Air Pollution Conditions Research Articles

Association of air pollution and weather conditions during infection course with COVID-19 case fatality rate in the United Kingdom

Although the relationship between the environmental factors, such as weather conditions and air pollution, and COVID-19 case fatality rate (CFR) has been found, the impacts of these factors to which infected cases are exposed at different infectious stages (e.g., virus exposure time, incubation period, and at or after symptom onset) are still unknown. Understanding this link can help reduce mortality rates. During the first wave of COVID-19 in the United Kingdom (UK), the CFR varied widely between and among the four countries of the UK, allowing such differential impacts to be assessed. We developed a generalized linear mixed-effect model combined with distributed lag nonlinear models to estimate the odds ratio of the weather factors (i.e., temperature, sunlight, relative humidity, and rainfall) and air pollution (i.e., ozone, N{O}_{2}, S{O}_{2}, CO, P{M}_{10} and P{M}_{2.5}) using data between March 26, 2020 and September 15, 2020 in the UK. After retrospectively time adjusted CFR was estimated using back-projection technique, the stepwise model selection method was used to choose the best model based on Akaike information criteria and the closeness between the predicted and observed values of CFR. The risk of death reached its maximum level when the low temperature (6 °C) occurred 1 day before (OR 1.59; 95% CI 1.52–1.63), prolonged sunlight duration (11–14 h) 3 days after (OR 1.24; 95% CI 1.18–1.30) and increased P{M}_{2.5} (19 μg/m3) 1 day after the onset of symptom (OR 1.12; 95% CI 1.09–1.16). After reopening, many COVID-19 cases will be identified after their symptoms appear. The findings highlight the importance of designing different preventive measures against severe illness or death considering the time before and after symptom onset.

Fresh air in the city: the impact of air pollution on the pricing of real estate.

This study investigates the impact of ambient air pollution on housing prices in Warsaw, Poland, by examining spatial dependencies. The high concentration of particulate matter (PM10, PM2.5 and PM1) is expected to reduce real estate values. Using a hedonic model with approximately 15,000 observations and a spatial error model, we did not find evidence of this impact. Standard and premium housing submarkets differ in price determinants, but both are insensitive to environmental issues. This could be explained by the lack of comprehensive intra-urban historical information on air pollution, which limits investors' rationality and their ability to properly value real estate based on environmental issues. Additionally, measurement and aggregation issues, along with low pollution variability within the city, may contribute to the insignificance of this information in real estate sales prices. Our empirical research confirms a strong link between air pollution and weather conditions within the city, where low temperatures and low-speed southern winds worsen contamination levels, while high temperatures and westerly winds improve air quality. Furthermore, we find that incorporating pollution data using PM yearly mean concentration works better in modelling than the PCA-reduced air pollution index.

Status of atmospheric air pollution in Ukraine prior to the full-scale russian invasion. Part 2: Pollutants total content according to the satellite data

The paper describes the main features of pollutant total content distribution over Ukraine that can be used as baseline air quality data observed before the full-scale russian invasion in Ukraine. The study is based on the data derived from the TROPOspheric Monitoring Instrument (TROPOMI) onboard of the Sentinel-5 Precursor (5P) satellite that indicates nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO) and formaldehyde (CH2O) levels. We defined the characteristics of pollutants spatial distribution with full coverage of Ukrainian territory. Despite the increasing role of automotive emissions, the most polluted air in Ukraine was still observed over large industrial cities and smaller settlements having the biggest thermal power plants (TPP). The high level of pollutants content over these locations negatively affects air quality in suburban and rural areas by the prevailing wind. They form relatively stable polluted spots over larger areas. Hence, main polluted areas include: Donetsk Region; territories in the central part of Ukraine along the Dnipro River and near the destroyed Kakhovka reservoir; Kharkiv and Zmiiv TPPs; Kyiv and Trypillia TPPs; and the territories in the western part, including Lviv, Dobrotvir and Burshtyn TPPs. The polluted air from these territories determines the air quality depending on a prevailing wind. In case of high wind speeds polluted air can be distributed from urban areas towards relatively clean territories such as Carpathian and Crimean Mountains, northern Polissia, and the Medobory National Park of Podillia. We determined quantitative parameters of wind speed and direction for every pollutant that causes higher total content over relatively clean territories. Pollutants dispersion in the atmosphere varies depending on a boundary layer height (BLH). It was found that NO2, CO and SO2 content significantly increased when the BLH was below 500 m over both urban areas and clean territories with no emission sources available. The inverse dependence on the BLH was identified for CH2O. This can be explained by a more intense photochemical production at higher altitudes. The detected baseline air pollution conditions can be used in order to assess the impact of the war on air quality in Ukraine and come up with relevant post-war development measures.

