Air pollution exposure associates with increased risk of neonatal jaundice

Long- and Intermediate-Term Ambient Particulate Pollution Is Associated with Increased Osteoarthritis Risk: A Population-Based Prospective Analysis

Recent studies found the intrusion and retention of exogenous fine particles into joints, but epidemiological data for long- and intermediate-term exposure associations are scare. Here, all urban working, retired employee, and rural residents (16.78 million) in Beijing from January 1, 2011 to December 31, 2019 were included to investigate the effects of long- and intermediate-term ambient particulate exposure on development of osteoarthritis. We identified 1,742,067 participants as first-visit patients with osteoarthritis. For each interquartile range increase in annual PM2.5 (23.32 μg/m3) and PM10 (23.92 μg/m3) exposure concentration, the pooled hazard ratios were respectively 1.238 (95% CI: 1.228, 1.249) and 1.178 (95% CI: 1.168, 1.189) for first osteoarthritis outpatient visits. Moreover, age at first osteoarthritis outpatient visits significantly decreased by 4.52 (95% CI: 3.45 to 5.40) days per μg/m3 for annual PM2.5 exposure at below 67.85 μg/m3. Finally, among the six constituents analyzed, black carbon appears to be the most important component associated with the association between PM2.5 exposure and the three osteoarthritis-related outcomes.

"Light" on Phototherapy-Complications and Strategies for Shortening Its Duration, A Review of the Literature

Neonatal hyperbilirubinemia is an extremely common metabolic complication of the neonatal period which may be associated with bilirubin encephalopathy and even death. Adverse neurological consequences are preventable if a timely diagnosis and treatment are provided. Phototherapy is usually the preferred option to decrease hyperbilirubinemia. Although considered to be safe, evidence in recent years has shown that this treatment may not be free of side effects and short- and long-term unfavorable outcomes. These are usually mild or rare, but should be decreased or avoided if possible. Many useful complementary measures and treatments have been described that could shorten the duration of exposure to phototherapy. However, there is no current unequivocal recommendation to use any of the methods presented in this review. Our review aims to depict the wide range of possible complementary treatments to phototherapy, and to provide the scientific and clinical evidence available regarding their usefulness. It is essential that, while utilizing the full potential of phototherapy to treat hyperbilirubinemia, caregivers are aware of its side effects and possible inherent dangers, and seek ways to minimize the exposure to phototherapy to what is really needed for the newborn. Further studies are needed to clarify the preferred complementary treatments that could reduce the duration of exposure to phototherapy without impairing its effectiveness.

A preliminary analysis of global neonatal disorders burden attributable to PM2.5 from 1990 to 2019

BACKGROUND

Prenatal fine particulate matter (PM_2.5) exposure is related to various neonatal diseases (ND). However, data and studies assessing the neonatal disease burden caused by PM_2.5 at the global level are limited, especially comparing countries with various socioeconomic development levels. We, therefore, assessed three-decades spatiotemporal changes in neonatal disease burden from 1990 at a national level, combined with the socio-demographic index (SDI).

METHODS

We extracted statistics from the Global Burden of Disease Study database for this retrospective study, and analyzed differences in the age-standardized mortality rate (ASMR) of ND and five sub-causes related to PM_2.5 by gender, nationality, and SDI. To describe the trend of ASMR, the Joinpoint model was adopted to predict the annual percentage change (APC) and the average annual percentage changes (AAPCs). We executed the Gaussian process regression model to predict the relevance between SDI and ASMR.

RESULTS

The ND burden associated with PM_2.5 kept rising since 1990, especially in low-middle SDI regions, South Asia, and Sub-Saharan Africa, and the sex ratio of ASMR was >1 at the global level and all five SDI regions. The leading cause of death was neonatal preterm birth. The global ASMR level of ND was 2.09 per 100,000 population in 2019 and AAPCs was 0.91 (98 % CI: 0.28, 1.55) meanwhile AAPCs decreased with rising SDI levels. The decreasing trend of ASMR in ND was detected in regions with higher SDI, such as North America, Europe, and Australasia.

CONCLUSIONS

In the past three decades, the global burden of ND related to PM_2.5 has ascended considerably in lower SDI regions hence PM_2.5 is still considered a notable environmental hazard factor for newborn diseases.

Dynamics of green spaces- Land surface temperature intensity nexus in cities of Ethiopia

In this study, the dynamics of green spaces and land surface temperature patterns in four cities in Ethiopia were investigated using Landsat imagery. The typical characteristics of LST over the past three decades (1990-2020) in relation to green space dynamics were first investigated; subsequently, the spatial distribution of LST was characterized based on hybrid geospatial techniques and mono-window algorithm analysis, in which the contributions of green spaces to LST were studied. In addition, the multiple linear regression method and spatial regression models (SRMs) were employed to investigate and predict the spatial dependence of LST and urbanization-induced green space dynamics. Results show that cities horizontally expanded unceasingly from 1990 to 2020, with a substantial discrepancy in expansion rates and the spatial patterns of UHI intensities among the cities (p < 0.05). Moreover, the area proportion of the UHI is significantly larger than that of the UGS, and the differences in the UGS cooling contribution were found in different land uses and zones of the cities. In the study periods, the spatial pattern of LST was significantly controlled by NDBI, and its coefficient in the OLS followed the pattern NDVI > MNDWI > latitudes > longitudes > population density > DEM. Due to the large proportions of buildings While green land and water bodies show significant capability to mitigate UHI effects, cooling effects are not apparent when their sizes are small. Besides, the SRMs show that UHI intensities were significantly influenced by MNDWI in Bahir Dar and Hawassa (p < 0.01).Cities' LAMBDA coefficients have a positive relationship with UHII (p < 0.01). Our study could help city planners and the government understand the current cooling potential of existing UGS to mitigate the dynamics of UHI and sustain the sustainability of green space management in cities.

