O3@ZnO composite-based gas sensor exhibits superior sensitivity performance to NO2 under visible light activation. The response value to 5 ppm of NO2 at room temperature is as high as 1800, which is 35 times higher than that of the pure In2O3-based sensor. Additionally, the gas sensor based on the In2O3@ZnO heterostructure demonstrates a significantly reduced response/recovery time of 30 s/67 s compared to the sensor based on pure In2O3 (74 s/235 s). The outstanding gas sensing properties of the In2O3@ZnO heterostructure-based sensors can be attributed to the enhanced photogenerated charge separation efficiency resulting from the heterostructure effect, and the improved receptor function toward NO2, which can increase the reactive sites and gas adsorption capacity. In summary, this work proposes a low-cost and efficient method to synthesize a 1D heterostructure material with microtube structures, which can serve as a fundamental technique for developing high-performance room-temperature gas sensors.

Residential exposure to ambient fine particulate matter (PM2.5) and nitrogen dioxide (NO2) and incident breast cancer among young women in Ontario, Canada.

BACKGROUND: Air pollution has been classified as a human carcinogen based largely on findings for respiratory cancers. Emerging, but limited, evidence suggests that it increases the risk of breast cancer, particularly among younger women. We characterized associations between residential exposure to ambient fine particulate matter (PM2.5) and nitrogen dioxide (NO2) and breast cancer. Analyses were performed using data collected in the Ontario Environmental Health Study (OEHS). METHODS: The OEHS, a population-based case-control study, identified incident cases of breast cancer in Ontario, Canada among women aged 18-45 between 2013 and 2015. A total of 465 pathologically confirmed primary breast cancer cases were identified from the Ontario Cancer Registry, while 242 population-based controls were recruited using random-digit dialing. Self-reported questionnaires were used to collect risk factor data and residential histories. Land-use regression and remote-sensing estimates of NO2 and PM2.5, respectively, were assigned to the residential addresses at interview, five years earlier, and at menarche. Logistic regression was used to estimate odds ratios (OR) and their 95 % confidence intervals (CI) in relation to an interquartile range (IQR) increase in air pollution, adjusting for possible confounders. RESULTS: PM2.5 and NO2 were positively correlated with each other (r = 0.57). An IQR increase of PM2.5 (1.9 µg/m3) and NO2 (6.6 ppb) at interview residence were associated with higher odds of breast cancer and the adjusted ORs and 95 % CIs were 1.37 (95 % CI = 0.98-1.91) and 2.33 (95 % CI = 1.53-3.53), respectively. An increased odds of breast cancer was observed with an IQR increase in NO2 at residence five years earlier (OR = 2.16, 95 % CI: 1.41-3.31), while no association was observed with PM2.5 (OR = 0.96, 95 % CI 0.64-1.42). CONCLUSIONS: Our findings support the hypothesis that exposure to ambient air pollution, especially those from traffic sources (i.e., NO2), increases the risk of breast cancer in young women.

Development of High-Precision NO2 Gas Sensor Based on Non-Dispersive Infrared Technology.

Increasing concerns about air quality due to fossil fuel combustion, especially nitrogen oxides (NOx) from marine and diesel engines, necessitate advanced monitoring systems due to the significant health and environmental impacts of nitrogen dioxide (NO2). In this study, a gas detection system based on the principle of the non-dispersive infrared (NDIR) technique is proposed. Firstly, the pyroelectric detector was developed by employing an ultra-thin LiTaO3 (LT) layer as the sensitive element, integrated with nanoscale carbon material prepared by wafer-level graphics technology as the infrared absorption layer. Then, the sensor was hermetically sealed using inert gas through energy storage welding technology, exhibiting a high detectivity (D*) value of 4.19 × 108 cm·âˆšHz/W. Subsequently, a NO2 gas sensor was engineered based on the NDIR principle employing a Micro Electro Mechanical System (MEMS) infrared (IR) emitter, featuring a light path chamber length of 1.5 m, along with integrated signal processing and software calibration algorithms. This gas sensor was capable of detecting NO2 concentrations within the range of 0-500 ppm. Initial tests indicated that the gas sensor exhibited a full-scale relative error of less than 0.46%, a limit of 2.8 ppm, a linearity of -1.09%, a repeatability of 0.47% at a concentration of 500 ppm, and a stability of 2% at a concentration of 500 ppm. The developed gas sensor demonstrated significant potential for application in areas such as industrial monitoring and analytical instrumentation.