Developing and testing a PM2.5 low-cost sensor in Ethiopia under ambient and indoor air pollution conditions

PM2.5 low-cost sensors are a promising trend for low-income countries, where the PM2.5 associated burden of disease is high and few measurement instruments are available. Commercially available Sensor Systems (SSys) are relatively affordable and easy to use. They are, however, not designed for or evaluated in contexts characterized by much biomass burning, regular power interruptions and/or low internet coverage, typical for low-income countries. Alternatively, local teams can build a sensor system with PM2.5 sensors from Original Equipment Manufacturers (OEM). Existing African OEM projects depend on international partners and funding. This puts the affordability for local teams without funding into question. Furthermore, field comparisons of such sensors for ambient concentrations and indoor settings are rarely conducted in low-income contexts. In Arba Minch, Ethiopia, we developed a sensor system (SPSA) with the OEM Sensirion SPS30 and other components, together with an Arduino microprocessor, with LoRaWAN data transmission. We used the hardware and software in multiple configurations. The SPSA was used in 14 contexts typical for Ethiopia. During these tests we encountered problems that were easily solved by maintenance on location. On seven locations we collocated the SPSA with itself, gravimetric instruments and/or SSys. Amongst SPSA we found coefficients of determination (R2) of at least 0.98 for three ambient and one indoor location. The accuracy in comparison with the gravimetric method was 16% under ambient and 13% under indoor circumstances. This is lower than the internationally required 25%. The R2 in comparison to two SSys was 0.91-0.98 under ambient and 0.88-1.00 under indoor circumstances. The SPSA is a versatile sensor system that can be used in both ambient and indoor air pollution circumstances. Local development without international partners and funding resulted in local experience gaining, low costs, local ownership, and the possibility of tailoring the system to local needs regarding power and connectivity.

Modeling the Air Pollution and Aerosol‐PBL Interactions Over China Using a Variable‐Resolution Global Model

AbstractModeling air quality has always been a challenge in global models constrained by coarse grids. Here, the variable‐resolution Community Atmosphere Model with full chemistry based on the scalable spectral element (SE) dynamical core (MUSICAv0) is applied in simulating air pollution with a finer grid resolution of ∼0.25° over East Asia (SE_VR), in contrast to the same model with a uniform resolution of ∼1.0° (SE_UR). Two nudging experiments and four free‐running experiments are conducted to investigate the capabilities of SE_VR in modeling the air pollution and aerosol‐planetary boundary layer (PBL) interactions over China. Results show the regional refinement in SE_VR is essential for simulating haze events over complex terrain areas attributed to its better performance in representing the local vertical and horizontal dispersion conditions. SE_VR shows prominent advantages over SE_UR in simulating surface ozone because of better resolving spatial segregation of NOx and volatile organic compounds (VOC) chemical regimes and subsequently representing more detailed chemical processes related to ozone formation, although the model generally overestimates surface ozone over China. Further analysis of SE_VR shows the daytime radiative effect of black carbon (BC) aerosols lowers PBL height by 12.0% (17.9%), and leads to an increase of PM2.5 by 14.5% (10.8%) under the moderate (severe) air pollution conditions over Sichuan Basin. However, SE_UR has deficiencies in simulating BC‐PBL interactions due to its inability to reproduce the strong inverse temperature structure caused by BC aerosols in the lower atmosphere layer. Our results highlight the value of variable‐resolution global models for simulating air pollution and its interactions with climate.

