Trends in atmospheric particles and their light extinction performance between 1980 and 2015 in Beijing, China

Impact of lifetime air pollution exposure patterns on the risk of chronic disease

Long-term exposure to air pollution can lead to cardiovascular disease, metabolic syndrome, and chronic respiratory disease. However, from a lifetime perspective, the critical period of air pollution exposure in terms of health risk is unknown. This study aimed to evaluate the impact of air pollution exposure at different life stages. The study participants were recruited from community centers in Northern Taiwan between October 2018 and April 2021. Their annual averages for fine particulate matter (PM2.5) exposure were derived from a national visibility database. Lifetime PM2.5 exposures were determined using residential address information and were separated into three stages (<20, 20-40, and >40 years). We employed exponentially weighted moving averages, applying different weights to the aforementioned life stages to simulate various weighting distribution patterns. Regression models were implemented to examine associations between weighting distributions and disease risk. We applied a random forest model to compare the relative importance of the three exposure life stages. We also compared model performance by evaluating the accuracy and F1 scores (the harmonic mean of precision and recall) of late-stage (>40 years) and lifetime exposure models. Models with 89% weighting on late-stage exposure showed significant associations between PM_2.5 exposure and metabolic syndrome, hypertension, diabetes, and cardiovascular disease, but not gout or osteoarthritis. Lifetime exposure models showed higher precision, accuracy, and F1 scores for metabolic syndrome, hypertension, diabetes, and cardiovascular disease, whereas late-stage models showed lower performance metrics for these outcomes. We conclude that exposure to high-level PM_2.5 after 40 years of age may increase the risk of metabolic syndrome, hypertension, diabetes, and cardiovascular disease. However, models considering lifetime exposure showed higher precision, accuracy, and F1 scores and lower equal error rates than models incorporating only late-stage exposures. Future studies regarding long-term air pollution modelling are required considering lifelong exposure pattern. .¹.

Vertical profiles of particle light extinction coefficient in the lower troposphere in Shanghai in winter based on tethered airship measurements

A cavity attenuated phase shift single scattering albedo monitor was set up on a tethered airship platform to study the vertical profiles of particle light extinction coefficient (b_ext) in the lower troposphere (<1000 m) in Shanghai during 12-29 December 2015. Clear transition heights (THs) for vertical profiles of b_ext during the polluted days (PM_2.5 > 75 μg m^-3) were observed below 1000 m. The vertical differences of b_ext were highly dynamic as the vertical variation in b_ext was significant by as much as 605 Mm^-1. The TH was observed mostly at about 100-200 m, and 450-650 m during night and daytime, respectively, and was in a wide range of ∼50-900 m during 15:00-22:00 due to the low boundary layer and/or the transport of pollutants. In particular, the TH was consistently below 500 m throughout the day during highly polluted haze episodes, highlighting the important role of a stagnant atmosphere situation for high concentrations of PM_2.5. The vertical distribution of b_ext did not have a constant rule with respect to relative humidity and wind. Sometimes, peak values of b_ext at ∼350 m and 500 m during daytime were caused by enhanced regional transport. During stagnant and highly polluted situations or well-mixed clean days, b_ext was usually uniformly distributed below and above the TH, respectively, although b_ext was much smaller above the TH. For other situations, local emissions, pollutant transport, and the physical and chemical characteristics of aerosols resulted in highly dynamic vertical profiles of b_ext.

Long-term validation of MODIS C6 and C6.1 Dark Target aerosol products over China using CARSNET and AERONET

This study provided a comprehensive evaluation of the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 006 (C6) and 061 (C6.1) Dark Target (DT) 10 km aerosol optical depth (AOD) over China during 2002-2014. Considering that sparse Aerosol Robotic Network (AERONET) sites are available in China, 18 sites from China Aerosol Remote Sensing Network (CARSNET) were also used to conduct this validation. The results showed that C6.1 DT outperform C6 with 59.03% of the retrievals falling within the expected error (EE) compared to C6 (54.94%). Meanwhile, C6.1 DT achieved a reduced RMSE of 0.171, a higher R of 0.901 and a bias closer to 0 relative to C6 (RMSE: 0.185; R: 0.890). When the validation was conducted over different underlying surfaces, C6 DT overestimated AOD by 19.8%, with only 45.01% of the retrievals within the EE over urban sites, whereas C6.1 showed clear improvements, with 11.8% more data falling within the EE. Hardly any improvement was observed in C6.1 over forest, cropland, and grassland sites. The C6.1 DT exhibited more significant improvements over Beijing area and northern China than southern China. The highest retrieval accuracy of 61.05% among the four Beijing sites was achieved at Beijing_CARSNET, but the improvements were lower than other Beijing sites. The extent of the improvements was positively correlated with the percentage of urban pixels over the sites in Beijing and northern China in terms of the retrieval accuracy. Moreover, C6.1 DT had a little effect on improvements over southern China and showed reduced collocation over coastal cities.

