Fertilizer management for global ammonia emission reduction

Crop production is a large source of atmospheric ammonia (NH3), which poses risks to air quality, human health and ecosystems1-5. However, estimating global NH3 emissions from croplands is subject to uncertainties because of data limitations, thereby limiting the accurate identification of mitigation options and efficacy4,5. Here we develop a machine learning model for generating crop-specific and spatially explicit NH3 emission factors globally (5-arcmin resolution) based on a compiled dataset of field observations. We show that global NH3 emissions from rice, wheat and maize fields in 2018 were 4.3 ± 1.0 Tg N yr-1, lower than previous estimates that did not fully consider fertilizer management practices6-9. Furthermore, spatially optimizing fertilizer management, as guided by the machine learning model, has the potential to reduce the NH3 emissions by about 38% (1.6 ± 0.4 Tg N yr-1) without altering total fertilizer nitrogen inputs. Specifically, we estimate potential NH3 emissions reductions of 47% (44-56%) for rice, 27% (24-28%) for maize and 26% (20-28%) for wheat cultivation, respectively. Under future climate change scenarios, we estimate that NH3 emissions could increase by 4.0 ± 2.7% under SSP1-2.6 and 5.5 ± 5.7% under SSP5-8.5 by 2030-2060. However, targeted fertilizer management has the potential to mitigate these increases.

Net effect of air pollution controls on health risk in the Beijing-Tianjin-Hebei region during the 2022 winter Olympics and Paralympics

Due to the non-linearity in ozone (O3) formation, reducing the emission of nitrogen oxides (NOx) may increase O3 concentration. Given the counteractive O3 response to NOx reduction, overall impact of air pollution controls can be ambiguous when the assessments focus on the changes in pollutant concentrations. In this study, a risk-based method was used to gauge the net effect of air pollution controls on mortality risk in the Beijing-Tianjin-Hebei (BTH) region during the 2022 Winter Olympics and Paralympics (WOP). This mega-event presents a unique opportunity to investigate the efficacy of deep cuts in pollutant emissions. Results show that O3 concentrations greatly increased as nitrogen dioxide (NO2) concentrations decreased in the BTH. Due to the active photochemical formations, O3 became the dominant pollutant that affected human health during the WOP. Despite the substantial O3 increases, the health benefits of NO2 reductions overwhelmed the adverse health effects of O3 increases in most regions of the BTH (at 81 out of 112 stations). After considering the impacts of particulate matter, the integrated health risk of air pollution mixtures declined almost everywhere in the BTH. Our results underscore the great necessity of changing the assessment paradigm of pollution control from using concentration-based methods to using risk-based methods. Together with the carbon neutrality policy, stringent control of NOx emission from combustion sources is a promising way to achieve synergistic control solutions for air pollution and climate change.

Effects of meteorological conditions on the mixing height of Nitrogen dioxide in China using new-generation geostationary satellite measurements and machine learning

Nitrogen dioxide (NO2) plays a critical role in terms of air quality, human health, ecosystems, and its impact on climate change. While the crucial roles of the vertical structure of NO2 have been acknowledged for some time, there is currently limited knowledge about this aspect in China. The Geostationary Environment Monitoring Spectrometer (GEMS) is the world's first geostationary satellite instrument capable of measuring the hourly columnar amount of NO2. The study presented here introduces the use of mixing height for NO2 in the atmosphere. A thorough examination of spatiotemporal variations in the mixing height of NO2 was conducted using data from both the GEMS and ground-based air quality monitoring networks. A random forest model based on machine learning techniques was utilized to examine how meteorological parameters affect the mixing height of NO2. The results of our study reveal a notable seasonal fluctuation in the mixing height of NO2, with the highest values observed during the summer and the lowest values during the winter. Additionally, there was an increasing diurnal trend from early morning to mid-afternoon. Moreover, the study discovered elevated NO2 mixing heights in the dry regions of northern China. The results also indicated a positive correlation between the mixing height of NO2 and temperature and wind speed, while negative associations were found with relative humidity and air pressure. The machine learning model's predicted NO2 mixing heights were in good agreement with the measurement-based outcomes, as evidenced by a coefficient of determination (R2) value of 0.96 (0.84 for the 10-fold cross-validation). These findings emphasize the noteworthy influence of meteorological variables on the vertical distribution of NO2 in the atmosphere and enhance our comprehension of the three-dimensional variations in NO2.