Urban and suburban decadal variations in air pollution of Beijing and its meteorological drivers

Air pollution is a major threat to human health and ecosystems. Using 10-year (2013–2022) multi-source observations for the Beijing, China, we showed that clean-air actions have significantly reduced PM2.5, PM10, CO, NO2, and SO2 pollution, with an increase in the surface maximum daily 8-h average ozone (MDA8O3) concentrations during autumn and winter, leading to a rapid diminishment of the urban–suburban gap in air pollution. Secondary sources and vehicle emissions were enhanced in both urban and suburban areas in all seasons except summer from 2013 to 2022. By combining statistical analysis with the convergent cross-mapping model, the varying relationships between air pollution and meteorological conditions in the urban and suburban areas were delineated. The results suggested that boundary layer height and relative humidity exerted strong and stable influences on all air pollutants, except for MDA8O3, whose key meteorological driver was temperature. This study showed that increasing O3 trends in autumn and winter and aggravated O3 formation in summer in urban areas in Beijing became non-negligible from 2013 to 2022, despite the declining levels of air pollutants. Meteorological observations suggested that weather patterns in Beijing, characterized by higher temperatures, sunshine hours, and boundary layer height and lower relative humidity, have become more favorable for O3 formation in autumn and winter. Future mitigation efforts should focus on reducing VOC and NOx emissions to avoid further deterioration of O3 pollution under the frequent adverse meteorological conditions predicted under the background of global warming.

Metabolite Profiling of Conifer Needles: Tracing Pollution and Climate Effects.

In the face of escalating environmental challenges, understanding the intricate relationship between plant metabolites, pollution stress, and climatic conditions is of paramount importance. This study aimed to conduct a comprehensive analysis of metabolic variations generated through 1H and 13C NMR measurements in evergreen needles collected from different regions with varying pollution levels. Multivariate analyses were employed to identify specific metabolites responsive to pollution stress and climatic factors. Air pollution indicators were assessed through ANOVA and Pearson correlation analyses. Our results revealed significant metabolic changes attributed to geographical origin, establishing these conifer species as potential indicators for both air pollution and climatic conditions. High levels of air pollution correlated with increased glucose and decreased levels of formic acid and choline. Principal component analysis (PCA) unveiled a clear species separation, largely influenced by succinic acid and threonine. Discriminant analysis (DA) confirmed these findings, highlighting the positive correlation of glucose with pollution grade. Beyond pollution assessment, these metabolic variations could have ecological implications, impacting interactions and ecological functions. Our study underscores the dynamic interplay between conifer metabolism, environmental stressors, and ecological systems. These findings not only advance environmental monitoring practices but also pave the way for holistic research encompassing ecological and physiological dimensions, shedding light on the multifaceted roles of metabolites in conifer responses to environmental challenges.

Simulating the effect of urban sprawl on air quality and outdoor human thermal comfort in a cold city, Erzurum, Turkey.

Research on climate-sensitive urban planning is important to improve the quality of city life. Cold climate cities should respect climatic characteristics to diversify outdoor uses and increase air quality to maximize the benefits of winter. This study is aimed to explore the impact of changing urban pattern on air pollution and outdoor human thermal comfort conditions (HTCCs) in a newly developed urban area in Şükrüpaşa neighbourhood, Erzurum, among the coldest cities in Turkey, with high PM10 and low HTCCs levels. Sensitivity of urban development pattern to climate conditions and its suitability to eliminate the winter disturbances caused by HTCCs and air pollution were investigated by producing maps for HTCCs and air pollution using morphological, meteorological and spatial data and ENVI-met model in winter period of 2017 and 2022. It was found that newly developed areas increase the unfavourable conditions in terms of air quality, temperature and HTCCs due to the reasons like improper land uses, urban sprawl, high urban density and ventilation problems. In high-elevated cold cities, spatial planning and design principles should strictly be followed by incorporating climate knowledge and without revising the spatial decisions.

