Characteristics of Fine Particulate Matter (PM2.5) over Urban, Suburban, and Rural Areas of Hong Kong

Association of smoking cessation with airflow obstruction in workers with silicosis: A cohort study

BACKGROUND

Studies in general population reported a positive association between tobacco smoking and airflow obstruction (AFO), a hallmark of chronic obstructive pulmonary disease (COPD). However, this attempt was less addressed in silica dust-exposed workers.

METHODS

This retrospective cohort study consisted of 4481 silicotic workers attending the Pneumoconiosis Clinic during 1981-2019. The lifelong work history and smoking habits of these workers were extracted from medical records. Spirometry was carried out at the diagnosis of silicosis (n = 4177) and reperformed after an average of 9.4 years of follow-up (n = 2648). AFO was defined as forced expiratory volume in one second (FEV1)/force vital capacity (FVC) less than lower limit of normal (LLN). The association of AFO with smoking status was determined using multivariate logistics regression, and the effect of smoking cessation on the development of AFO was evaluated Cox regression.

RESULTS

Smoking was significantly associated with AFO (current smokers: OR = 1.92, 95% CI 1.51-2.44; former smokers: OR = 2.09, 95% CI 1.65-2.66). The risk of AFO significantly increased in the first 3 years of quitting smoking (OR = 1.23, 95% CI 1.02-1.47) but decreased afterwards with increasing years of cessation. Smoking cessation reduced the risk of developing AFO no matter before or after the confirmation of silicosis (pre-silicosis cessation: HR = 0.58, 95% CI 0.46-0.74; post-silicosis cessation: HR = 0.62, 95% CI 0.48-0.79).

CONCLUSIONS

Smoking cessation significantly reduced the risk of AFO in the workers with silicosis, although the health benefit was not observed until 3 years of abstinence. These findings highlight the importance of early and long-term smoking cessation among silicotic or silica dust-exposed workers.

The Impact of the Numbers of Monitoring Stations on the National and Regional Air Quality Assessment in China During 2013-18

China national air quality monitoring network has become the core data source for air quality assessment and management in China. However, during network construction, the significant change in numbers of monitoring sites with time is easily ignored, which brings uncertainty to air quality assessments. This study aims to analyze the impact of change in numbers of stations on national and regional air quality assessments in China during 2013-18. The results indicate that the change in numbers of stations has different impacts on fine particulate matter (PM2.5) and ozone concentration assessments. The increasing number of sites makes the estimated national and regional PM2.5 concentration slightly lower by 0.6-2.2 µg m-3 and 1.4-6.0 µg m-3 respectively from 2013 to 2018. The main reason is that over time, the monitoring network expands from the urban centers to the suburban areas with low population densities and pollutant emissions. For ozone, the increasing number of stations affects the long-term trends of the estimated concentration, especially the national trends, which changed from a slight upward trend to a downward trend in 2014-15. Besides, the impact of the increasing number of sites on ozone assessment exhibits a seasonal difference at the 0.05 significance level in that the added sites make the estimated concentration higher in winter and lower in summer. These results suggest that the change in numbers of monitoring sites is an important uncertainty factor in national and regional air quality assessments, that needs to be considered in long-term concentration assessment, trend analysis, and trend driving force analysis.

Long-term spatiotemporal trends in aerosol optical depth and its relationship with enhanced vegetation index and meteorological parameters over South Asia