Relative contributions of ambient air and internal sources to multiple air pollutants in public transportation modes

Commuters are often exposed to relatively high air pollutant concentrations in public transport microenvironments (TMEs) because of their proximity to emission sources. Previous studies have mainly focused on assessing the concentrations of air pollutants in TMEs, but few studies have distinguished between the contributions of ambient air and internal sources to the exposure of commuters to air pollutants. The main objective of this study was to quantify the contributions of ambient air and internal sources to the measured particulate matter and gaseous pollutant concentrations in selected TMEs in Hong Kong, a high-rise, high-density city in Asia. A sampling campaign was conducted to measure air pollutant concentrations in TMEs in Hong Kong in July and November 2018 using portable air quality monitors. We measured the concentrations of each pollutant in different TMEs and quantified the infiltration of particulate matter into these TMEs. The double-decker bus had the lowest particulate matter concentrations (mean PM1, PM2.5, and PM10 concentrations of 5.1, 9.5, and 13 μg/m3, respectively), but higher concentrations of CO (0.9 ppm), NO (422 ppb), and NO2 (100 ppb). For all the TMEs, about half of the PM2.5 were PM1 particles. The Mass Transit Railway (MTR) subway system had a PM2.5/PM10 ratio of about 0.90, whereas the PM2.5/PM10 ratio was about 0.60-0.70 for the other TMEs. The MTR had infiltration factor estimates <0.4 for particulate matter, lower than those of the double-decker bus and minibus. The MTR had the highest contribution from internal sources (mean PM1, PM2.5, and PM10 concentrations of 4.6, 13.4, and 15.8 μg/m3, respectively). This study will help citizens to plan commuting routes to reduce their exposure to air pollution and help policy-makers to prioritize effective exposure reduction strategies.

Concurrent measurements of nitrate at urban and suburban sites identify local nitrate formation as a driver for urban episodic PM2.5 pollution

Nitrate (NO3-) is often among the leading components of urban particulate matter (PM) during PM pollution episodes. However, the factors controlling its prevalence remain inadequately understood. In this work, we analyzed concurrent hourly monitoring data of NO3- in PM2.5 at a pair of urban and suburban locations (28 km apart) in Hong Kong for a period of two months. The concentration gradient in PM2.5 NO3- was 3.0 ± 2.9 (urban) vs. 1.3 ± 0.9 μg m-3 (suburban) while that for its precursors nitrogen oxides (NOx) was 38.1 vs 4.1 ppb. NO3- accounted for 45 % of the difference in PM2.5 between the sites. Both sites were characterized to have more available NH3 than HNO3. Urban nitrate episodes, defined as periods of urban-suburban NO3- difference exceeding 2 μg m-3, constituted 21 % of the total measurement hours, with an hourly NO3- average gradient of 4.2 and a peak value of 23.6 μg m-3. Our comparative analysis, together with 3-D air quality model simulations, indicates that the high NOx levels largely explain the excessive NO3- concentrations in our urban site, with the gas phase HNO3 formation reaction contributing significantly during the daytime and the N2O5 hydrolysis pathway playing a prominent role during nighttime. This study presents a first quantitative analysis that unambiguously shows local formation of NO3- in urban environments as a driver for urban episodic PM2.5 pollution, suggesting effective benefits of lowering urban NOx.