Prenatal air pollution, maternal immune activation, and autism spectrum disorder

BackgroundAutism Spectrum Disorder (ASD) risk is highly heritable, with potential additional non-genetic factors, such as prenatal exposure to ambient particulate matter with aerodynamic diameter < 2.5 µm (PM2.5) and maternal immune activation (MIA) conditions. Because these exposures may share common biological effect pathways, we hypothesized that synergistic associations of prenatal air pollution and MIA-related conditions would increase ASD risk in children. ObjectivesThis study examined interactions between MIA-related conditions and prenatal PM2.5 or major PM2.5 components on ASD risk. MethodsIn a population-based pregnancy cohort of children born between 2001 and 2014 in Southern California, 318,751 mother–child pairs were followed through electronic medical records (EMR); 4,559 children were diagnosed with ASD before age 5. Four broad categories of MIA-related conditions were classified, including infection, hypertension, maternal asthma, and autoimmune conditions. Average exposures to PM2.5 and four PM2.5 components, black carbon (BC), organic matter (OM), nitrate (NO3–), and sulfate (SO42-), were estimated at maternal residential addresses during pregnancy. We estimated the ASD risk associated with MIA-related conditions, air pollution, and their interactions, using Cox regression models to adjust for covariates. ResultsASD risk was associated with MIA-related conditions [infection (hazard ratio 1.11; 95% confidence interval 1.05–1.18), hypertension (1.30; 1.19–1.42), maternal asthma (1.22; 1.08–1.38), autoimmune disease (1.19; 1.09–1.30)], with higher pregnancy PM2.5 [1.07; 1.03–1.12 per interquartile (3.73 μg/m3) increase] and with all four PM2.5 components. However, there were no interactions of each category of MIA-related conditions with PM2.5 or its components on either multiplicative or additive scales. ConclusionsMIA-related conditions and pregnancy PM2.5 were independently associations with ASD risk. There were no statistically significant interactions of MIA conditions and prenatal PM2.5 exposure with ASD risk.

Short-term effects of air pollution and weather changes on the occurrence of acute aortic dissection in a cold region.

Air pollution and severe weather conditions can adversely affect cardiovascular disease emergencies. Nevertheless, it remains unclear whether air pollutants and low ambient temperature can trigger the occurrence of acute aortic dissection (AAD) in cold regions. We applied a retrospective analysis to assess the short-term effects of air pollution and ambient temperature on the occurrence of AAD in Harbin, China. A total of 564 AAD patients were enrolled from a major hospital in Harbin between January 1, 2017, and February 5, 2021. Weather condition data and air pollutant concentrations, including fine particulate matter smaller than 10 μm (PM10) and 2.5 μm in diameter (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3), were collected every day. Conditional logistic regressions and correlation analysis were applied to analyze the relationship of environmental and atmospheric parameters with AAD occurrence at lags of 0 to 7 days. Specifically, we appraised the air quality index, CO, NO2, SO2, O3, PM10, PM2.5, temperature, dew point temperature, atmospheric pressure, and cloud amount. A total of 1,496 days at risk were assessed, of which 564 patients developed AAD. Specifically, AAD did not occur on 1,043 (69.72%) days, while 1 or more cases occurred on 453 (30.28%) days. Several pollution and weather predictors for AAD were confirmed by multilevel modeling. The air quality index (p = 0.0012), cloud amount (p = 0.0001), and concentrations of PM2.5 (p = 0.0004), PM10 (p = 0.0013), NO2 (p = 0.0007) and O3 (p = 0.0001) predicted AAD as early as 7 days before the incident (lag of 7 days) in the study period. However, only concentrations of the air pollutants NO2 (p = 0.0468) and O3 (p = 0.011) predicted the occurrence of AAD after the COVID-19 outbreak. Similar predictive effects were observed for temperature, dew point temperature, and atmospheric pressure (all p < 0.05) on all days. The risk of AAD is closely related to air pollution and weather characteristics in Harbin. While causation was not determined, the impact of air pollutants on the risk of AAD was reduced after the COVID-19 outbreak.

