Health burden attributable to ambient PM2.5 in China

Association between Exposure to Ambient Air Particulates and Metabolic Syndrome Components in a Saudi Arabian Population

Recent epidemiological evidence suggests that exposure to particulates may be a factor in the etiology of metabolic syndrome (MetS). In this novel study, we investigated the relationship between particulate levels and prevalence of MetS component abnormalities (hypertension, hyperglycemia, obesity) in a recruited cohort (N = 2025) in Jeddah, Saudi Arabia. We observed significant associations between a 10 μg/m³ increase in PM_2.5 and increased risks for MetS (Risk Ratio (RR): 1.12; 95% Confidence Interval (CI): 1.06-1.19), hyperglycemia (RR: 1.08; 95% CI: 1.03-1.14), and hypertension (RR: 1.09; 95% CI: 1.04-1.14). PM_2.5 from soil/road dust was found to be associated with hyperglycemia (RR: 1.12; 95% CI: 1.06-1.19) and hypertension (RR: 1.11; 95% CI: 1.05-1.18), while PM_2.5 from traffic was associated with hyperglycemia (RR: 1.33; 95% CI: 1.05-1.71). We did not observe any health associations with source-specific mass exposures. Our findings suggest that exposure to specific elemental components of PM_2.5, especially Ni, may contribute to the development of cardiometabolic disorders.

India Is Overtaking China as the World's Largest Emitter of Anthropogenic Sulfur Dioxide

Severe haze is a major public health concern in China and India. Both countries rely heavily on coal for energy, and sulfur dioxide (SO2) emitted from coal-fired power plants and industry is a major pollutant contributing to their air quality problems. Timely, accurate information on SO2 sources is a required input to air quality models for pollution prediction and mitigation. However, such information has been difficult to obtain for these two countries, as fast-paced changes in economy and environmental regulations have often led to unforeseen emission changes. Here we use satellite observations to show that China and India are on opposite trajectories for sulfurous pollution. Since 2007, emissions in China have declined by 75% while those in India have increased by 50%. With these changes, India is now surpassing China as the world's largest emitter of anthropogenic SO2. This finding, not predicted by emission scenarios, suggests effective SO2 control in China and lack thereof in India. Despite this, haze remains severe in China, indicating the importance of reducing emissions of other pollutants. In India, ~33 million people now live in areas with substantial SO2 pollution. Continued growth in emissions will adversely affect more people and further exacerbate morbidity and mortality.

Capturing PM2.5 Emissions from 3D Printing via Nanofiber-based Air Filter

This study investigated the feasibility of using polycaprolactone (PCL) nanofiber-based air filters to capture PM2.5 particles emitted from fused deposition modeling (FDM) 3D printing. Generation and aggregation of emitted particles were investigated under different testing environments. The results show that: (1) the PCL nanofiber membranes are capable of capturing particle emissions from 3D printing, (2) relative humidity plays a signification role in aggregation of the captured particles, (3) generation and aggregation of particles from 3D printing can be divided into four stages: the PM2.5 concentration and particles size increase slowly (first stage), small particles are continuously generated and their concentration increases rapidly (second stage), small particles aggregate into more large particles and the growth of concentration slows down (third stage), the PM2.5 concentration and particle aggregation sizes increase rapidly (fourth stage), and (4) the ultrafine particles denoted as "building unit" act as the fundamentals of the aggregated particles. This work has tremendous implications in providing measures for controlling the particle emissions from 3D printing, which would facilitate the extensive application of 3D printing. In addition, this study provides a potential application scenario for nanofiber-based air filters other than laboratory theoretical investigation.

Air pollution in China: Status and spatiotemporal variations

In recent years, China has experienced severe and persistent air pollution associated with rapid urbanization and climate change. Three years' time series (January 2014 to December 2016) concentrations data of air pollutants including particulate matter (PM_2.5 and PM₁₀) and gaseous pollutants (SO₂, NO₂, CO, and O₃) from over 1300 national air quality monitoring sites were studied to understand the severity of China's air pollution. In 2014 (2015, 2016), annual population-weighted-average (PWA) values in China were 65.8 (55.0, 50.7) μg m^-3 for PM_2.5, 107.8 (91.1, 85.7) μg m^-3 for PM₁₀, 54.8 (56.2, 57.2) μg m^-3 for O₃_8 h, 39.6 (33.3, 33.4) μg m^-3 for NO₂, 34.1 (26, 21.9) μg m^-3 for SO₂, 1.2 (1.1, 1.1) mg m^-3 for CO, and 0.60 (0.59, 0.58) for PM_2.5/PM₁₀, respectively. In 2014 (2015, 2016), 7% (14%, 19%), 17% (27%, 34%), 51% (67%, 70%) and 88% (97%, 98%) of the population in China lived in areas that meet the level of annual PM_2.5, PM₁₀, NO₂, and SO₂ standard metrics from Chinese Ambient Air Quality Standards-Grade II. The annual PWA concentrations of PM_2.5, PM₁₀, O₃_8 h, NO₂, SO₂, CO in the Northern China are about 40.4%, 58.9%, 5.9%, 24.6%, 96.7%, and 38.1% higher than those in Southern China, respectively. Though the air quality has been improving recent years, PM_2.5 pollution in wintertime is worsening, especially in the Northern China. The complex air pollution caused by PM and O₃ (the third frequent major pollutant) is an emerging problem that threatens the public health, especially in Chinese mega-city clusters. NOx controls were more beneficial than SO₂ controls for improvement of annual PM air quality in the northern China, central, and southwest regions. Future epidemiologic studies are urgently required to estimate the health impacts associated with multi-pollutants exposure, and revise more scientific air quality index standards.

Stroke Mortality Attributable to Ambient Particulate Matter Pollution from 1990 to 2015 in China: An Age-Period-Cohort and Spatial Autocorrelation Analysis

In this study, we analyzed the temporal and spatial variations of stroke mortality attributable to ambient particulate matter pollution (stroke mortality-PM_2.5) in China from 1990 to 2015. Data were collected from the Global Burden of Disease (GBD) 2015 study and analyzed by an age-period-cohort model (APC) with an intrinsic estimator (IE) algorithm, as well as spatial autocorrelation based on the Geographic Information System. Based on APC analysis with the IE method, stroke mortality-PM_2.5 increased exponentially with age, its relative risk reaching 42.85 (95% CI: 28.79, 63.43) in the 75–79 age group. The period effects showed a reversed V-shape and its highest relative risk was 1.22 (95% CI: 1.15, 1.27) in 2005. The cohort effects decreased monotonically from 1915–1919 to 1990–1994. The change rate fluctuated from 1920–1924 to 1990–1994, including three accelerating and three decelerating decreases. There was a positive spatial autocorrelation in stroke mortality-PM_2.5 from 1990 to 2015. Hot-spots moved from the northeastern areas to the middle and southwestern areas, whereas cold-spots lay mostly in coastal provinces. Besides the aging process in recent years, stroke mortality-PM_2.5 had significantly declined from 2005 to 2015 due to socio-economic and healthcare development. Stroke mortality-PM_2.5 varied substantially among different regions, and cost-effective prevention and control should be implemented more in the middle and southwestern areas of China.