Short-term PM10 and emergency department admissions for selective cardiovascular and respiratory diseases in Beijing, China

BACKGROUND

Few studies have explored PM₁₀'s connection with specific respiratory and cardiovascular emergency department admissions (EDAs). This study aimed to examine the overall effects of PM₁₀ on EDAs for cardiovascular and respiratory diseases, including specifically, cerebrovascular events (CVE), ischemic heart disease (IHD), arrhythmia, heart failure (HF), upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), chronic obstructive pulmonary disease (COPD) and asthma.

METHODS

We collected daily data for EDAs from the 10 largest hospitals in Beijing, between January 2013 and December 2013 as well as daily measurements of PM₁₀ from 17 stations in Beijing. The generalized-additive model was utilized to evaluate the associations between daily PM₁₀ and cardio-pulmonary disease admissions. Differences in gender, age, and season groups were also examined by models. Relative risks (RR) with 95% confidence interval (CI) were calculated based on subtype, age, gender and seasonal groups. In all, there were approximately 56,212 cardiovascular and 92,464 respiratory emergency admissions presented in this study.

RESULTS

The largest estimate effects in EDAs of total cardiovascular disease, CVE, IHD, total respiratory diseases, URTI, LRTI and COPD were found for PM₁₀ at day 4 (accumulative) moving average, were 0.29% (95% CI:0.12%, 0.46%), 0.36% (95% CI:0.11%, 0.61%), 0.68% (95% CI:0.25%, 1.10%), 0.34% (95% CI:0.22%, 0.47%), 0.35% (95% CI:0.18%, 0.51%), 0.34% (95% CI:0.14%, 0.55%), 2.75% (95% CI:1.38%, 4.12%) respectively. In two-pollutant models and full-pollutant model modified confounding factors, the positive correlation remained unchanged. The elderly (age ≥ 65 years) and male subjects were more susceptible to specific respiratory diseases. PM₁₀'s impact on EDAs for HF was found higher during the hot season however, EDAs for COPD peaked during the cold season.

CONCLUSION

The study markedly informed that PM₁₀ pollution was strongly associated with EDAs for cardio-pulmonary diseases. The effects of PM₁₀ pollution on COPD and heart failure EDAs were clearly determined by seasonal-temperatures.

The Relationship Between Air Pollution and Lung Cancer in Nonsmokers in Taiwan

INTRODUCTION

For never-smokers (smoked <100 lifetime cigarettes), lung cancer (LC) has emerged as an important issue. We aimed to investigate the effects of prevalence changes in tobacco smoking and particulate matter (PM) 2.5 (PM_2.5) levels on LC in Taiwan, in relation to contrasting PM_2.5 levels, between Northern Taiwan (NT) and Southern Taiwan (ST).

METHODS

We reviewed 371,084 patients with LC to assess smoking prevalence and correlations between the incidence of adenocarcinoma lung cancer (AdLC) and non-AdLC. Two subsets were selected to assess different AdLC stage trends and the effect of PM_2.5 on survival of patients with AdLC.

RESULTS

From 1995 to 2015, the proportion of male adult ever-smokers decreased from 59.4% to 29.9% whereas the female smoking rate remained low (3.2% to 5.3%). AdLC incidence in males and females increased from 9.06 to 23.25 and 7.05 to 24.22 per 100,000 population, respectively. Since 1993, atmospheric visibility in NT improved (from 7.6 to 11.5 km), but deteriorated in ST (from 16.3 to 4.2 km). The annual percent change in AdLC stages IB to IV was 0.3% since 2009 (95% confidence interval [CI]: -1.9%-2.6%) in NT, and 4.6% since 2007 (95% CI: 3.3%-5.8%) in ST; 53% patients with LC had never smoked. Five-year survival rates for never-smokers, those with EGFR wild-type genes, and female patients with AdLC were 12.6% in NT and 4.5% in ST (hazard ratio: 0.79, 95% CI: 0.70-0.90).

CONCLUSIONS

In Taiwan, greater than 50% of patients with LC had never smoked. PM_2.5 level changes can affect AdLC incidence and patient survival.