Evaluation of the hourly ERA5 radiation product and its relationship with aerosols over China

Surface solar radiation (SSR) and its components are important parameters in studies of land, hydrology and the atmosphere. However, the SSR of ECMWF Reanalysis 5 (ERA5) rather than observations is often used in related research fields due to the sparse and uneven spatial distribution of observations. Therefore, understanding the deviation from observations and the attribution is essential for the appropriate use of reanalysis SSR. Based on station observations in China for 2014–2020, this study evaluates the ERA5 SSR products including global radiation (Rs), direct radiation (Rdir) and diffuse radiation (Rdif) under various PM2.5 concentrations to explore the influence of aerosols on ERA5 radiation. Overall, Rs from ERA5 has higher accuracy than Rdir and Rdif. The ERA5 product generally overestimates (underestimates) Rdir (Rdif), and this overestimate (underestimate) increases with the intensification of particle pollution. Under the influence of biomass burning (BB) events, the Rdir (Rdif) of ERA5 exhibits overestimation (underestimation) similar to that under the heaviest particle pollution. In terms of the time series, the deviations of Rdir and Rdif from ERA5 in 1999–2020 still vary with the local aerosol optical depth (AOD). The diurnal variation in Rdir (Rdif) from ERA5 also shows larger deviations under air pollution conditions than under clean conditions, especially at the hours around noon. Furthermore, the misrepresentation of aerosols also causes large deviations in the Rdif/Rdir of ERA5 from observations, especially at stations in eastern China. Similar changes in the deviation of ERA5 radiation from observations with increasing aerosol loading are found under both all sky and clear sky conditions. The high association with aerosol pollution found here indicates that ERA5 SSR products should be used with caution in the presence of atmospheric particle pollution.

Air Pollution and Meteorological Conditions Significantly Associated With Vernal Keratoconjunctivitis Exacerbations.

Vernal keratoconjunctivitis (VKC) is a severe chronic allergic inflammation of the ocular surface with episodes of acute exacerbations, that primarily affects children and young adults. Although the etiology and pathogenesis of VKC remain unclear, studies have suggested that environmental factors may be involved. This study aims to investigate the association between exposure to meteorological and environmental factors and the incidence of VKC exacerbations. This study was conducted in southern Israel, which is a semi-arid, hot, and dry climate with frequent dust storms. Patients diagnosed with VKC were recruited for the study. VKC exacerbations were identified as the need for medical intervention. Pollutants measured included nitrogen dioxide (NO2), ozone (O3), particulate matter (PM10 and PM2.5), sulfur dioxide (SO2), relative humidity (RH), temperature, and solar radiation (SR). To assess the association between VKC exacerbations and exposure to different pollutants, a case-crossover analysis was conducted. We also stratified the analysis by sex, age, ethnicity, immigration status, and social state score. Our results demonstrated that the pollutants NO2, O3, and PM10 were associated with VKC exacerbations with odds ratio (OR) = 2.17 (95% confidence interval [CI] =1.40 to 3.04), OR = 2.28 (95% CI = 1.30 to 3.39), and OR = 1.89 (95% CI = 1.06 to 2.74). Other pollutants PM2.5, temperature, and solar radiation were also independently associated with incidence of exacerbations with OR = 1.15 (95% CI = 0.87 to 1.50), OR = 1.75 (95% CI = 1.16 to 2.65), and OR = 1.37 (95% CI = 1.01 to 1.63) and had varying effects in different demographic strata. The environmental parameters, NO2, O3, PM10, PM2.5, temperature, and solar radiation were found to be significantly associated with VKC exacerbations, with NO2, O3, and PM10 showing the strongest associations. Our findings suggest that environmental factors should be considered when developing strategies to prevent and manage VKC exacerbations.