Impacts of pollution heterogeneity on population exposure in dense urban areas using ultra-fine resolution air quality data

Traditional air quality data have a spatial resolution of 1 km or above, making it challenging to resolve detailed air pollution exposure in complex urban areas. Combining urban morphology, dynamic traffic emission, regional and local meteorology, physicochemical transformations in air quality models using big data fusion technology, an ultra-fine resolution modeling system was developed to provide air quality data down to street level. Based on one-year ultra-fine resolution data, this study investigated the effects of pollution heterogeneity on the individual and population exposure to particulate matter (PM_2.5 and PM₁₀), nitrogen dioxide (NO₂), and ozone (O₃) in Hong Kong, one of the most densely populated and urbanized cities. Sharp fine-scale variabilities in air pollution were revealed within individual city blocks. Using traditional 1 km average to represent individual exposure resulted in a positively skewed deviation of up to 200% for high-end exposure individuals. Citizens were disproportionally affected by air pollution, with annual pollutant concentrations varied by factors of 2 to 5 among 452 District Council Constituency Areas (DCCAs) in Hong Kong, indicating great environmental inequities among the population. Unfavorable city planning resulted in a positive spatial coincidence between pollution and population, which increased public exposure to air pollutants by as large as 46% among districts in Hong Kong. Our results highlight the importance of ultra-fine pollutant data in quantifying the heterogeneity in pollution exposure in the dense urban area and the critical role of smart urban planning in reducing exposure inequities.

Cardiovascular Mortality, Habitual Exercise, and Particulate Matter 2.5 Exposure: A Longitudinal Cohort Study

INTRODUCTION

Habitual exercise may amplify the respiratory uptake of air pollutants in the lung, exacerbating the adverse effects of air pollution. However, it is unclear whether this can reduce the health benefits of habitual exercise (referred to as leisure-time exercise). Thus, the combined effects of habitual exercise and chronic exposure to ambient fine particulate matter 2.5 on cardiovascular mortality were examined among adults in Taiwan.

METHODS

A total of 384,128 adults were recruited between 2001 and 2016 and followed up to May 31, 2019. Participants' vital status was obtained by matching their unique identification numbers with records of cardiovascular death in the National Death Registry of Taiwan. A time-varying Cox regression model was used to analyze the data. Analyses were conducted in 2021.

RESULTS

Cardiovascular death risks were inversely associated with habitual exercise and positively associated with chronic exposure to particulate matter 2.5. The beneficial effects of habitual exercise on cardiovascular mortality were not modified by chronic exposure to particulate matter 2.5. Inactive participants with high particulate matter 2.5 exposure exhibited a 123% higher risk of cardiovascular death than high-exercise-group participants exposed to low levels of particulate matter 2.5 (95% CI=89, 163).

CONCLUSIONS

High level of habitual exercise combined with low exposure level of ambient particulate matter 2.5 is associated with the lowest risk of cardiovascular death. A higher level of habitual exercise is associated with a lower risk of cardiovascular death at all levels of particulate matter 2.5 exposure studied. The results indicate that habitual exercise is a safe health promotion strategy even for people residing in relatively polluted regions.

Life-course exposure to ambient fine particulate matter and hypertension in adulthood: a longitudinal cohort study

PM_2.5-hypertension association were well documented in adults, while the effects of life-course exposure to PM_2.5 on adulthood hypertension remained unclear. This study aimed to investigate the associations between life-course exposure to ambient PM_2.5 and incident hypertension in adulthood in Asia. We included 4272 participants with 17,814 medical visits from two open cohorts in Taiwan and Hong Kong between 2000 and 2018. We used a satellite-based model to assess 2-year average PM_2.5 exposure at a resolution of 1 km². A linear mixed model was used to examine the association with blood pressure. A Cox regression model with time-dependent covariates was used to examine the overall association with the development of hypertension in adulthood. Life-course mixed models were used to examine the effects of PM_2.5 exposure at different life stages on blood pressure and hypertension. For every 10 μg/m³ increase in PM_2.5, the overall risk of adulthood hypertension increased by 40% (95% confidence interval [CI] 8-80%). The health effects of PM_2.5 exposure at different life-stages on incident hypertension were generally independent of each other. In critical model, the risk of developing hypertension increased 23%, 27%, and 55% for each 10 μg/m³ increase in PM_2.5 exposure during school age, adolescence, and adulthood, respectively. Similar associations were found between life-course PM_2.5 exposure and blood pressure. Association between PM_2.5 and adulthood hypertension can be traced back to childhood. Our study suggests that life-course control of air pollution exposure should be implemented to alleviate the huge burden of adulthood hypertension.