Development of On-Demand Antiviral Electrostatic Precipitators with Electrothermal-Based Antiviral Surfaces against Airborne Virus Particles

Particulate matter, including airborne pathogens, is of particular concern because it can cause the spread of diseases through aerosol transmission. In this study, a new concept is proposed: on-demand antiviral electrostatic precipitators (ESPs) with electrothermal-based antiviral surfaces. We applied electrothermal-based antiviral surfaces to air-purifying applications and demonstrated that the proposed method is effective with regard to collecting airborne virus particles on collection plates in a two-stage ESP. With alternating current power, MS2 bacteriophage and H1N1 viruses were completely deactivated after exposure to 50 °C for 30 min. This remarkable antiviral performance via electrothermal effects indicates that on-demand platforms for self-antiviral surfaces can perform sterilization immediately without generating secondary pollutants, thus effectively preventing the spread of infectious microorganisms in public places. We believe that the results of this study can provide useful guidelines for the design and realization of practical and wearable devices for antiviral air-purifying applications.

Evaluation Methods for Water Resource Suitability in Territorial Spatial Planning: A Case Study of Baiyin City in a Semi-Arid Region

Water resources are a major factor in the spatial layout of agricultural production and urban construction, which is an important part of China's ongoing territorial spatial planning. In order to assess the constraining and guiding effects of water resources on territorial spatial planning, water resources suitability evaluation needs to be carried out at the grid scale. Traditional basin or regional-scale indicators of water resources cannot satisfy the requirements with high spatial accuracy in territorial spatial planning, because the internal differences could not be described. In this study, irrigation water supply cost index (CIA) and urban water supply cost index (CIU) were evaluated to characterize the affordability of potential water supply costs by simulating of optimal water supply path. Further, grid-scale indexes of water resource suitability for agricultural production (WRSA) and for urban construction (WRSU) were constructed. The grades of WRSA and WRSU were classified at a 20 m grid scale in Baiyin City. The areas of water resources that were suitable, relatively suitable, less suitable, and unsuitable for agricultural production were 381.0 km², 3354.7 km², 3663.9 km², and 12,700.7 km², respectively, accounting for 1.9%, 16.7%, 18.2%, and 63.2% of the total area of Baiyin City. The areas of water resources that were suitable, relatively suitable, less suitable, and unsuitable for urban construction were 1657.7 km², 4184.5 km², 1177.7 km², and 13,075.7 km², respectively, accounting for 8.2%, 20.8%, 5.9%, and 65.1% of the total area of Baiyin City. Coupling analysis with land use and land resources suitability were carried out in this study, which showed that the grid-scale WRSA and WRSU could well characterize the spatial differences of water resources suitability for agricultural production and urban construction. The results of the Geodetector-based study show that the WRSA and WRSU indicators have better explanatory power for the land-use spatial distribution compared to indicators such as water distance. Therefore, the indexes could provide scientific support to delimit agricultural space and urban space, and are effective means of "determining regional functions by water resources" in territorial spatial planning. Furthermore, the indexes could be applied to other arid and semi-arid areas, and also hilly areas, where water supply suitability plays a restrictive role in agricultural production and urban construction.

Structural and Dynamic Analysis of Sulphur Dioxide Adsorption in a Series of Zirconium‐Based Metal–Organic Frameworks

We report reversible high capacity adsorption of SO₂ in robust Zr‐based metal–organic framework (MOF) materials. Zr‐bptc (H₄bptc=biphenyl‐3,3′,5,5′‐tetracarboxylic acid) shows a high SO₂ uptake of 6.2 mmol g⁻¹ at 0.1 bar and 298 K, reflecting excellent capture capability and removal of SO₂ at low concentration (2500 ppm). Dynamic breakthrough experiments confirm that the introduction of amine, atomically‐dispersed Cu^II or heteroatomic sulphur sites into the pores enhance the capture of SO₂ at low concentrations. The captured SO₂ can be converted quantitatively to a pharmaceutical intermediate, aryl N‐aminosulfonamide, thus converting waste to chemical values. In situ X‐ray diffraction, infrared micro‐spectroscopy and inelastic neutron scattering enable the visualisation of the binding domains of adsorbed SO₂ molecules and host–guest binding dynamics in these materials at the atomic level. Refinement of the pore environment plays a critical role in designing efficient sorbent materials.