Impacts of air pollution and meteorological conditions on dry eye disease among residents in a northeastern Chinese metropolis: a six-year crossover study in a cold region

The purpose of this study is to explore the associations among dry eye disease (DED), air pollution, and meteorological conditions in the cold region of a northeastern Chinese metropolis (i.e., Changchun). Data on ambient air pollutants and meteorological parameters as well as diagnosed DED outpatients during 2015–2021 were collected. The associations between DED and environmental factors were analysed at multiple time scales using various statistical methods (i.e., correlation, regression and machine learning). Among the 10,809 DED patients (21,617 eyes) studied, 64.60% were female and 35.40% were male. A higher frequency of DED was observed in March and April, followed by January, August and October. Individual and multiple factor models showed the positive importance of particles with aerodynamic diameters <10 μm (PM10), carbon monoxide (CO), and ozone (O3) among normal air pollutants and air pressure (AP), air temperature (AT) and wind speed (WS) among normal meteorological parameters. Air pollutants (PM10, nitrogen dioxide: NO2) and meteorological parameters (AT, AP) have combined impacts on DED occurrence. For the first time, we further explored the associations of detailed components of atmospheric particles and DED, suggesting potential emission sources, including spring dust from bare soil and roads and precursor pollutants of summer O3 formation from vehicles and industry in Northeast China. Our results revealed the quantitative associations among air pollutants, meteorological conditions and DED outpatients in cold regions, highlighting the importance of coordinated policies in air pollution control and climate change mitigation.

O-214 interaction of air pollution and meteorological factors on IVF outcomes: a multicenter study in China

Abstract Study question Is there an interaction between air pollution and meteorological factors on IVF outcomes? Summary answer The correlation between air-pollutant exposure and IVF outcomes was modified by meteorological conditions, especially temperature and wind speed. What is known already Previous studies revealed associations between air-pollutant exposure and in vitro fertilization (IVF) outcomes. However, modification effects of air pollution on IVF outcomes by meteorological conditions remain elusive. Study design, size, duration Multicenter retrospective cohort study, 2015–2020. Participants/materials, setting, methods This multicenter retrospective cohort study included 15,217 women from five northern Chinese cities during 2015–2020. Daily average concentrations of air pollutants (PM2.5, PM10, O3, NO2, SO2, and CO) and meteorological factors (temperature, relative humidity, wind speed, and sunshine duration) during different exposure windows were calculated as individual approximate exposure. Generalized estimating equations and stratification models were used to assess the associations of air pollution and meteorological conditions with IVF outcomes and estimated potential interactions. Main results and the role of chance Exposure to PM2.5, SO2, and O3 was adversely correlated with pregnancy outcomes in fresh IVF cycles. Positive associations of wind speed and sunshine duration with pregnancy outcomes were detected. In addition, we observed that embryo transfer in spring and summer had a higher likelihood to achieve a live birth compared with winter. In stratified models, pieces of evidence of interaction between meteorological factors and air pollutants on pregnancy outcomes were detected. Negative associations of PM2.5 with clinical pregnancy were only significant at lower temperatures and wind speeds. Moreover, the effects of O3 on live birth were enhanced by higher quartiles of wind speed. Limitations, reasons for caution First of all, we used the data from monitoring stations to estimate the individual exposure, which was inaccurate and may introduce bias. Second, due to data limitations, this study did not discuss socio-economic factors, which were reported to be associated with spatial-temporal variations of air pollutants and reproductive outcomes. Wider implications of the findings Pregnant women should be advised to reduce outdoor time when the air quality was poor, particularly at lower temperatures. Trial registration number not applicable

Unbalanced emission reductions of different species and sectors in China during COVID-19 lockdown derived by multi-species surface observation assimilation