Multi-pollutant air pollution and renal health in Asian children and adolescents: An 18-year longitudinal study

BACKGROUND

Few studies have examined the effects of multi-pollutant air pollution on renal health, especially in children and adolescents. This study investigated the association between long-term ambient air pollution exposure and renal health in Asian children and adolescents.

METHODS

This study included 10,942 children and adolescents from Taiwan and Hong Kong between 2000 and 2017. PM_2.5, NO₂ and O₃ concentrations were estimated using satellite-based spatiotemporal regression models. Two-year average concentrations, those of the year of visit and the preceding year, were used. Linear mixed models were used to examine the association between air pollution and yearly changes in estimated glomerular filtration rate (eGFR). Cox regression models with time-dependent covariates were used to examine the association between air pollution and the development of chronic kidney disease (CKD).

RESULTS

Median age of the participants was 19 years (range: 2-25). The overall average concentration of PM_2.5, NO₂ and O₃ was 26.7 μg/m³, 44.1 μg/m³ and 51.1 μg/m³, respectively. The mean yearly change in eGFR was 0.37 μL/min/1.73 m² and the incidence rate of CKD was 6.8 per 1,000 person-years. In single-pollutant models, each 10 μg/m³ increase in PM_2.5 was associated with a 0.45 μL/min/1.73 m² [95% confidence interval (CI): 0.28-0.63] reduction in the yearly increase in eGFR and 53% [hazard ratio (HR): 1.53 (95%CI: 1.07-2.2)] greater risk of incident CKD. Each 10 μg/m³ increase in NO₂ was associated with a 7% [HR (95%CI): 1.07 (1.00-1.15)] higher risk of incident CKD, while an equivalent increase in O₃ was associated with a 19% [HR (95%CI): 0.81 (0.67-0.98)] lower risk.

CONCLUSIONS

Long-term exposure to ambient PM_2.5 and NO₂ was associated with a slower growth of eGFR and a higher risk of incident CKD in children and adolescents. Our findings suggest that air pollution control in early life is imperative to improve lifelong renal health and alleviate the CKD burden.

Risk tradeoffs between nitrogen dioxide and ozone pollution during the COVID-19 lockdowns in the Greater Bay area of China

Photochemical regime for ozone (O3) formation is complicated in the sense that reducing emission of nitrogen oxides (NOx) may increase O3 concentration. The lockdown due to COVID-19 pandemic affords a unique opportunity to use real observations to explore the O3 formation regime and the effectiveness of NOx emission control strategies. In this study, observations from ground networks during the lockdowns were used to assess spatial disparity of the Ratio of Ozone Formation (ROF) for nitrogen dioxide (NO2) reduction in the Greater Bay Area (GBA) of China. The health risk model from Air Quality Health Index (AQHI) system in Hong Kong was adopted to evaluate the risk tradeoffs between NO2 and O3. Results show that the levels of O3 increase and NO2 reduction were comparable due to high ROF values in urban areas of central GBA. The ozone reactivity to NO2 reduction gradually declined outwards from central GBA. Despite the O3 increases, the NOx emission controls reduced the Integrated Health Risk (IHR) of NO2 and O3 in most regions of the GBA. When risk coefficients from the AQHI in Canada or the global review were adopted in the risk analyses, the results are extremely encouraging because the controls of NOx emission reduced the IHR of NO2 and O3 almost everywhere in the GBA. Our results underscore the importance of using a risk-based method to assess the effectiveness of emission control measures and the overall health benefit from NOx emission controls in the GBA.