Engineering surface segregation of perovskite oxide through wet exsolution for CO catalytic oxidation

Cation segregation occurring near the surface or interfaces of solid catalysts plays an important role in catalytic reactions. Unfortunately, the native surface of perovskite oxides is dominated by passivated A-site segregation, which severely hampers the catalytic activity and durability of the system. To address this issue, herein, we present a wet exsolution method to reconstruct surface segregation in perovskite cobalt oxide. Under reduction etching treatment of glycol solution, inert surface Sr segregation was transformed into active Co₃O₄ segregation. By varying the reaction time, we achieved differing coverage of the active Co₃O₄ segregation on the La_0.5Sr_0.5CoO_3-δ (LSCO) perovskite oxide surface. This study reveals that CO oxidation activity exhibits a volcano-shaped dependence on the coverage of Co₃O₄ segregation at the surface of a perovskite cobalt oxide. Furthermore, we find that a suitable coverage of Co₃O₄ segregation can dramatically improve the catalytic activity of the perovskite catalyst by enhancing interface interactions. Co K-edge, Co L-edge, and O K-edge X-ray absorption spectra confirm that the synergistic effect optimizes the covalence of the metal-oxygen bond at the surface and interface. This work not only contributes to the design and development of perovskite-type catalysts, but also provides important insight into the relationship between surface segregation and catalytic activity.

Development and validation of a maternal anxiety for neonatal jaundice scale in China

BACKGROUND

Maternal anxiety induced by neonatal jaundice has adverse effects on maternal and infant health, but there was no specific tool to identify the anxiety level of mothers. This study aims to develop a Maternal Anxiety for Neonatal Jaundice Scale (MANJS) and to validate it in the target population.

METHODS

An initial 11-items MANJS was developed through literature review, expert panel consultation, and a pilot-test. Subsequently, mothers of neonates with jaundice were recruited from the Maternal and Child Health Hospital of Hainan Province, China, from June to December 2018, for a formal questionnaire survey. Based on the data collected, the scale was validated for construct validity, convergent validity, discriminant validity, content validity, and internal consistency reliability after the items screening.

RESULTS

The reliability and validity of MANJS were validated in 1127 mothers of jaundiced neonates. After the item with cross-loadings was removed using exploratory factor analysis, MANJS consisted of two dimensions and 10 items, with a cumulative variance contribution of 74.36% and factor loadings above 0.6 for all items. The confirmatory factor analysis identified three items with cross-factor loading or error correlation and then they were removed orderly. The further confirmatory factor analysis showed a good construct validity for the 7-item MANJS, with standardized root mean square residual (SRMR) = 0.029, root mean square error of approximation (RMSEA) = 0.068, comparative fit index (CFI) = 0.961, Tucker-Lewis index (TLI) = 0.937, incremental fit index (IFI) = 0.961, normed fit index (NFI) = 0.954, goodness of fit index (GFI) = 0.998, adjusted goodness of fit index (AGFI) = 0.996, respectively. The average variance extracted values (AVE) of the two factors were 0.80 and 0.72, and the combined reliability (CR) were 0.94 and 0.88, respectively. Cronbach's alpha was 0.90 for the MANJS, and split-half reliability was 0.72.

CONCLUSIONS

MANJS was demonstrated to have satisfactory reliability and validity in evaluating maternal anxiety caused by neonatal jaundice among Chinese postpartum women.

Safety Assessment of One Lactiplantibacillus plantarum Isolated from the Traditional Chinese Fermented Vegetables—Jiangshui

Lactiplantibacillus plantarum is a kind of extensively utilized probiotic species, which plays a critical role in the prevention of pathogenic bacteria and development of functional probiotics. Our group previously isolated one Lactiplantibacillus from Jiang Shui, a traditional Chinese fermented vegetable, which remarkably inhibited the growth of Aspergillus flavus. Herein, the safety of this isolate was assessed to ensure its application feasibility in food industry. Firstly, the phenotypic analyses including tolerance to low pH and bile salt, aggregation ability, and hemolytic activity detection, indicated the isolate could survive and colonize in the gastrointestinal tract, without hemolysin activity. The susceptibilities of the isolate to eight antibiotics and the absence of most resistance genes were demonstrated by agar disk diffusion and PCR, respectively. Furthermore, no mortality or toxicity was observed in mice by in vivo tests using gross autopsy, hematology, serum biochemistry, and HE-staining. Taken together, this study demonstrated the safety of Lactiplantibacillus plantarum WYH as a probiotic strain in terms of phenotypic analyses, absence of antimicrobial resistance and toxin-related genes, as well as mice toxicity test, while supported the prospect of applying isolate in suppression of fungal growth and mycotoxin biosynthesis.

Adsorption of Sulfur Dioxide in Cu(II)-Carboxylate Framework Materials: The Role of Ligand Functionalization and Open Metal Sites

The development of efficient sorbent materials for sulfur dioxide (SO₂) is of key industrial interest. However, due to the corrosive nature of SO₂, conventional porous materials often exhibit poor reversibility and limited uptake toward SO₂ sorption. Here, we report high adsorption of SO₂ in a series of Cu(II)-carboxylate-based metal–organic framework materials. We describe the impact of ligand functionalization and open metal sites on the uptake and reversibility of SO₂ adsorption. Specifically, MFM-101 and MFM-190(F) show fully reversible SO₂ adsorption with remarkable capacities of 18.7 and 18.3 mmol g^–1, respectively, at 298 K and 1 bar; the former represents the highest reversible uptake of SO₂ under ambient conditions among all porous solids reported to date. In situ neutron powder diffraction and synchrotron infrared microspectroscopy enable the direct visualization of binding domains of adsorbed SO₂ molecules as well as host–guest binding dynamics. We have found that the combination of open Cu(II) sites and ligand functionalization, together with the size and geometry of metal–ligand cages, plays an integral role in the enhancement of SO₂ binding.