Atomically thin-layered WS2based resistive sensors for detection of CO and NO2at room temperature.

The number of layers present in a two-dimensional (2D) nanomaterial plays a critical role in applications that involve surface interaction, for example, gas sensing. This paper reports the synthesis of 2D WS2nanoflakes using the facile liquid exfoliation technique. The nanoflakes were exfoliated using bath sonication (BS-WS2) and probe sonication (PS-WS2). The thickness of the BS-WS2was found to range between 70 and 200 nm, and that of PS-WS2varied from 0.6 to 80 nm, indicating the presence of single to few layers of WS2when characterized using atomic force microscope. All the WS2samples were thoroughly characterized using electron microscopes, x-ray diffractometer, Raman spectroscopy, UV-Visible spectroscopy, Fourier transform infrared spectroscope, and thermogravimetric analyser. Both the nanostructured samples were exposed to 2 ppm of NO2at room temperature. Interestingly, BS-WS2which comprises of a greater number of WS2layers exhibited -14.2% response as against -3.4% response of PS-WS2, the atomically thin sample. The BS-WS2sample was found to be highly selective towards NO2but was slower (with incomplete recovery) as compared to PS-WS2. The PS-WS2sample was observed to exhibit -11.9% to -27.4% response to 2-10 ppm of CO and -3.4%-35.2% response to 2-10 ppm of NO2at room temperature, thereby exhibiting the potential to detect two gases simultaneously. These gases could be accurately predicted and quantified if the response times of the PS-WS2sample were considered. The atomically thin WS2-based sensor exhibited a limit of detection of 131 and 81 ppb for CO and NO2, respectively.

Construction of Fully Integrated and Energy Self-Sufficient NO2 Gas Sensors Utilizing Zinc-Air Batteries.

Exploration of novel self-powered gas sensors free of external energy supply restrictions, such as light illumination and mechanical vibration, for flexible and wearable applications is in urgent need. Herein, this work constructs a flexible and self-powered NO2 gas sensor based on zinc-air batteries (ZABs) with the cathode of the ZABs also acting as the gas-sensitive layer. Furthermore, the SiO2 coating film, serving as a hydrophobic layer, increases the three-phase interfaces for the NO2 reduction reaction. The constructed sensors exhibit a high sensing response (0.3 V @ 5 ppm), an ultralow detection limit (61 ppb), a fast sensing process (129 and 103 s), and excellent selectivity. Moreover, the sensors also possess a wide working temperature range and a low working temperature tolerance (0.34 V at -15 °C). Simulations indicate that the hydrophobic surface at the cathode-hydrogel interface will accommodate more NO2 gas molecules at the reaction sites and prevent the influence of inner water evaporation and direct dissolution of NO2 in the electrolyte, which is beneficial to the enhanced gas sensing abilities. Finally, the self-powered sensing device is incorporated into a smart sensing system for practical applications. This work will pave a new insight into the construction of integrated and energy self-sufficient smart gas sensing systems.