Habitual Exercise, Air Pollution, and Pneumonia Mortality: A Longitudinal Cohort Study of Approximately 0.4 Million Adults

In this study, we aimed to examine the combined associations of particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5) and habitual exercise with pneumonia mortality. We included 384,130 persons aged ≥18 years from Taiwan, Republic of China, during 2001-2016. We followed participants until May 31, 2019, to obtain information on vital status. A time-dependent Cox regression model was used for statistical analysis. We found that risks of pneumonia mortality were reduced by 55% (hazard ratio (HR) = 0.45, 95% confidence interval (CI): 0.36, 0.55) and 36% (HR = 0.64, 95% CI: 0.52, 0.80) in participants who engaged in high and moderate levels of exercise, respectively, as compared with inactive persons. By contrast, each 10-μg/m3 increase in chronic PM2.5 exposure was associated with a 30% (HR = 1.30, 95% CI: 1.17, 1.45) higher risk of pneumonia mortality. Risk of pneumonia death was 72% lower (HR = 0.28, 95% CI: 0.20, 0.41) for persons with a high exercise level and a low PM2.5 level. Lower risk of pneumonia mortality was associated with both higher exercise and lower PM2.5 air pollution levels. For adults exposed to different levels of PM2.5, exercise benefits remained. Our findings suggest that engaging in exercise is a safe and effective strategy for alleviating the burden of pneumonia mortality, even for people who reside in a moderately polluted area.

Assessment of the impact of sensor error on the representativeness of population exposure to urban air pollutants

For the monitoring of urban air pollution, smart sensors are often seen as a welcome addition to fixed-site monitoring (FSM) networks. Due to price and simple installation, increases in spatial representation are thought to be achieved by large numbers of these sensors, however, a number of sensor errors have been identified. Based on a high-resolution modelling system, up to 400 pseudo smart sensors were perturbated with the aim of simulating common sensor errors and added to the existing FSM network in Hong Kong, resulting in 1200 pseudo networks for PM_2.5 and 1040 pseudo networks for NO₂. For each pseudo network, population-weighted area representativeness (PWAR) was calculated based on similarity frequency. For PM_2.5, improvements (up to 16%) to the high baseline representativeness (PWAR = 0.74) were achievable only by the addition of high-quality sensors and favourable environmental conditions. The baseline FSM network represents NO₂ less well (PWAR = 0.52), as local emissions in the study domain resulted in high spatial pollution variation. Due to higher levels of pollution (population-weighted average 37.3 ppb) in comparison to sensor error ranges, smart sensors of a wider quality range were able to improve network representativeness (up to 42%). Marginal representativeness increases were found to exponentially decrease with existing sensor number. The quality and maintenance of added sensors had a stronger effect on overall network representativeness than the number of sensors added. Often, a small number of added sensors of a higher quality class led to larger improvements than hundreds of lower-class sensors. Whereas smart sensor performance and maintenance are important prerequisites particularly for developed cities where pollutant concentration is low and there is an existing FSM network, our study shows that for places with high pollutant variability and concentration such as encountered in some developing countries, smart sensors will provide benefits for understanding population exposure.

Optimized neural network for daily-scale ozone prediction based on transfer learning

Tropospheric ozone (O₃) pollution is worsening in China, and an accurate forecast is a prerequisite to lower the O₃ peak level. In recent years, machine learning techniques have attracted increasing attention in O₃ prediction owing to their high efficiency and simple operation. However, the accuracy of predicting the daily O₃ level is low. This study proposed a novel model by coupling long short-term memory neural network with transfer learning (TL-LSTM), with meteorology and pollutant concentration information as the model input. L2 regularization was applied to reduce the risk of overfitting and to improve the accuracy and generalization ability of the model prediction. Our results indicated that by transferring the knowledge in the model configuration from the hourly LSTM module, TL-LSTM greatly improves the predictability of the daily maximum 8 h average (MDA8) of O₃ in Hong Kong. The coefficient of determination (R²) increased from 0.684 to 0.783 and the mean square error (MSE) reduced from 1.36 × 10^-2 to 1.05 × 10^-2. Furthermore, R² and MSE were the highest in summer, indicating an under-prediction of peak O₃ levels. This was a result of the limited number of high O₃ days, which did not provide sufficient knowledge for the model to make an accurate prediction. Sobol analysis indicated that wind speed was the most sensitive factor in O₃ prediction, largely due to the development of land-sea breeze circulation which effectively traps pollutants and expedites O₃ formation. The results clearly demonstrate the effectiveness of the TL-LSTM in predicting the daily O₃ concentration in Hong Kong. Thus, TL-LSTM can be promulgated into other photochemically active regions to assist in O₃ pollution forecasting and management.