Ambient temperatures associated with increased risk of motor vehicle crashes in New York and Chicago

Motor Vehicle Crashes (MVC) are a major cause of death and disability worldwide. Yet it remains unknown to what extent changes in cold and hot temperatures affect the MVC. Here we quantify the linkage between ambient temperature exposure and the MVC risk of the driver in four cities of the United States. After adjusting for confounding factors, we find both a cold effect and a hot effect on MVC in New York, and a cold effect on MVC in Chicago. A 1 °C decrease in mean daily temperature below a cold threshold of -4.8 °C is associated with an increase in the overall cumulative relative risk of MVC by 11.59% (95% CI: 5.17%-16.43%) over 0-28 lag days for New York. The respective risk increase is 1.58% (95% CI: 0.36%-2.79%) over 0-2 lag days for a 1 °C increase in mean daily temperature above the hot threshold of 26.1 °C for New York. There is no significant heat wave or cold spell effects except for the heat wave effect on the consecutive heat wave days 7-10 in New York. Our study provides evidence of the association between driver exposure to low or high temperatures and the MVC risk. Improved public- administration preventive measures and policymaking are needed to minimize the negative consequences of abnormal temperatures on road safety driving.

Using Multi-Source Geospatial Information to Reduce the Saturation Problem of DMSP/OLS Nighttime Light Data

The DMSP/OLS Nighttime light (NTL) data directly reflect the spatial distribution and light intensity of artificial lighting from the Earth’s surface at night, and has become an emerging instrument for urbanization research, including in the monitoring of urban expansion, assessment of socio-economic vitality, and estimation of energy consumption and population. However, due to the imperfect sensor design of DMSP/OLS, the dynamic range of the digital number (DN) of NTL is limited (0, 63), leading to a significant saturation problem when describing the actual light intensity, especially in dense urban areas with high light intensity. This saturation problem masks spatial differences in light intensity and weakens the reliability of DMSP/OLS NTL data. Therefore, this study proposes a novel desaturation indicator that combines NDBI and POI, the Building and POI Density-Adjusted Nighttime Light Index (BPANTLI), to regulate the DMSP/OLS NTL saturation problem based on the spatial characteristics of urban structures and human activity intensity. The proposed method is applied to three urban agglomerations with the most severe light saturation issues in China. The geographical detector model is firstly utilized to quantify the effectiveness of NDBI and POI in reflecting the difference in light intensity distribution from the NTL potential saturation region (NTL DN value (53, 63)) and NTL unsaturation region (NTL DN value (0, 52)), so as to clarify the feasibility of developing the BPANTLI. The applicability of BPANTLI is validated through three aspects—comparison of the desaturation capacity and the performance of delineating light intensity; verification of the consistency of BPANTLI with radiometric calibration nighttime light product (RCNTL) and NPP/VIIRS data; and assessing the accuracy of the BPANTLI in estimating socio-economic parameters (GDP, electricity consumption, population density). The results indicate that the BPANTLI possesses superior capability in regulating the NTL saturation problem, achieving good performance in distinguishing inner-urban structures. The regulated results reveal a remarkably improved correspondence with the RCNTL and NPP/VIIRS data, providing a more realistic picture of the light intensity distribution. It is worth noting that, given the advantages of NDBI and POI vector data in spatial resolution, the BPANTLI established in this study can overcome the limitation of the spatial resolution of DMSP/OLS nighttime lighting data and achieve dynamic transformation of the spatial resolution. The higher spatial resolution desaturation results allow for a better characterization of the light intensity distribution. Moreover, the BPANTLI-regulated light intensity significantly improves the accuracy of estimating electricity consumption, GDP, and population density, which provides a valuable reference for urban socio-economic activity assessment. Thus, the BPANTLI proposed in this study can be considered as a reasonable desaturation method with a high application value.

Comparison of Four Machine Learning Techniques for Prediction of Intensive Care Unit Length of Stay in Heart Transplantation Patients

Background

Post-operative heart transplantation patients often require admission to an intensive care unit (ICU). Early prediction of the ICU length of stay (ICU-LOS) of these patients is of great significance and can guide treatment while reducing the mortality rate among patients. However, conventional linear models have tended to perform worse than non-linear models.

Materials and Methods

We collected the clinical data of 365 patients from Wuhan Union Hospital who underwent heart transplantation surgery between April 2017 and August 2020. The patients were randomly divided into training data (N = 256) and test data (N = 109) groups. 84 clinical features were collected for each patient. Features were validated using the Least Absolute Shrinkage and Selection Operator (LASSO) regression’s fivefold cross-validation method. We obtained Shapley Additive explanations (SHAP) values by executing package “shap” to interpret model predictions. Four machine learning models and logistic regression algorithms were developed. The area under the receiver operating characteristic curve (AUC-ROC) was used to compare the prediction performance of different models. Finally, for the convenience of clinicians, an online web-server was established and can be freely accessed via the website https://wuhanunion.shinyapps.io/PredictICUStay/.