Satellite-based aerosol optical depth (AOD) is columnar light extinction by aerosol absorption and scattering and has become the most important variable for the assessment of the spatiotemporal distribution of aerosols at a regional and global level. In this paper, we have used AOD observations of multiangle imaging spectroradiometer (MISR) from September 2002 to May 2017, moderate resolution imaging spectroradiometer (MODIS) from September 2002 to December 2020, and sea-viewing wide field-of-view sensor (SeaWiFS) from September 2002 to December 2010 over South Asia. We have observed the association of AOD with enhanced vegetation index (EVI) and meteorological variables (temperature (TEMP), wind speed (WS), and relative humidity (RH)) acquired from Giovanni during the period September 2002-December 2020. The satellite observations of Terra-, MISR-, and SeaWiFS-AOD were also compared with Aqua-AOD. The findings show that AOD in eastern Pakistan is higher than in the western Pakistan due to increase in population density and biomass burning. Mean annual peak AOD (˃ 0.7) has been observed over the IGB region because of the significant increase in economical, industrial, and agricultural activities while AOD of ˃ 0.6 is observed over Bangladesh. The lowest mean annual AOD of ˂ 0.3 is observed over northeastern Afghanistan, western Nepal, and Bhutan whereas the AOD of 0.3 is seen over Sri Lanka. The highest seasonal mean AOD of 0.8 has been seen over Bihar, India, and AOD of ~ 0.7 is observed over Bangladesh while the lowest AOD is observed over Afghanistan, Sri Lanka, Nepal, and Bhutan during the winter season. However, the mean AOD over eastern Pakistan is maximum in both monsoon and post-monsoon season but relatively low in pre-monsoon and winter. The highest positive seasonal AOD anomalies were observed over South Asia in winter season followed by post-monsoon, pre-monsoon, and least being monsoon. The higher mean AOD anomaly value is found to be 0.2 over eastern Pakistan and western India. In northeastern Pakistan and central India, AOD and RH are positively correlated (r ˃ 0.54) while negatively correlated over Afghanistan, southwestern region of Pakistan, eastern India, Nepal, Bhutan, and Bangladesh. AOD is negatively correlated (r =  ~  - 0.3) with EVI over eastern Pakistan and western India. The highest correlation coefficient (r) obtained among Terra and Aqua is 0.97, MISR and Aqua is 0.93, and SeaWiFS and Aqua is 0.58 over South Asia.

Spatiotemporal Variation and Influencing Factors of TSP and Anions in Coastal Atmosphere of Zhanjiang City, China

Water-soluble anions and suspended fine particles have negative impacts on ecosystems and human health, which is a current research hotspot. In this study, coastal suburb, coastal urban area, coastal tourist area, and coastal industrial area were explored to study the spatiotemporal variation and influencing factors of water-soluble anions and total suspended particles (TSP) in Zhanjiang atmosphere. In addition, on-site monitoring, laboratory testing, and analysis were used to identify the difference of each pollutant component at the sampling stations. The results showed that the average concentrations of Cl⁻, NO₃⁻, SO₄²⁻, PO₄³⁻, and TSP were 29.8 μg/m³, 19.6 μg/m³, 45.6 μg/m³, 13.5 μg/m³, and 0.28 mg/m³, respectively. The concentration of Cl⁻, NO₃⁻, PO₄³⁻, and atmospheric TSP were the highest in coastal urban area, while the concentration of SO₄²⁻ was the highest in coastal industrial area. Moreover, there were significantly seasonal differences in the concentration of various pollutants (p < 0.05). Cl⁻ and SO₄²⁻ were high in summer, and NO₃⁻ and TSP were high in winter. Cl⁻, SO₄²⁻, PO₄³⁻, and TSP had significant correlations with meteorological elements (temperature, relative humidity, atmospheric pressure, and wind speed). Besides, the results showed the areas with the most serious air pollution were coastal urban area and coastal industrial area. Moreover, the exhaust emissions from vehicles, urban enterprise emissions, and seawater evaporation were responsible for the serious air pollution in coastal urban area. It provided baseline information for the coastal atmospheric environment quality in Zhanjiang coastal city, which was critical to the mitigation strategies for the emission sources of air pollutants in the future.

Identification of ozone sensitivity for NO2 and secondary HCHO based on MAX-DOAS measurements in northeast China

In this study, tropospheric formaldehyde (HCHO) vertical column densities (VCDs) were measured using multi-axis differential optical absorption spectroscopy (MAX-DOAS) from January to November 2019 in Shenyang, Northeast China. The maximum HCHO VCD value appeared in the summer (1.74 × 10¹⁶ molec/cm²), due to increased photo-oxidation of volatile organic compounds (VOCs). HCHO concentrations increased from 08:00 and peaked near 13:00, which was mainly attributed to the increased release of isoprene from plants and enhanced photolysis at noon. The HCHO VCDs observed by MAX-DOAS and OMI have a good correlation coefficient (R) of 0.78, and the contributions from primary and secondary HCHO sources were distinguished by the multi-linear regression model. The anthropogenic emissions showed unobvious seasonal variations, and the primary HCHO was relatively stable in Shenyang. Secondary HCHO contributed 82.62%, 83.90%, 78.90%, and 41.53% to the total measured ambient HCHO during the winter, spring, summer, and autumn, respectively. We also found a good correlation (R = 0.78) between enhanced vegetation index (EVI) and HCHO VCDs, indicating that the oxidation of biogenic volatile organic compounds (BVOCs) was the main source of HCHO. The ratio of secondary HCHO to nitrogen dioxide (NO₂) was used as the tracer to analyze O₃-NO_x-VOC sensitivities. We found that the VOC-limited, VOC-NO_x-limited, and NO_x-limited regimes made up 93.67%, 6.23%, 0.11% of the overall measurements, respectively. In addition, summertime ozone (O₃) sensitivity changed from VOC-limited in the morning to VOC-NO_x-limited in the afternoon. Therefore, this study offers information on HCHO sources and corresponding O₃ production sensitivities to support strategic management decisions.