Habitual exercise, chronic exposure to fine particulate matter and high-sensitivity C reactive protein in Asian adults

OBJECTIVES

Exercise may increase the inhaled amount of air pollutants and exacerbate the adverse health effects. We investigated the combined effects of chronic exposure to fine particulate matter with an aerodynamic diameter less than 2.5 µm (PM_2.5) and habitual exercise on C reactive protein (CRP), a sensitive marker of inflammation.

METHODS

We selected 40 209 Taiwanese adults who joined a standard medical screening programme between 2001 and 2016. The PM_2.5 exposure was estimated at each participant's address using a satellite-based spatiotemporal model. Information on habitual exercise was collected using a standard self-administered questionnaire. Mixed-effects linear regression models were used to investigate the associations of CRP with PM_2.5 and exercise. An interaction term of PM_2.5 and exercise was introduced in the models to test the modifying effects.

RESULTS

A greater amount of habitual exercise was associated with a decreased level of CRP, while a higher concentration of PM_2.5 exposure was associated with an increased level of CRP. The inverse associations of habitual exercise with CRP were not modified by chronic exposure to PM_2.5. The participants in the group with a low level of exercise and a high level of PM_2.5 exposure exhibited a 19.1% higher level of CRP than those in the group with a high level of exercise and a low level of PM_2.5 exposure (95% CI: 13.7% to 24.8%; p<0.001). The longitudinal and sensitivity analyses yielded similar results.

CONCLUSIONS

Increased levels of exercise and reduced exposure levels of PM_2.5 are associated with a lower CRP level. Habitual exercise reduces CRP level regardless of the levels of chronic PM_2.5 exposure. Our results support that habitual exercise is a safe approach for reducing systemic inflammation to improve cardiovascular health even for people residing in relatively polluted areas.

Spread of SARS-CoV-2 aerosols via two connected drainage stacks in a high-rise housing outbreak of COVID-19

Vertical transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) along a vertical column of flats has been documented in several outbreaks of coronavirus disease 2019 (COVID-19) in Guangdong and Hong Kong. We describe an outbreak in Luk Chuen House, involving two vertical columns of flats associated with an unusually connected two-stack drainage system, in which nine individuals from seven households were infected. The index case resided in Flat 812 (8th floor, Unit 12), two flats (813, 817) on its opposite side reported one case each (i.e., a horizontal sub-cluster). All other flats with infected residents were vertically associated, forming a vertical sub-cluster. We injected tracer gas (SF₆) into drainage stacks via toilet or balcony of Flat 812, monitored gas concentrations in roof vent, toilet, façade, and living room in four of the seven flats with infected residents and four flats with no infected residents. The measured gas concentration distributions agreed with the observed distribution of affected flats. Aerosols leaking into drainage stacks may generate the vertical sub-cluster, whereas airflow across the corridor probably caused the horizontal sub-cluster. Sequencing and phylogenetic analyses also revealed a common point-source. The findings provided additional evidence of probable roles of drainage systems in SARS-CoV-2 transmission.

Long-term Exposure to Fine Particulate Matter and Mortality A Longitudinal Cohort Study of 400,459 Adults

BACKGROUND

Cohort studies on the association between long-term exposure to fine particulate matter (PM2.5) and mortality have been well established for America and Europe, but limited and inconsistent in Asia with much higher air pollution. This study aims to investigate the associations between ambient PM2.5 and all-cause and cause-specific mortality over a period of rising and then declining PM2.5.