Results

In this study, 365 consecutive patients undergoing heart transplantation surgery for moderate (NYHA grade 3) or severe (NYHA grade 4) heart failure were collected in Wuhan Union Hospital from 2017 to 2020. The median age of the recipient patients was 47.2 years, while the median age of the donors was 35.58 years. 330 (90.4%) of the donor patients were men, and the average surgery duration was 260.06 min. Among this cohort, 47 (12.9%) had renal complications, 25 (6.8%) had hepatic complications, 11 (3%) had undergone chest re-exploration and 19 (5.2%) had undergone extracorporeal membrane oxygenation (ECMO). The following six important clinical features were selected using LASSO regression, and according to the result of SHAP, the rank of importance was (1) the use of extracorporeal membrane oxygenation (ECMO); (2) donor age; (3) the use of an intra-aortic balloon pump (IABP); (4) length of surgery; (5) high creatinine (Cr); and (6) the use of continuous renal replacement therapy (CRRT). The eXtreme Gradient Boosting (XGBoost) algorithm presented significantly better predictive performance (AUC-ROC = 0.88) than other models [Accuracy: 0.87; sensitivity: 0.98; specificity: 0.51; positive predictive value (PPV): 0.86; negative predictive value (NPV): 0.93].

Conclusion

Using the XGBoost classifier with heart transplantation patients can provide an accurate prediction of ICU-LOS, which will not only improve the accuracy of clinical decision-making but also contribute to the allocation and management of medical resources; it is also a real-world example of precision medicine in hospitals.

Exposure to air pollution is associated with congenital anomalies in the population born by in vitro fertilization

BACKGROUND

Congenital anomalies (CAs) are the leading causes for children's disabilities and mortalities worldwide. The associations between air pollution and CAs are not fully characterized in fetuses born by in vitro fertilization (IVF) who are at high risk of congenital anomalies.

METHODS

We conducted a cross-sectional study including 16,971 IVF cycles from three hospitals in Hebei Province, China, 2014-2019. Air quality data was obtained from 149 air monitoring stations. Individual average daily concentrations of PM_2.5, PM₁₀, NO₂, SO₂, CO, and O₃ were estimated by spatiotemporal kriging method. Exposure windows were divided into 5: preantral follicle period, antral follicle period, germinal period, embryonic period and early fetal period. Logistic generalized estimating equations were used to estimate the associations between air pollutants and overall or organ-system specific congenital anomalies. Negative control exposure method was used to detect and reduce bias of estimation.

RESULTS

We found increasing levels of PM_2.5 and PM₁₀ were associated with higher risk of overall congenital anomalies during early fetal period, equating gestation 10-12 weeks (OR: 1.05, 95% CI: 1.02-1.09, p = 0.013 for a 10 μg/m³ increase of PM_2.5; OR: 1.03, 95% CI: 1.01-1.06, p = 0.021 for a 10 μg/m³ increase of PM₁₀). Cleft lip and cleft palate were associated with PM₁₀ in germinal period and early fetal period. The CAs of eye, ear, face and neck were related to CO in preantral follicle stage. We did not find an association between chromosome abnormalities and air pollution exposure.

CONCLUSIONS

We concluded that ambient air pollution was a risk factor for congenital anomalies in the fetuses conceived through IVF, especially exposure in early fetal period.

Exposure to air pollutants during pregnancy and after birth increases the risk of neonatal hyperbilirubinemia

OBJECTIVES

Exposure to air pollution is associated with increased risks of several adverse conditions in newborns, such as preterm birth. Whether air pollution is associated with neonatal hyperbilirubinemia remains unclear. We aimed to develop and validate an air-quality-based model to better predict neonatal hyperbilirubinemia.

METHODS

A multicenter, population-based cohort of neonates with a gestational age (GA) ≥35 weeks and birth weight ≥2000 g was enrolled in the study. The study was conducted in Shanghai, China, from July 2017 to December 2018. The daily average concentrations of particulate matter (PM) with aerodynamic diameters≤2.5 μm (PM2.5) and ≤10 μm (PM10), sulfur dioxide (SO₂), nitrogen dioxide (NO2) and carbon monoxide (CO) were measured. Neonatal hyperbilirubinemia was diagnosed according to the American Academy of Pediatrics (AAP) guidelines by trained neonatologists. We used logistic least absolute shrinkage and selection operator (LASSO) regression to screen air pollutant indicators related to neonatal hyperbilirubinemia and build an air-quality signature for each patient. An air-quality-based nomogram was then established to predict the risk of neonatal hyperbilirubinemia.

RESULTS

A total of 11196 neonates were evaluated. Prenatal PM10, CO and NO₂ exposure and postpartum SO₂ exposure were significantly associated with neonatal hyperbilirubinemia. The air-quality score was calculated according to the hyperbilirubinemia-related pollutants. The air-quality score of the hyperbilirubinemia group was significantly higher than that of the nonhyperbilirubinemia group (P < .01, odds ratio = 2.97). An air-quality-based logistic regression model was built and showed good discrimination (C-statistic of 0.675 [95% CI (confidence interval), 0.658 to 0.692]) and good calibration. Decision curve analysis showed that the air-quality-based model was better than the traditional clinical model in predicting neonatal hyperbilirubinemia.