Long-term effects of air quality on hospital readmission for heart failure in patients with acute myocardial infarction.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death worldwide, with air pollution posing significant risks to cardiovascular health. The effect of air quality on heart failure (HF) readmission in acute myocardial infarction (AMI) patients is unclear.The aim of this study was to evaluate the role of a single measure of air pollution exposure collected on the day of first hospitalization. METHODS: We retrospectively analyzed data from 12,857 acute coronary syndrome (ACS) patients (January 2015-March 2023). After multiple screenings, 4023 AMI patients were included. The air pollution data is updated by the automatic monitoring data of the national urban air quality monitoring stations in real time and synchronized to the China Environmental Monitoring Station. Cox proportional hazards regression assessed the impact of air quality indicators on admission and outcomes in 4013 AMI patients. A decision tree model identified the most susceptible groups. RESULTS: After adjusting for confounders, NO2 (HR 1.009, 95% CI 1.004-1.015, P = 0.00066) and PM10 (HR 1.006, 95% CI 1.002-1.011, P = 0.00751) increased the risk of HF readmission in ST-segment elevation myocardial infarction (STEMI) patients. No significant effect was observed in non-STEMI (NSTEMI) patients (P > 0.05). STEMI patients had a 2.8-fold higher risk of HF readmission with NO2 > 13 µg/m3 (HR 2.857, 95% CI 1.439-5.670, P = 0.00269) and a 1.65-fold higher risk with PM10 > 55 µg/m3 (HR 1.654, 95% CI 1.124-2.434, P = 0.01064). CONCLUSION: NO2 and PM10 are linked to increased HF readmission risk in STEMI patients, particularly when NO2 exceeds 13 µg/m3 and PM10 exceeds 55 µg/m3. Younger, less symptomatic male STEMI patients with fewer underlying conditions are more vulnerable to these pollutants.

Flexible Resistive Gas Sensor Based on Molybdenum Disulfide-Modified Polypyrrole for Trace NO2 Detection.

High sensitivity and selectivity and short response and recovery times are important for practical conductive polymer gas sensors. However, poor stability, poor selectivity, and long response times significantly limit the applicability of single-phase conducting polymers, such as polypyrrole (PPy). In this study, PPy/MoS2 composite films were prepared via chemical polymerization and mechanical blending, and flexible thin-film resistive NO2 sensors consisting of copper heating, fluorene polyester insulating, and PPy/MoS2 sensing layers with a silver fork finger electrode were fabricated on a flexible polyimide substrate using a flexible electronic printer. The PPy/MoS2 composite films were characterized using X-ray diffraction, Fourier-transform infrared spectroscopy, and field-emission scanning electron microscopy. A home-built gas sensing test platform was built to determine the resistance changes in the composite thin-film sensor with temperature and gas concentration. The PPy/MoS2 sensor exhibited better sensitivity, selectivity, and stability than a pure PPy sensor. Its response to 50 ppm NO2 was 38% at 150 °C, i.e., 26% higher than that of the pure PPy sensor, and its selectivity and stability were also higher. The greater sensitivity was attributed to p-n heterojunction formation after MoS2 doping and more gas adsorption sites. Thus, PPy/MoS2 composite film sensors have good application prospects.

Synergistic Etching and Hydrogen Bonding-Induced Self-Assembly of MXene/MOF Hybrid Aerogel for Flexible Room-Temperature Gas Sensing.

Limited by insufficient active sites and restricted mechanical strength, designing reliable and wearable gas sensors with high activity and ductility remains a challenge for detecting hazardous gases. In this work, a thermally induced and solvent-assisted oxyanion etching strategy was implemented for selective pore opening in a rigid microporous Cu-based metal-organic framework (referred to as CuM). A conductive CuM/MXene aerogel was then self-assembled through cooperative hydrogen bonding interactions between the carbonyl oxygen atom in PVP grafted on the surface of defect-rich Cu-BTC and the surface functional hydroxyl group on MXene. A flexible NO2 sensing performance using the CuM/MXene aerogel hybridized sodium alginate hydrogel is finally achieved, demonstrating extraordinary sensitivity (S = 52.47 toward 50 ppm of NO2), good selectivity, and rapid response/recovery time (0.9/4.5 s) at room temperature. Compared with commercial sensors, the relative error is less than 7.7%, thereby exhibiting significant potential for application in monitoring toxic and harmful gases. This work not only provides insights for guiding rational synthesis of ideal structure models from MOF composites but also inspires the development of high-performance flexible gas sensors for potential multiscenario applications.

Tomato pomace-derived nitrated fatty acids: Synthesis and antiplatelet activity.