Particulate matter (PM2.5) and diseases: an autoregressive distributed lag (ARDL) technique

Air pollution can be attributed to the reduction in visibility, less agricultural activity, more health issues, and long-term destruction to infrastructure. This paper aimed to examine the validity of association among the Particulate matter (PM_2.5) and number of acute upper respiratory infection (ARI) and Asthma (AS) patients using an autoregressive distributed lag (ARDL) approach. This ARDL model study was conducted in Lahore, Pakistan. We used monthly data of ARI and AS patients acquired from Directorate General Health Services Punjab and PM_2.5 from Air Visual-IQAir during the period January 2018-August 2019. ARDL bound testing technique was used to investigate the association between number of AS, ARI patients and PM_2.5. In the short run, the PM_2.5 has substantial positive impact on number of AS patients in Lahore. The values of short-run coefficient depicts that the association between PM_2.5 and ARI patients is stronger than AS. The effect of PM_2.5 on number of patients in short term is more than that in the long-term. For both AS and ARI, in the long run, PM_2.5 has negative impact on number of patients.

Reduction of surface radiative forcing observed from remote sensing data during global COVID-19 lockdown

The calamity of the COVID-19 pandemic during the early half of 2020 not only caused a huge physical and economic loss but altered the social behavior of the whole world. The social and economic stagnation imposed in many countries and served as a major cause of perturbation in atmospheric composition. This paper utilized the relation between atmospheric composition and surface radiation and analyzed the impact of global COVID-19 lockdown on land surface solar and thermal radiation. Top of atmosphere (TOA) and surface radiation are obtained from the Clouds and Earth's Radiant Energy System (CERES) and European Reanalysis product (ERA5) reanalysis product. Aerosol Optical Depth (AOD) is obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) while Nitrogen dioxide (NO₂)_, and sulfur dioxide (SO₂) are obtained from Ozone Monitoring Instrument (OMI). Observations of all mentioned parameters are studied for the global lockdown period of 2020 (from January to July) and compared with the corresponding months of the previous four years (2016-19) observations. Regarding surface radiation, April 2020 is the most affected month during the pandemic in which 0.2% increased net solar radiation (NSR), while 3.45% and 4.8% decreased net thermal radiation (NTR) and net radiation (NR) respectively was observed. Average radiative forcing during March-May 2020 was observed as 1.09 Wm^-2, -2.19 Wm^-2 and -1.09 Wm^-2 for NSR, NTR and NR, respectively. AOD was reduced by 0.2% in May 2020 while NO₂ and SO₂ were reduced by 5.4% and 8.8%, respectively, in April 2020. It was observed that NO₂ kept on reducing since January 2020 while SO₂ kept on reducing since February 2020 which were the pre-lockdown months. These results suggest that a more sophisticated analysis is needed to explain the atmosphere-radiation relation.