CONCLUSIONS

The findings of this study suggest that ambient air pollution exposure is associated with an increased risk of neonatal hyperbilirubinemia. Our results encourage further exploration of this possibility in future studies.

Spatiotemporal Variations and Driving Factors of Ecological Land during Urbanization—A Case Study in the Yangtze River’s Lower Reaches

Ecological land change is an important indicator of eco-environment quality when balancing urbanization and regional ecological safety. Nantong, located in the Yangtze River’s lower reaches, has experienced rapid urbanization since the reform and opening-up policy was implemented in China in 1978. To ensure the regional ecological conservation and restoration of the Yangtze River and the city’s sustainable development, we used remote sensing technology and statistical yearbook data as well as land use dynamic degree (LUDD) and Geodetector methods to determine the spatiotemporal dynamics of ecological land in the Nantong riverine area from 1980 to 2020 and further discussed the potential driving factors. We found that (1) from 1980 to 2020, the major types of ecological land changed from cropland (82.08%), water (17.19%), and grassland (0.69%) to cropland (70.11%), water (26.98%), and forestland (2.25%), and the ecological land area decreased by 4091.36 km2 during the same period with a significantly increased dynamic degree of land use. (2) Spatial heterogeneity existed in the distribution and variation of ecological land. Water was the dominant ecological land use in the Yangtze River levee’s inner area, with transitions to cropland and impervious surfaces as the primary conversion types; cropland was the primary land use in the levee’s external area, with transitions from cropland and water to impervious surface as the primary conversion types. In addition, in cities with an early start and a high level of urbanization, most of the ecological land had been converted to impervious surfaces by urban development, whereas cities without those characteristics had retained more of their ecological land. (3) Ecological land change was influenced by a combination of natural and socio-economic factors, and there were enhanced-bi and enhanced-nonlinear interactions between them. (4) The dominant factors influencing ecological land changes during the three stages of urbanization (1980–2000, 2000–2010, and 2010–2020) were the distance to the Yangtze River, the population, and the GDP (Gross Domestic Product) of secondary industry, respectively. The role of environmental policies has gradually increased in recent years, which has played a positive role in ecological land use restoration. The findings of this study can assist policymakers in optimizing land use and restoring ecological space to conserve biodiversity.

Maternal Exposure to Air Pollution Is Associated with Neonatal Jaundice: A Retrospective Cohort Study

OBJECTIVE

To evaluate the association between maternal ambient pollutant exposure and neonatal jaundice in multiple pollutant species and examine sex differences.

STUDY DESIGN

Epidemiologic study: Records of 13 297 newborns (6153 male, 7144 female) born in Taichung, Taiwan were obtained from a national database. Average concentrations of prenatal air pollutants 3 months prior to birth were divided into low, middle, and high levels. Neonatal jaundice phototherapy rates between mothers who suffered varying air pollutant levels were compared. Clinical study: Three hundred seventy-six newborns (189 male, 187 female) born and received jaundice treatment with phototherapy in a hospital in Taichung, Taiwan were recruited. The correlation between prenatal exposure to air pollutants 3 months prior to birth, newborn's serum bilirubin, and serum hemoglobin were calculated.

RESULTS

Epidemiologic study: Male newborns born to mothers exposed to high carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO₂), and methane (CH₄) levels had higher phototherapy rates. In female newborns, the same was noted for CO and CH₄. Clinical study: Male newborns had a positive correlation between CO, ≤2.5 μm diameter particles, ≤10 μm diameter particles, NO, NO₂, nonmethane hydrocarbon, and CH₄ exposure 3 months prior to birth and serum bilirubin levels. Female newborns had a positive correlation for CH₄. A positive correlation between CO, ≤2.5 μm diameter particles, ≤10 μm diameter particles, NO₂, nonmethane hydrocarbon, CH₄ exposure, and serum hemoglobin levels was noted in male newborns.

CONCLUSION

Maternal exposure to air pollutants may increase neonatal jaundice treatment rates for phototherapy and higher neonatal serum total bilirubin level. Higher hemoglobin levels because of higher pollutant exposures may explain our findings. The association was more obvious in male newborns.

The deep blue day is decreasing in China

The deep blue sky is an indicator of a lower concentration of aerosols and a cloudless sky. With increasing human emissions, a trend towards days with fewer deep blue skies might indicate a decline in a good living environment for humans. This study investigates the long-term changes of the deep blue sky in China from 1980 to 2018. Due to a lack of direct measurements, we use atmospheric visibility and low cloud cover to classify blue sky days into three grades: light blue day, medium blue day, and deep blue day. Climatologically, annual deep blue days increase from southeast China to northwest China, with the maximum number in Xinjiang and eastern Inner Mongolia and the minimum number in western Qinghai and southern Hebei. From 1980 to 2018, annual deep blue days show a prominent decreasing trend in most of China, with area-mean annual deep blue days decreasing by -0.48 days per year (d/y) in China, and the variation becomes more obvious after 2013. The maximum decreasing trend is observed in eastern China. The most prominent decreases of deep blue days are seen in winter. Both air pollution and the change in meteorological conditions contribute to the decrease of wintertime deep blue days in China. Specifically, the decrease in surface wind speed hinders the cleaning of air by winds, the increase in surface air temperature, and decrease in relative humidity is favorable for low cloud increase, and the increasing emission of pollution reduces atmospheric visibility.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00704-021-03898-1.