This study investigates the antiplatelet properties of tomato pulp to combat cardiovascular diseases. Notably, it examines the formation of nitrated fatty acids (NO2-FA) in tomato pomace, renowned for its potential antiplatelet effects. Through diverse assays, including tandem mass spectrometry, microplate-based platelet aggregation, and flow cytometry, the research identifies NO2-OA, NO2-LA, and NO2-LnA as pivotal antiplatelet compounds. It demonstrates the concentration-dependent antiplatelet effects of nitrated tomato pomace against thrombin receptor activator peptide 6 (TRAP-6) and collagen-induced platelet activation, alongside the modulation of platelet activation markers. Additionally, synergistic effects were observed with nitrated tomato pomace extracts. The findings suggest therapeutic potential for NO2-FA derived from tomato pomace in preventing blood clot formation, with nitrated extracts exhibiting superior efficacy compared to non-nitrated ones. This research highlights the promising role of natural products, such as tomato pomace, in mitigating cardiovascular risks and proposes novel strategies for population health enhancement and cardiovascular disease management.

Atmospheric nitrogen dioxide suppresses the activity of phytochrome interacting factor 4 to suppress hypocotyl elongation.

MAIN CONCLUSION: Ambient concentrations of atmospheric nitrogen dioxide (NO2) inhibit the binding of PIF4 to promoter regions of auxin pathway genes to suppress hypocotyl elongation in Arabidopsis. Ambient concentrations (10-50 ppb) of atmospheric nitrogen dioxide (NO2) positively regulate plant growth to the extent that organ size and shoot biomass can nearly double in various species, including Arabidopsis thaliana (Arabidopsis). However, the precise molecular mechanism underlying NO2-mediated processes in plants, and the involvement of specific molecules in these processes, remain unknown. We measured hypocotyl elongation and the transcript levels of PIF4, encoding a bHLH transcription factor, and its target genes in wild-type (WT) and various pif mutants grown in the presence or absence of 50 ppb NO2. Chromatin immunoprecipitation assays were performed to quantify binding of PIF4 to the promoter regions of its target genes. NO2 suppressed hypocotyl elongation in WT plants, but not in the pifq or pif4 mutants. NO2 suppressed the expression of target genes of PIF4, but did not affect the transcript level of the PIF4 gene itself or the level of PIF4 protein. NO2 inhibited the binding of PIF4 to the promoter regions of two of its target genes, SAUR46 and SAUR67. In conclusion, NO2 inhibits the binding of PIF4 to the promoter regions of genes involved in the auxin pathway to suppress hypocotyl elongation in Arabidopsis. Consequently, PIF4 emerges as a pivotal participant in this regulatory process. This study has further clarified the intricate regulatory mechanisms governing plant responses to environmental pollutants, thereby advancing our understanding of how plants adapt to changing atmospheric conditions.

MAX-DOAS observations of ship emissions in the North Sea.

Shipping emissions were measured in Dunkirk, France. Elevated aerosol extinction coefficients (AEC), nitrogen dioxide (NO2) and sulphur dioxide (SO2) were observed up to 500 m from surface. Formaldehyde (HCHO) did not show an increase every time, which suggests that oxidation of emitted volatile organic compounds (VOCs) took longer than the transport to the observation path and dilution of direct emissions had occurred. Background NO2, HCHO, and SO2 levels were higher when the wind came over land or the surrounding industrial area, indicating that land-based sources contribute significantly; however, clear spikes in NO2 and SO2 were observed whenever ship plumes were sampled. Observations show that the ship emission contribution to pollution is significant, but land-based sources still dominate. The SO2/NO2 ratio was low throughout the campaign, although varying according to the ship type, confirming that the new fuel content regulations are being followed by most ships in this region.

Capabilities of satellite Geostationary Environment Monitoring Spectrometer (GEMS) NO2 data for hourly ambient NO2 exposure modeling.