Effect of urban underlying surface on PM2.5 vertical distribution based on UAV in Xi'an, China

Fine particulate matter (PM_2.5) has become a significant issue of ecological environment. However, few studies have explored the vertical distribution of PM_2.5 in cities. The objectives of this paper are to reveal the vertical distribution regular pattern of PM_2.5 over urban underlying surfaces near the ground with a hexacopter-type unmanned aerial vehicle (UAV) in winter. Results showed that the maximum vertical gradient of PM_2.5 near the ground was typically the greatest in the morning as the stable atmospheric conditions. Moreover, regression model illustrated that relative humidity had the greatest impact on the vertical profile of PM_2.5 compared to air temperature and altitude as hygroscopic of PM_2.5 aerosols. Curve model shown that vertical profile of PM_2.5 over the surfaces of water and green space first increased slowly and then declined, besides, the highest concentration inflection of PM_2.5 above the water body (23.7 m) is higher than the green space (14.3 m). Thus, suggesting residents living vertical of 10-30 m from the ground around large water bodies and green spaces should not open windows for ventilation in the morning. Therefore, this study provides insights into the vertical distributions of PM_2.5 over different underlying surfaces and should be of reference value to urban planners for designing urban spaces to optimize atmosphere environment to provide a healthy living environment.

Age and Gender Effects on Genotoxicity in Diesel Exhaust Particles Exposed C57BL/6 Mice

There is growing evidence that the accumulation of DNA damage induced by fine particulate matter (PM2.5) exposure is an underlying mechanism of pulmonary disease onset and progression. However, there is a lack of experimental evidence on whether common factors (age, gender) affect PM2.5 induced genomic damage. Here, we assessed the DNA damage potency of PM2.5 using conventional genotoxicity testing in old male and female mice aged 8 and 40 weeks. Mice were intratracheally instilled with diesel exhaust PM2.5 (DEP, NIST SRM 1650b), twice a week for 4 weeks. Exposure to DEP was not associated with an increase in the frequency of micronucleated polychromatic erythrocytes and did not induce a systemic genotoxic effect in the bone marrow. Meanwhile, the results from the comet assay showed a significant increase in DNA damage in DEP exposed mouse lung specimens. The positive relationship between DEP exposure and DNA damage is stronger in the older than in the younger group. Statistical analysis showed that there was a modifying effect of age on the association between PM2.5 exposure and DNA damage. Our results suggest that the age factor should be considered to better understand the cellular adverse effects of PM2.5.

Spatio-Temporal Characteristics of PM2.5, PM10, and AOD over the Central Line Project of China’s South-North Water Diversion in Henan Province (China)

The spatio-temporal characteristics of particulate matter with a particle size less than or equal to 2.5 μm (PM2.5), particulate matter with a particle size less than or equal to 10 μm (PM10), meteorological parameters from September 2018 to September 2019, and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) aerosol optical depth (AOD) from 2007 to 2019 were investigated over the Central Line Project of China’s South-North Water Diversion (CSNWD) in Henan Province. To better understand the characteristics of the atmospheric environment over the CSNWD, air quality monitoring stations were installed in Nanyang (in the upper reaches), Zhengzhou (in the middle reaches), and Anyang (in the lower reaches). In this study, daily, monthly, and seasonal statistical analyses of PM2.5 and PM10 concentrations were performed and their relationship with meteorological parameters was investigated. The results show extremely poor air quality conditions over the Zhengzhou Station compared with the Nanyang and Anyang Stations. The annual average PM2.5 concentration did not meet China’s ambient air secondary standard (35 μg/m3 annual mean) over all the stations, while the annual average PM10 concentration satisfied China’s ambient air secondary standard (100 μg/m3 annual mean) over the Anyang and Nanyang Stations, except for the Zhengzhou Station. The highest PM2.5 and PM10 concentrations were observed during winter compared with the other seasons. The results show that PM2.5 and PM10 concentrations were negatively correlated with wind speed and temperature at the Nanyang and Zhengzhou Stations, but positively correlated with relative humidity. However, no significant negative or positive correlation was observed at Anyang Station. There is a strong linear positive correlation between PM2.5 and PM10 (R = 0.99), which indicates that the particulate matter at the three stations was mainly caused by local emissions. Additionally, the AOD values at the three stations were the highest in summer, which may be related to the residues of crops burned in Henan Province in summer.

The associations between social, built and geophysical environment and age-specific dementia mortality among older adults in a high-density Asian city

Background

Although socio-environmental factors which may affect dementia have widely been studied, the mortality of dementia and socio-environmental relationships among older adults have seldom been discussed.

Method

A retrospective, observational study based on territory-wide register-based data was conducted to evaluate the relationships of four individual-level social measures, two community-level social measures, six short-term (temporally varying) environmental measures, and four long-term (spatially varying) environmental measures with dementia mortality among older adults in a high-density Asian city (Hong Kong), for the following decedents: (1) all deaths: age >= 65, (2) “old-old”: age > = 85, (3) “mid-old”: aged 75–84, and (4) “young-old”: aged 65–74.

