Spatial Characteristics and Regional Transmission Analysis of PM2.5 Pollution in Northeast China, 2016-2020

Estimating the spatiotemporal distribution of PM2.5 concentrations in Tianjin during the Chinese Spring Festival: Impact of fireworks ban

SETTING

off fireworks during the Spring Festival (SF) is a traditional practice in China. However, because of its environmental impact, the Chinese government has banned this practice completely. Existing evaluations of the effectiveness of firework prohibition policies (FPPs) lack spatiotemporal perspectives, making it difficult to comprehensively assess their effects on air quality. Consequently, this study used remote sensing technology based on aerosol optical depth and multiple variables, compared nine statistical learning methods, and selected the optimal model, transformer, to estimate daily spatiotemporal continuous PM2.5 concentration datasets for Tianjin from 2016 to 2020. The overall model accuracy reached a root mean square error of 15.30 μg/m³, a mean absolute error of 9.55 μg/m³, a mean absolute percentage error of 21.07%, and an R2 of 0.88. Subsequently, we analysed the variations in PM2.5 concentrations from three time dimensions-the entire year, winter, and SF periods-to exclude the impact of interannual variations on the experimental results. Additionally, we quantitatively estimated firework-specific PM2.5 concentrations based on time-series forecasting. The results showed that during the three years following the implementation of the FPPs, firework-specific PM2.5 concentrations decreased by 52.70%, 49.76%, and 86.90%, respectively, compared to the year before the implementation of the FPPs. Spatially, the central urban area and industrial zones are more affected by FPPs than the suburbs. However, daily variations of PM2.5 concentrations during the SF showed that high concentrations of PM2.5 produced in a short period will return to normal rapidly and will not cause lasting effects. Therefore, the management of fireworks needs to consider both environmental protection and the public's emotional attachment to traditional customs, rather than simply imposing a blanket ban on fireworks. We advocate improving firework policies in four aspects-production, sales, supervision, and control-to promote sustainable development of the ecological environment and human society.

Impact of surface ultraviolet radiation intensity on hospital admissions for ischemic and hemorrhagic stroke: A large-scale database study using distributed lag nonlinear analysis, 2015-2022, in Harbin, China

OBJECTIVES

Our aim is to evaluate the impact of surface ultraviolet radiation intensity on hospital admissions for stroke and to compare the correlation and differences among different subtypes of strokes.

MATERIALS AND METHODS

We collected daily data on surface ultraviolet radiation intensity, temperature, air pollution, and hospital admissions for stroke in Harbin from 2015 to 2022. Using a distributed lag non-linear model, we determined the correlation between daily surface ultraviolet radiation intensity and the stroke admission rate. Relative risks (RR) with 95% confidence intervals (CI) and attributable fractions (AF) with 95% CI were calculated based on stroke subtypes, gender, and age groups.

RESULTS

A total of 132,952 hospitalized stroke cases (including hemorrhagic and ischemic strokes) were included in the study. We assessed the non-linear effects of ultraviolet intensity on hospitalized patients with ischemic and hemorrhagic strokes. Compared to the maximum morbidity benchmark ultraviolet intensity (19.2 × 10^5 for ischemic stroke and 20.25 for hemorrhagic stroke), over the 0-10 day lag period, the RR for extreme low radiation (1st percentile) was 0.86 (95% CI: 0.77, 0.96), and the RR for extreme high radiation (99th percentile) was 0.86 (95% CI: 0.77, 0.96). In summary, -4.842% (95% CI: -7.721%, -2.167%) and -1.668% (95% CI: -3.061%, -0.33%) of ischemic strokes were attributed to extreme low radiation intensity with a lag of 0 to 10 days and extreme high radiation intensity with a lag of 0 to 5 days, respectively. The reduction in stroke hospitalization rates due to low or high ultraviolet intensity was more pronounced in females and younger individuals compared to males and older individuals. None of the mentioned ultraviolet intensity intensities and lag days had a statistically significant impact on hemorrhagic stroke.