METHODS

We enrolled a total of 400,459 adults from an open cohort between 2001 and 2016, and followed them up until 31 May 2019. We obtained mortality data from the National Death Registry maintained by the Ministry of Health and Welfare in Taiwan. We estimated ambient PM2.5 exposures using a satellite-based spatiotemporal model. We performed a Cox regression model with time-dependent covariates to investigate the associations of PM2.5 with deaths from all causes and specific causes.

RESULTS

This study identified 14,627 deaths and had a total of 5 million person-years of follow-up. Each 10 µg/m3 increase in PM2.5 was associated with an increased hazard risk of 29% (95% confidence interval: 24%-35%) in all-cause mortality. Risk of death increased by 30% for natural causes, 20% for cancer, 42% for cardiovascular disease (CVD) causes, and 53% for influenza and pneumonia causes, for each 10 µg/m3 increase in PM2.5. Sensitivity analyses generally yielded similar results.

CONCLUSION

Long-term exposure to ambient PM2.5 was associated with increased risks of all-cause mortality and deaths from cancers, natural causes, CVD, and influenza and pneumonia. Longitudinal study design should be encouraged for air pollution epidemiologic investigation.

Total and differential white blood cell count and cause-specific mortality in 436 750 Taiwanese adults

BACKGROUND AND AIMS

White blood cell (WBC) count is an easily obtainable biomarker of systematic inflammation. Our study aimed to investigate the associations of differential WBC count with all-cause and cause-specific mortality in a general Asian population.

METHODS AND RESULTS

Cox proportional hazards model was used to evaluate the associations of WBC count with mortality separately for men and women, with adjustment for multiple variables including age, smoking, and other lifestyle factors. Stratified analyses by age, smoking, diabetes, and hypertension were conducted to explore potential effect modification. Elevated WBC count was significantly associated with increased mortality risk. The adjusted hazard ratios of total WBC (10th decile compared to decile of lowest risk) for all-cause mortality were 1.42 (95% CI: 1.33, 1.53) for men and 1.54 (95% CI: 1.42, 1.68) for women. Similar risks were observed for neutrophils, monocytes, and neutrophil/lymphocyte (NL) ratio. The highest deciles of neutrophils, monocytes, and NL ratio were also positively associated with risk of cardiovascular/cerebrovascular, cancer, and respiratory mortality after adjusting for covariates. Results for all-cause mortality remained statistically significant for participants who were <60 years old, non-smokers, non-diabetic, and non-hypertensive.

CONCLUSIONS

Total and differential WBC counts (neutrophils, monocytes, and NL ratios) are positively associated with increased risk of all-cause mortality, cardiovascular and cerebrovascular, cancer, and respiratory mortality among Taiwanese adults.

Removing the effects of meteorological factors on changes in nitrogen dioxide and ozone concentrations in China from 2013 to 2020

Previous studies on long-term ozone (O₃) variations in China have reported inconsistent conclusions on the role of meteorological factors in controlling said variations. In this study, we used an observation-based decomposition model to conduct an up-to-date investigation of the effects of meteorological factors on the variations in nitrogen dioxide (NO₂) and O₃ concentrations in China in the summer from 2013 to 2020. The variations in NO₂ and O₃ concentrations after removing the major meteorological effects were then analyzed to improve our understanding of O₃ formation regimes. Ground measurements show that both NO₂ and O₃ concentrations decreased in eastern, central, and southeastern China (e.g., NO₂ and O₃ concentrations in Wuhan reduced by 4.3 and 6.2 ppb, respectively), which was not anticipated. Analyses of meteorological effects showed that reduced wind strength, decreased temperature, and increased relative humidity significantly reduced O₃ concentrations in eastern and central China (e.g., by 10.5 ppb in Wuhan). After removing the major meteorological effects, the O₃ trends were reversed in eastern and central China (e.g., increased by 4.9 ppb in Wuhan). The contrasting trends in NO₂ and O₃ concentrations suggest that their O₃ formations were sensitive to volatile organic compounds (VOC-limited regime). In southeastern China, both NO₂ and O₃ concentrations decreased, implying that the O₃ formation regimes changed to mixed sensitive or nitrogen oxide-limited (NO_x-limited) regimes. The meteorological effects varied by region and may play a dominant role in controlling the long-term O₃ variation. Our results indicate that the attribution of O₃ variation to emission control without accounting for meteorological effects can be misleading.