The Geostationary Environment Monitoring Spectrometer (GEMS) is the world's first geostationary instrument that monitors hourly gaseous air pollutant levels, including nitrogen dioxide (NO2). Using the first-of-its-kind capabilities of GEMS NO2 data, we examined how well GEMS NO2 levels can explain the spatiotemporal variabilities in hourly NO2 concentrations in the Republic of Korea for the year 2022. A correlation analysis between hourly GEMS NO2 levels and ground NO2 concentrations showed a higher spatial correlation [Pearson r = 0.56 (SD = 0.20)] than a temporal one [Pearson r = 0.42 (SD = 0.14)], on average. To take advantage of the enhanced spatial predictability of GEMS NO2 data, we employed a mixed effects model to allow hour-specific relationships between GEMS NO2 and NO2 concentrations on a given day in each region and subsequently estimated hourly NO2 concentrations in all urban and rural areas. The 10-fold cross validation demonstrated R2 = 0.72, mean absolute error (MAE) = 3.7 ppb, and root mean squared error (RMSE) = 5.5 ppb. The hourly variations of the relationships were attributed particularly to those of wind speed among meteorological parameters considered in this study. The spatial distributions of hourly estimated NO2 concentrations were highly correlated between hours [average r = 0.91 (SD = 0.06)]. Nonetheless, they represented the diurnal patterns of urban versus rural NO2 contrasts during the day [urban/rural NO2 ratios from 1.22 (5 p.m.) to 1.37 (12 p.m.)]. The newly retrieved GEMS NO2 data enable temporally as well as spatially resolved NO2 exposure assessment. In combination with the time-activity patterns of individual subjects, the GEMS NO2 data can generate 'sub-population' exposure estimates and therefore enhance health effect studies.

Combination of toxicological and epidemiological approaches for estimating the health impact of atmospheric pollutants. A proof of concept for NO2.

BACKGROUND: Regular monitoring of the air pollutant nitrogen dioxide (NO2), an indicator for traffic-related emissions, is a priority in urban environments. The health impacts associated with NO2 exposure are the result of a combination of factors, including concentration, duration of exposure, and interactions with other pollutants. WHO has established air quality guidelines based on epidemiological studies. OBJECTIVE: This study develops a new concept "Health Impact Pathways (HIPs)" using adversity as a probabilistic indicator of health effects. For this purpose, it integrates available toxicological and epidemiological information, using Adverse Outcome Pathways (AOPs), in order to understand chemical-biological interactions and their consequences on health. METHODS: Literature review and meta-analysis of toxicological data supported by expert judgment were performed to establish: a) adversity pathways, b) quantitative criteria for scoring the observed toxicological effects (adversity indicators), c) NO2 exposure - adversity relationship for both long-term (1-36 months) and shortterm (1-7 days). The NO2 daily concentrations from January 2001 to December 2022, were obtained from Madrid city Air Quality network monitoring database. Adversity levels were compared with relative risk levels for all-cause and respiratory mortality estimated using linear equations from WHO 2021 guidelines. RESULTS: Non-linear relations were obtained for all long- and short-term NO2 related adversity indicators; for long-term effects, the best fitting was obtained with a modified Haber's law model with an exponential coefficient for the exposure time of 0.25. Estimations are presented for a set of case studies for Madrid city, covering temporal and spatial variability. A clear improvement trend along the two decades was observed, as well as high inter- and intra-station variability; the adversity indicators provided integrated information on the temporal and spatial evolution of population level risk. DISCUSSION: The proposed HIP conceptual approach offers promising advances for integrating experimental and epidemiological data. The next step is linking the concentration-adversity relationship with population health impacts through probability estimations, the preliminary estimations confirm the need for assessing independently different population groups.

A global comparative study on the impact of COVID-19 policy on atmospheric nitrogen dioxide (NO2): Evidence from remote sensing data in 2019-2022.

A significant body of research has documented the profound changes in global atmospheric conditions during the COVID-19 pandemic. However, there is still an inadequate comprehensive comparison and assessment of countries before, during, and after the pandemic. Variations in restriction policies, human behaviors, and national traits lead to significant differences in how restriction policies affect atmospheric pollution. This study focuses on NO2, a pollutant with high temporal sensitivity, and utilizes the Oxford COVID-19 policy stringency index along with demographic information. Through spatial-temporal mapping, we analyzed NO2 emission fluctuations and calculated the emission changes in each country. Drawing from this analysis, we explored the relationships among these factors and found that over the span of 2019-2022, across 193 countries, global NO2 emissions displayed a distinct trajectory: initially decreasing, subsequently rebounding, and eventually fluctuating. Most countries exhibited seasonal variations in NO2 emissions. Additionally, the study uncovered a correlation between the stringency of COVID-19 policies and the reduction in NO2 emissions: as policies became stricter, emissions significantly decreased in most countries. In contrast, in countries with lower population densities, stricter policies paradoxically led to an increase in emissions. These findings underscore the importance of considering demographic factors and geographical context in the formulation and implementation of environmental policies.