Abstract. The unprecedented lockdown of human activities during the COVID-19 pandemic has significantly influenced social life in China. However, understanding the impact of this unique event on the emissions of different species is still insufficient, prohibiting the proper assessment of the environmental impacts of COVID-19 restrictions. Here we developed a multi-air-pollutant inversion system to simultaneously estimate the emissions of NOx, SO2, CO, PM2.5 and PM10 in China during COVID-19 restrictions with high temporal (daily) and horizontal (15 km) resolutions. Subsequently, contributions of emission changes versus meteorological variations during the COVID-19 lockdown were separated and quantified. The results demonstrated that the inversion system effectively reproduced the actual emission variations in multi-air pollutants in China during different periods of COVID-19 lockdown, which indicate that the lockdown is largely a nationwide road traffic control measure with NOx emissions decreasing substantially by ∼40 %. However, emissions of other air pollutants were found to only decrease by ∼10 % because power generation and heavy industrial processes were not halted during lockdown, and residential activities may actually have increased due to the stay-at-home orders. Consequently, although obvious reductions of PM2.5 concentrations occurred over the North China Plain (NCP) during the lockdown period, the emission change only accounted for 8.6 % of PM2.5 reductions and even led to substantial increases in O3. The meteorological variation instead dominated the changes in PM2.5 concentrations over the NCP, which contributed 90 % of the PM2.5 reductions over most parts of the NCP region. Meanwhile, our results suggest that the local stagnant meteorological conditions, together with inefficient reductions of PM2.5 emissions, were the main drivers of the unexpected PM2.5 pollution in Beijing during the lockdown period. These results highlighted that traffic control as a separate pollution control measure has limited effects on the coordinated control of O3 and PM2.5 concentrations under current complex air pollution conditions in China. More comprehensive and balanced regulations for multiple precursors from different sectors are required to address O3 and PM2.5 pollution in China.

Interaction of air pollution and meteorological factors on IVF outcomes: A multicenter study in China

BackgroundPrevious studies revealed associations between air-pollutant exposure and in vitro fertilization (IVF) outcomes. However, modification effects of air pollution on IVF outcomes by meteorological conditions remain elusive. MethodsThis multicenter retrospective cohort study included 15,217 women from five northern Chinese cities during 2015–2020. Daily average concentrations of air pollutants (PM2.5, PM10, O3, NO2, SO2, and CO) and meteorological factors (temperature, relative humidity, wind speed, and sunshine duration) during different exposure windows were calculated as individual approximate exposure. Generalized estimating equations models and stratified analyses were conducted to assess the associations of air pollution and meteorological conditions with IVF outcomes and estimate potential interactions. ResultsPositive associations of wind speed and sunshine duration with pregnancy outcomes were detected. In addition, we observed that embryo transfer in spring and summer had a higher likelihood to achieve a live birth compared with winter. Exposure to PM2.5, SO2, and O3 was adversely correlated with pregnancy outcomes in fresh IVF cycles, and the associations were modified by air temperature, relative humidity, and wind speed. The inverse associations of PM2.5 and SO2 exposure with biochemical pregnancy were stronger at lower temperatures and humidity. Negative associations of PM2.5 with clinical pregnancy were only significant at lower temperatures and wind speeds. Moreover, the effects of O3 on live birth were enhanced by higher wind speed. ConclusionsOur results suggested that the associations between air-pollutant exposure and IVF outcomes were modified by meteorological conditions, especially temperature and wind speed. Women undergoing IVF treatment should be advised to reduce outdoor time when the air quality was poor, particularly at lower temperatures.

FlorTree: A unifying modelling framework for estimating the species-specific pollution removal by individual trees and shrubs

Atmospheric pollution is a threatening problem around the world, with tropospheric ozone (O3), nitrogen dioxide (NO2) and particulate matter (PM10) among the most harmful pollutants for citizens’ health. Nature-based solutions such as urban trees can cut down air concentrations of these pollutants thanks to stomatal uptake and dry deposition on their canopies and, in addition, uptake carbon dioxide (CO2) and store carbon in their tissues. Unfortunately, some species emit biogenic Volatile Organic Compounds (bVOCs) that are O3-precursors leading to air quality deterioration. As a proper selection of species is essential for urban greening, we developed an innovative single-tree model (FlorTree) to estimate the maximum flux of air pollutants. FlorTree considered species-specific parameters, such as tree morphology (height and crown leaf area), leaf/shoot structure, leaf habit (deciduous/evergreen) and eco-physiological responses to environmental factors, for 221 urban tree and shrub species. We applied the FlorTree model to examine i) which are the best species for air pollution removal in the case study of Florence (Italy) and ii) whether the species-specific removal performance is affected by different climate and air pollution conditions in other cities, namely Bucharest (Romania) and Tokyo (Japan). Results suggested that 24 tall trees (mainly broadleaves belonging to Tilia, Acer and Fraxinus genus) may be recommended for Florence due to their large crowns at maturity (50 years old), relatively high stomatal conductance and no bVOCs release. These general characteristics, however, were affected by climatic and pollutant conditions, suggesting that FlorTree must be applied to the local conditions. Therefore, our results demonstrated that FlorTree can be applied in any city for maximizing the air quality improvement by urban trees.