CONCLUSIONS

Our study fundamentally suggests that both lower and higher levels of surface ultraviolet radiation intensity in Harbin, China, contribute to a reduced incidence of ischemic stroke, with this effect lasting approximately 10 days. This finding holds significant potential for public health and clinical relevance.

Spatial and Temporal Distribution Characteristics and Cytotoxicity of Atmospheric PM2.5 in the Main Urban Area of Lanzhou City

PM2.5, as one of the most harmful pollutant in the atmospheric environment and population health, has received much attention. We monitored PM2.5 levels at five sampling sites in the Lanzhou City and collected PM2.5 particles from two representative sites for cytotoxicity experiment. The cytotoxicity of PM2.5 samples on A549 cells and migration ability of the cells were respectively detected by Cell Counting kit-8 (CCK-8) assay and scratch assay. We detected the levels of cellular inflammatory factors and oxidative damage-related biochemical indexes. RT-qPCR was used to detect the mRNA levels of NF-κB and epithelial-mesenchymal transition (EMT)-related genes. We found that the Lanlian Hotel station had the highest PM2.5 annual average concentration. The annual average concentration change curve of PM2.5 showed a roughly "U"-shaped distribution during the whole sampling period. The cytotoxicity experiment showed the viability of A549 cells decreased and the scratch healing rate increased in the 200 and 400 μg/mL PM2.5-treated groups. We also found 400 μg/mL PM2.5 induced changes in the mRNA levels of NF-κB and EMT-related genes, the mRNA levels of IKK-α, NIK, and NF-κB in the 400 μg/mL PM2.5 group were higher than those in the control group. The mRNA levels of E-cadherin decreased and α-SMA increased in the 400 μg/mL PM2.5 groups, and the mRNA levels of Fibronectin increased in the 400 μg/mL PM2.5 groups. Moreover, we found hydroxyl radical scavenging ability and T-AOC levels were lower, and LPO levels were higher in the 200 and 400 μg/mL PM2.5 groups, and the SOD activity of cells in the 400 µg/mL PM2.5 group decreased. And compared with the control group, the levels of TNF-α were higher in the 200 and 400 μg/mL PM2.5 groups and the levels of IL-1 were higher in the 400 μg/mL PM2.5 group. The results indicated that the cytotoxicity of atmospheric PM2.5 was related to oxidative damage, inflammatory response, NF-κB activity and EMT.

Identifying interactions among air pollutant emissions on diabetes prevalence in Northeast China using a complex network

BACKGROUND

Low air quality related to ambient air pollution is the largest environmental risk to health worldwide. Interactions between air pollution emissions may affect associations between air pollution exposure and chronic diseases. Therefore, this study aimed to quantify interactions among air pollution emissions and assess their effects on the association between air pollution and diabetes.

METHODS

After constructing long-term emission networks for six air pollutants based on data collected from routine monitoring stations in Northeast China, a mutual information network was used to quantify interactions among air pollution emissions. Multiple linear regression analysis was then used to explore the influence of emission interactions on the association between air pollution exposure and the prevalence of diabetes based on data reported from the Northeast Natural Cohort Study in China.

RESULTS

Complex network analysis detected three major emission sources in Northeast China located in Shenyang and Changchun. The effects of particulate matter (PM2.5 and PM10) and ground-level ozone (O3) emissions were limited to certain communities but could spread to other communities through emissions in Inner Mongolia. Emissions of sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO) significantly influenced other communities. These results indicated that air pollutants in different geographic areas can interact directly or indirectly. Adjusting for interactions between emissions changed associations between air pollution emissions and diabetes prevalence, especially for PM2.5, NO2, and CO.

CONCLUSIONS

Complex network analysis is suitable for quantifying interactions among air pollution emissions and suggests that the effects of PM2.5 and NO2 emissions on health outcomes may have been overestimated in previous population studies while those of CO may have been underestimated. Further studies examining associations between air pollution and chronic diseases should consider controlling for the effects of interactions among pollution emissions.