Assessment of the Factors Influencing Sulfur Dioxide Emissions in Shandong, China

Sulfur dioxide (SO2) is a serious air pollutant emitted from different sources in many developing regions worldwide, where the contribution of different potential influencing factors remains unclear. Using Shandong, a typical industrial province in China as an example, we studied the spatial distribution of SO2 and used geographical detectors to explore its influencing factors. Based on the daily average concentration in Shandong Province from 2014 to 2019, we explored the influence of the diurnal temperature range, secondary production, precipitation, wind speed, soot emission, sunshine duration, and urbanization rate on the SO2 concentration. The results showed that the diurnal temperature range had the largest impact on SO2, with q values of 0.69, followed by secondary production (0.51), precipitation (0.46), and wind speed (0.42). There was no significant difference in the SO2 distribution between pairs of sunshine durations, soot emissions, and urbanization rates. The meteorological factors of precipitation, wind speed, and diurnal temperature range were sensitive to seasonal changes. There were nonlinear enhancement relationships among those meteorological factors to the SO2 pollution. There were obvious geographical differences in the human activity factors of soot emissions, secondary production, and urbanization rates. The amount of SO2 emissions should be adjusted in different seasons considering the varied effect of meteorological factors.

Evaluation of the Influence between Local Meteorology and Air Quality in Beijing Using Generalized Additive Models

Previous studies have confirmed the inextricable connection between meteorological factors and air pollutants. This study presents the complex nonlinear relationship between meteorological variables and four major air pollutants under high-concentration air pollution in Beijing. The generalized additive model combined with marginal effects is used for quantitative analysis. After controlling the confounding factors such as long-term trends, seasonality and spatio-temporal deviation, the final fitting results exhibit that temperature, relative humidity and visibility are the most significant meteorological variables associating with PM2.5 concentration, and the marginal effect reaches 80%, −23% and 270%, respectively. Temperature and relative humidity are the most significant variables for SO2, and the marginal effect reaches 15% and 7%. The most significant variables for O3 are temperature and solar radiation, with marginal effect of up to 70% and 8%. Atmospheric pressure and temperature results in a positive effect on CO, and the marginal effect can reach 18% and 80%. All these indicate that local meteorological variables are a significant driving factor for air quality in Beijing. Other variables, such as wind speed, visibility, and precipitation, display some influence on air pollutants, but have less explanatory power in the model. Overall, our study provides a better understanding of the relationship between local meteorological variables and air quality, as well as an insight into how climate change affects air quality.

Investigating the Role of Green Infrastructure on Urban WaterLogging: Evidence from Metropolitan Coastal Cities

Urban green infrastructures (UGI) can effectively reduce surface runoff, thereby alleviating the pressure of urban waterlogging. Due to the shortage of land resources in metropolitan areas, it is necessary to understand how to utilize the limited UGI area to maximize the waterlogging mitigation function. Less attention, however, has been paid to investigating the threshold level of waterlogging mitigation capacity. Additionally, various studies mainly focused on the individual effects of UGI factors on waterlogging but neglected the interactive effects between these factors. To overcome this limitation, two waterlogging high-risk coastal cities—Guangzhou and Shenzhen, are selected to examine the effectiveness and stability of UGI in alleviating urban waterlogging. The results indicate that the impact of green infrastructure on urban waterlogging largely depends on its area and biophysical parameter. Healthier or denser vegetation (superior ecological environment) can more effectively intercept and store rainwater runoff. This suggests that while increasing the area of UGI, more attention should be paid to the biophysical parameter of vegetation. Hence, the mitigation effect of green infrastructure would be improved from the “size” and “health”. The interaction of composition and spatial configuration greatly enhances their individual effects on waterlogging. This result underscores the importance of the interactive enhancement effect between UGI composition and spatial configuration. Therefore, it is particularly important to optimize the UGI composition and spatial pattern under limited land resource conditions. Lastly, the effect of green infrastructure on waterlogging presents a threshold phenomenon. The excessive area proportions of UGI within the watershed unit or an oversized UGI patch may lead to a waste of its mitigation effect. Therefore, the area proportion of UGI and its mitigation effect should be considered comprehensively when planning UGI. It is recommended to control the proportion of green infrastructure at the watershed scale (24.4% and 72.1% for Guangzhou and Shenzhen) as well as the area of green infrastructure patches (1.9 ha and 2.8 ha for Guangzhou and Shenzhen) within the threshold level to maximize its mitigation effect. Given the growing concerns of global warming and continued rapid urbanization, these findings provide practical urban waterlogging prevention strategies toward practical implementations.