Results

This study identified 5438 deaths (3771 old-old; 1439 mid-old; 228 young-old) from dementia out of 228,600 all-cause deaths among older adults in Hong Kong between 2007 and 2014. Generally, regional air pollution, being unmarried or female, older age, and daily O₃ were associated with higher dementia mortality, while more urban compactness and greenness were linked to lower dementia mortality among older adults. Specifically, being unmarried and the age effect were associated with higher dementia mortality among the “old-old”, “mid-old” and “young-old”. Regional air pollution was linked to increased dementia mortality, while urban compactness and greenness were associated with lower dementia mortality among the “old-old” and “mid-old”. Higher daily O₃ had higher dementia mortality, while districts with a greater percentage of residents whose native language is not Cantonese were linked to lower dementia mortality among the “old-old”. Economic inactivity was associated with increased dementia mortality among the “young-old”. Gender effect varied by age.

Conclusion

The difference in strengths of association of various factors with dementia mortality among different age groups implies the need for a comprehensive framework for community health planning. In particular, strategies for air quality control, usage of greenspace and social space, and activity engagement to reduce vulnerability at all ages are warranted.

Spatio-Temporal Characteristics of PM2.5, PM10, and AOD over Canal Head Taocha Station, Henan Province

In this study, spatio-temporal characteristics of particulate matter (PMx; x = 2.5 and 10) mass concentrations and aerosol optical properties were analyzed over the water source area of the South–North Water Diversion Central Line. For this purpose, PM2.5 and PM10 mass concentrations were collected at the Taocha(TC)station from October 2018 to September 2019, and aerosol optical depth (AOD) was obtained from the Cloud-Aerosol LiDAR and Infrared Pathfinder Satellite Observation (CALIPSO) satellite from 2007 to 2019. The monthly, seasonal, and daily statistical analyses and related comparisons were conducted in the present study. The results showed that the PM10 concentrations meet China’s ambient air secondary quality standard (100 μg/m3 annual mean), whereas PM2.5 did not meet China’s ambient air secondary quality standard (35 μg/m3 annual mean) at the TC station, no obvious seasonal and diurnal variations are observed, and these particulates are caused by local emissions and outside sources. A significant positive correlation of PM2.5 and PM10 was observed with relative humidity and temperature, whereas no relationship was found with wind direction. The results also showed low (~0.1) AOD in spring, autumn, and winter, whereas slightly higher AOD (~0.3) was observed in summer. This may be caused by straw burning from long-distance transportation. This study may provide new data support for comprehensive ecological measures such as strengthening the ecological environment and water quality protection in the Middle Route Project of the South–North Water Diversion.

Estimation of High-Resolution PM2.5 over the Indo-Gangetic Plain by Fusion of Satellite Data, Meteorology, and Land Use Variables

Very high spatially resolved satellite-derived ground-level concentrations of particulate matter with an aerodynamic diameter of less than 2.5 μm (PM_2.5) have multiple potential applications, especially in air quality modeling and epidemiological and climatological research. Satellite-derived aerosol optical depth (AOD) and columnar water vapor (CWV), meteorological parameters, and land use data were used as variables within the framework of a linear mixed effect model (LME) and a random forest (RF) model to predict daily ground-level concentrations of PM_2.5 at 1 km × 1 km grid resolution across the Indo-Gangetic Plain (IGP) in South Asia. The RF model exhibited superior performance and higher accuracy compared with the LME model, with better cross-validated explained variance (R² = 0.87) and lower relative prediction error (RPE = 24.5%). The RF model revealed improved performance metrics for increasing averaging periods, from daily to weekly, monthly, seasonal, and annual means, which supported its use in estimating PM_2.5 exposure metrics across the IGP at varying temporal scales (i.e., both short and long terms). The RF-based PM_2.5 estimates showed high PM_2.5 levels over the middle and lower IGP, with the annual mean exceeding 110 μg/m³. As for seasons, winter was the most polluted season, while monsoon was the cleanest. Spatially, the middle and lower IGP showed poorer air quality compared to the upper IGP. In winter, the middle and lower IGP experienced very poor air quality, with mean PM_2.5 concentrations of >170 μg/m³.