Spatial interpolation of regional PM2.5 concentrations in China during COVID-19 incorporating multivariate data

During specific periods when the PM_2.5 variation pattern is unusual, such as during the coronavirus disease 2019 (COVID-19) outbreak, epidemic PM_2.5 regional interpolation models have been relatively little investigated, and little consideration has been given to the residuals of optimized models and changes in model interpolation accuracy for the PM_2.5 concentration under the influence of epidemic phenomena. Therefore, this paper mainly introduces four interpolation methods (kriging, empirical Bayesian kriging, tensor spline function and complete regular spline function), constructs geographically weighted regression (GWR) models of the PM_2.5 concentration in Chinese regions for the periods from January-June 2019 and January-June 2020 by considering multiple factors, and optimizes the GWR regression residuals using these four interpolation methods, thus achieving the purpose of enhancing the model accuracy. The PM_2.5 concentrations in many regions of China showed a downward trend during the same period before and after the COVID-19 outbreak. Atmospheric pollutants, meteorological factors, elevation, zenith wet delay (ZWD), normalized difference vegetation index (NDVI) and population maintained a certain relationship with the PM_2.5 concentration in terms of linear spatial relationships, which could explain why the PM_2.5 concentration changed to a certain extent. By evaluating the model accuracy from two perspectives, i.e., the overall interpolation effect and the validation set interpolation effect, the results showed that all four interpolation methods could improve the numerical accuracy of GWR to different degrees, among which the tensor spline function and the fully regular spline function achieved the most stable effect on the correction of GWR residuals, followed by kriging and empirical Bayesian kriging.

Impact of Air Pollution on the Ocular Surface and Tear Cytokine Levels: A Multicenter Prospective Cohort Study

Purpose

To assess air pollution-induced changes on ocular surface and tear cytokine levels.

Methods

As a prospective multicenter cohort study, 387 dry eye disease (DED) participants were recruited from five provinces in China and underwent measurements of ocular surface disease index (OSDI), Schirmer’s I test (ST), tear meniscus height (TMH), tear film break-up time (TBUT), corneal fluorescein staining (CFS), meibomian gland (MG) function, and tear cytokines. The associations between ocular surface parameters and exposure to particulate matter (PM), ozone (O₃), nitrogen dioxide (NO₂), and sulfur dioxide (SO₂) for 1 day, 1 week, and 1 month before the examination were analyzed in single- and multi-pollutant models adjusted for confounding factors.

Results

In the multi-pollutant model, the OSDI score was positively correlated with PM with diameter ≤2.5 μm (PM_2.5), O₃, and SO₂ exposure [PM_2.5: β (1 week/month) = 0.229 (95% confidence interval (CI): 0.035–0.424)/0.211 (95% CI: 0.160–0.583); O₃: β (1 day/week/month) = 0.403 (95% CI: 0.229–0.523)/0.471 (95% CI: 0.252–0.693)/0.468 (95% CI: 0.215–0.732); SO₂: β (1 day/week) = 0.437 (95% CI: 0.193–0.680)/0.470 (95% CI: 0.040–0.901)]. Tear secretion was negatively correlated with O₃ and NO₂ exposures but positively correlated with PM_2.5 levels. Air pollutants were negatively correlated with TBUT and positively related with CFS score. Besides SO₂, all other pollutants were associated with aggravated MG dysfunction (MG expression, secretion, and loss) and tear cytokines increasement, such as PM_2.5 and interleukin-8 (IL-8) [β (1 day) = 0.016 (95% CI: 0.003–0.029)], PM with diameter ≤10 μm (PM₁₀) and IL-6 [β (1 day) = 0.019 (95% CI: 0.006–0.033)], NO₂ and IL-6 [β (1 month) = 0.045 (95% CI: 0.018–0.072)], among others. The effects of air pollutants on DED symptoms/signs, MG functions and tear cytokines peaked within 1 week, 1 month, and 1 day, respectively.

Conclusion

Increased PM_2.5, O₃, and SO₂ exposures caused ocular discomfort and damage with tear film instability. PM₁₀ exposure led to tear film instability and ocular injury. PM, O₃, and NO₂ exposures aggravated MG dysfunction and upregulated tear cytokine levels. Therefore, each air pollutant may influence DED via different mechanisms within different time windows.