Ultrafast Detection of Sulfur Dioxide Derivatives by a Distinctive "Dual-Positive-Ion" Platform that Features a Doubly Activated but Irreversible Michael Addition Site

Sulfur dioxide (SO₂) is a gaseous signaling molecule and widely used as a preservative for foods, but its excessive intake is closely related to a series of diseases. Therefore, the development of a potent fluorescence probe for the detection of SO₂ in foods and biological systems is of great significance. Herein, we report for the first time a "dual-positive-ion" platform-based fluorescence probe CMQ, designed by a doubly activated but irreversible strategy, which results in its ultrafast response to SO₂ within 5 s in pure aqueous solution together with a low detection limit as 15.6 nM. In addition, the probe was successfully applied for imaging of SO₂ in mitochondria of living cells and zebrafish and prepared as a reagent kit for convenient and instantaneous quantification of HSO₃^- in real food samples.

Ambient PM2.5 exposure and rapid spread of COVID-19 in the United States

It has been posited that populations being exposed to long-term air pollution are more susceptible to COVID-19. Evidence is emerging that long-term exposure to ambient PM2.5 (particulate matter with aerodynamic diameter 2.5 μm or less) associates with higher COVID-19 mortality rates, but whether it also associates with the speed at which the disease is capable of spreading in a population is unknown. Here, we establish the association between long-term exposure to ambient PM2.5 in the United States (US) and COVID-19 basic reproduction ratio R0- a dimensionless epidemic measure of the rapidity of disease spread through a population. We inferred state-level R0 values using a state-of-the-art susceptible, exposed, infected, and recovered (SEIR) model initialized with COVID-19 epidemiological data corresponding to the period March 2-April 30. This period was characterized by a rapid surge in COVID-19 cases across the US states, implementation of strict social distancing measures, and a significant drop in outdoor air pollution. We find that an increase of 1 μg/m3 in PM2.5 levels below current national ambient air quality standards associates with an increase of 0.25 in R0 (95% CI: 0.048-0.447). A 10% increase in secondary inorganic composition, sulfate-nitrate-ammonium, in PM2.5 associates with ≈10% increase in R0 by 0.22 (95% CI: 0.083-0.352), and presence of black carbon (soot) in the ambient environment moderates this relationship. We considered several potential confounding factors in our analysis, including gaseous air pollutants and socio-economical and meteorological conditions. Our results underscore two policy implications - first, regulatory standards need to be better guided by exploring the concentration-response relationships near the lower end of the PM2.5 air quality distribution; and second, pollution regulations need to be continually enforced for combustion emissions that largely determine secondary inorganic aerosol formation.

Ambient air pollution exposed during preantral-antral follicle transition stage was sensitive to associate with clinical pregnancy for women receiving IVF

Maternal exposure to air pollution is associated with poor reproductive outcomes in in vitro fertilization (IVF). However, the susceptible time windows are still not been known clearly. In the present study, we linked the air pollution data with the information of 9001 women receiving 10,467 transfer cycles from August 2014 to August 2019 in The Second Hospital of Hebei Medical University, Shijiazhuang City, China. Maternal exposure was presented as individual average daily concentrations of PM_2.5, PM₁₀, NO₂, SO₂, CO, and O_3, which were predicted by spatiotemporal kriging model based on residential addresses. Exposure windows were divided to five periods according to the process of follicular and embryonic development in IVF. Generalized estimating equation model was used to evaluate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for association between clinical pregnancy and interquartile range increased average daily concentrations of pollutants during each exposure period. The increased PM_2.5 (adjusted OR = 0.95, 95% CI: 0.90, 0.99), PM₁₀ (adjusted OR = 0.93, 95% CI: 0.89, 0.98), NO₂ (adjusted OR = 0.89, 95% CI: 0.85, 0.94), SO₂ (OR = 0.94, 95% CI: 0.90, 0.98), CO (adjusted OR = 0.93, 95% CI: 0.89, 0.97) whereas decreased O₃ (OR = 1.08, 95% CI: 1.02, 1.14) during the duration from preantral follicles to antral follicles were the strongest association with decreased probability of clinical pregnancy among the five periods. Especially, women aged 20-29 years old were more susceptible in preantral-antral follicle transition stage. Women aged 36-47 years old were more vulnerable during post-oocyte retrieve period. Our results suggested air pollution exposure during preantral-antral follicle transition stage was a note-worthy challenge to conceive among females receiving IVF.

Spatial Heterogeneity of Winter Wheat Yield and Its Determinants in the Yellow River Delta, China

Understanding spatial differences of crop yields and quantitatively exploring the relationship between crop yields and influencing factors are of great significance in increasing regional crop yields, promoting sustainable development of regional agriculture and ensuring regional food security. This study investigates spatial heterogeneity of winter wheat yield and its determinants in the Yellow River Delta (YRD) region. The spatial pattern of winter wheat in 2015 was mapped through time series similarity analysis. Winter wheat yield was estimated by integrating phenological information into yield model, and cross-validation was performed using actual yield data. The geographical detector method was used to analyze determinants influencing winter wheat yield. This study concluded that the overall classification accuracy for winter wheat is 88.09%. The estimated yield agreed with actual yield, with R2 value of 0.74 and root mean square error (RMSE) of 1.02 t ha−1. Cumulative temperature, soil salinity and their interactions were key determinants affecting winter wheat yield. Several measures are recommended to ensure sustainable crop production in the YRD region, including improving irrigation and drainage systems to reduce soil salinity, selecting salt-tolerant winter wheat varieties, and improving agronomy techniques to extend effective cumulative temperature.