Exploring Pore Formation and Gas Sensing Kinetics Using Conjugated Polymer-Small Molecule Blends.

Controlling miscibility between mixture components helps induce spontaneous phase separation into distinct domain sizes, thereby resulting in porous conjugated polymer (CP) films with different pore sizes after selective removal of auxiliary components. The miscibility of the CP mixture can be tailored by blending auxiliary model components designed by reflecting the difference in solubility parameters with the CP. The pore size increases as the difference in solubility parameters between the matrix CP and auxiliary component increases. Electrical properties are not critically damaged even after forming pores in the CP; however, excessive pore formation enables pores to spread to the vicinity of the dielectric layer of CP-based field-effect transistors (FETs), leading to partial loss of the carrier-transporting active channel in the FET. The porous structure is advantageous for not only increasing detection sensitivity but also improving the detection speed when porous CP films are applied to FET-based gas sensors for NO2 detection. The quantitative analysis of the response-recovery trend of the FET sensor using the Langmuir isotherm suggests that the response speed can be improved by more than 2.5 times with a 50-fold increase in NO2 sensitivity compared with pristine CP, which has no pores.

Low ppm NO2 detection through advanced ultrasensitive copper oxide gas sensor.

The imperative development of a cutting-edge environmental gas sensor is essential to proficiently monitor and detect hazardous gases, ensuring comprehensive safety and awareness. Nanostructures developed from metal oxides are emerging as promising candidates for achieving superior performance in gas sensors. NO2 is one of the toxic gases that affects people as well as the environment so its detection is crucial. The present study investigates the gas sensing capability of copper oxide-based sensor for 5 ppm of NO2 gas at 100 °C. The sensing material was synthesized using a facile precipitation method and characterized by XRD, FE-SEM, UV-visible spectroscopy, photoluminescence spectroscopy, XPS and BET techniques. The developed material shows a response equal to 67.1% at optimal temperature towards 5 ppm NO2 gas. The sensor demonstrated an impressive detection limit of 300 ppb, along with a commendable percentage response of 5.2%. Under optimized conditions, the synthesized material demonstrated its high selectivity, as evidenced by the highest percentage response recorded for NO2 gas among NO2, NH3, CO, CO2 and H2S.

Does Exposure to Ambient Air Pollution Affect Gestational Age and Newborn Weight?-A Systematic Review.

Current evidence suggests that airborne pollutants have a detrimental effect on fetal growth through the emergence of small for gestational age (SGA) or term low birth weight (TLBW). The study's objective was to critically evaluate the available literature on the association between environmental pollution and the incidence of SGA or TLBW occurrence. A comprehensive literature search was conducted across Pubmed/MEDLINE, Web of Science, Cochrane Library, EMBASE, and Google Scholar using predefined inclusion and exclusion criteria. The methodology adhered to the PRISMA guidelines. The systematic review protocol was registered in PROSPERO with ID number: CRD42022329624. As a result, 69 selected papers described the influence of environmental pollutants on SGA and TLBW occurrence with an Odds Ratios (ORs) of 1.138 for particulate matter ≤ 10 µm (PM10), 1.338 for particulate matter ≤ 2.5 µm (PM2.5), 1.173 for ozone (O3), 1.287 for sulfur dioxide (SO2), and 1.226 for carbon monoxide (CO). All eight studies analyzed validated that exposure to volatile organic compounds (VOCs) is a risk factor for SGA or TLBW. Pregnant women in the high-risk group of SGA occurrence, i.e., those living in urban areas or close to sources of pollution, are at an increased risk of complications. Understanding the exact exposure time of pregnant women could help improve prenatal care and timely intervention for fetuses with SGA. Nevertheless, the pervasive air pollution underscored in our findings suggests a pressing need for adaptive measures in everyday life to mitigate worldwide environmental pollution.