Relationship of emergency department visits for suicide attempts with meteorological and air pollution conditions

BackgroundEnvironmental factors such as meteorological and air pollution conditions have been identified as risk factors for suicide. This study aimed to clarify the relationship of the number of visits to the emergency department for suicide attempts with meteorological and air pollution conditions. MethodsThis cross-sectional study included patients who attempted suicide and were transported to Yokohama City University Medical Center from April 2005 to March 2022. The meteorological conditions recorded at the time of transport included mean atmospheric pressure, mean temperature, maximum temperature, minimum temperature, mean humidity, wind speed, and sunshine hours, and the air pollution conditions included SO2 (ppm), NO (ppm), NO2 (ppm), NOX (ppm), OX (ppm), CH4 (ppmC), NMHC (ppmC), THC (ppmC), SPM (μg/m3), and PM2.5 (μg/m3). Poisson regression analysis was used to examine the association between the number of suicide attempts and the meteorological and air pollution conditions. Subgroup analyses were conducted by classifying the subjects according to the means of suicide attempt; comparisons were performed using t-tests. ResultsThe study included 1737 patients. Multivariate Poisson regression analyses revealed a significant positive relationship between the number of suicide attempts and SO2 levels and a significant negative relationship between the number of suicide attempts and NO levels. When subjects were divided by means of suicide attempt, different relationships with meteorological and air pollution conditions were observed. ConclusionMeteorological and air pollution conditions are environmental factors that can enable a more detailed understanding of suicide behavior according to the means of suicide attempts.

An integrated analysis of air pollution and meteorological conditions in Jakarta

Air pollution and climate change are general problems for society. This paper proposes an integrated analysis of the Air Quality Index (AQI) and meteorological conditions in Jakarta. The column-based data integration model is applied to create integrated data of the Air Quality Index and meteorological conditions. The integrated data is then used to generate a causal graph using the PC algorithm. The causal graph reveals that there exist causal relationships between pollutants and meteorological conditions, e.g, humidity, rainfall, wind speed, and duration of sunshine affect particulate matter 10 (PM_{10}); wind speed affects sulfur dioxide (SO_2); temperature affects ozone (O_3). The historical data records that the average wind speed is decreased and the number of unhealthy days has risen. Ozone and particulate matter are two pollutants that mainly influence poor air quality in Jakarta. The integrated data is also used to train Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) for forecasting. Experimental results show that LSTM using integrated data produces smaller errors for forecasting AQI and meteorological conditions.

Traffic congestion and air pollution: Empirical evidence before/after COVID-19 in Seoul, Korea

Severe traffic congestion leads to toxic levels of air pollution. We attempt to explore how traffic congestion affects air pollution, especially PM10 and PM2.5, by focusing on the city of Seoul, Korea, which is one of the largest cities in the world and is plagued by severe traffic congestion. We employ a fixed-effect panel model with various datasets, including air pollution, travel speed, and weather conditions. The findings show that traffic congestion adversely affects air quality by increasing the concentration of PM10 and PM2.5. In particular, the impact of traffic congestion on PM10 and PM2.5 was 1.2 times and 1.7 times greater during the COVID-19 period than during the non-COVID-19 period, respectively. In addition, an increase in one unit of RCI is associated with 0.4 increase in PM10 during the peak hours, but 6.7 increase in PM10 during the non-peak hour because of the increased traffic of trucks and motorcycles induced by increased online shopping. To mitigate air pollution, it is suggested that not only reducing vehicle use, but also minimizing traffic congestion is important.