Reduced ambient PM2.5, better lung function, and decreased risk of chronic obstructive pulmonary disease

BACKGROUND

Several studies reported that long-term exposure to fine particulate matter (PM_2.5) was associated with an increased risk of chronic obstructive pulmonary disease (COPD). It remains unclear whether reduced PM_2.5 can decrease the risk of COPD development.

OBJECTIVE

To investigate the associations of dynamic changes (including deterioration and improvement) in long-term exposure to ambient PM_2.5 with changes in lung function and the incidence of COPD.

METHODS

A total of 133,119 adults (aged 18 years or older) were recruited in Taiwan between 2001 and 2014. All participants underwent at least two standard medical examinations including spirometry test. We estimated PM_2.5 concentrations using a high-resolution (1 km²) satellite-based spatio-temporal model. The change in PM_2.5 (ΔPM_2.5) was defined as the difference in concentration of PM_2.5 between the respective visit and the previous visit. We used a multivariable mixed linear model and time-varying Cox model to investigate the associations of change in PM_2.5 with annual change of lung function and the incidence of COPD, respectively.

RESULT

The PM_2.5 concentration in Taiwan increased during 2002-2004 and began to decrease around 2005. Every 5-µg/m³/year decrease in the annual change of PM_2.5 (i.e., ΔPM_2.5/year of 5 µg/m³/year) was associated with an average increase of 19.93 mL/year (95 %CI: 17.42,22.43) in forced expiratory volume in 1 s (FEV₁), 12.76 mL/year (95 %CI: 9.84,15.66) in forced vital capacity (FVC), 70.22 mL/s/year (95 %CI: 64.69,76.16) in midexpiratory flow between 25 and 75% of the forced vital capacity (MEF25-75), 0.27%/year (95 %CI: 0.21%, 0.32%) in FEV₁/FVC/year. Every 5 µg/m³ decrease in PM_2.5 (i.e., ΔPM_2.5 of 5 µg/m³) was associated with a 12% (95 %CI: 7%, 17%) reduced risk of COPD development. The stratified and sensitivity analyses generally yielded similar results.

CONCLUSION

An improvement in PM_2.5 pollution exposure was associated with an attenuated decline in lung function parameters of FEV₁, FVC, MEF25-75, and FEV₁/FVC, and a decreased risk of COPD development. Our findings suggest that strategies aimed at reducing air pollution may effectively combat the risk of COPD development.

Seasonality of tuberculosis in intermediate endemicity setting dominated by reactivation diseases in Hong Kong

Summer-spring predominance of tuberculosis (TB) has been widely reported. The relative contributions of exogenous recent infection versus endogenous reactivation to such seasonality remains poorly understood. Monthly TB notifications data between 2005 and 2017 in Hong Kong involving 64,386 cases (41% aged ≥ 65; male-to-female ratio 1.74:1) were examined for the timing, amplitude, and predictability of variation of seasonality. The observed seasonal variabilities were correlated with demographics and clinical presentations, using wavelet analysis coupled with dynamic generalised linear regression models. Overall, TB notifications peaked annually in June and July. No significant annual seasonality was demonstrated for children aged ≤ 14 irrespective of gender. The strongest seasonality was detected in the elderly (≥ 65) among males, while seasonal pattern was more prominent in the middle-aged (45–64) and adults (30–44) among females. The stronger TB seasonality among older adults in Hong Kong suggested that the pattern has been contributed largely by reactivation diseases precipitated by defective immunity whereas seasonal variation of recent infection was uncommon.

Combined effects of chronic PM2.5 exposure and habitual exercise on cancer mortality: a longitudinal cohort study

BACKGROUND

Exercise may increase the inhalation and deposition of air pollutants, which may counteract its beneficial effects. We thus examined the combined effects of chronic exposure to fine particulate matter (PM2.5) and habitual exercise on the risk of death from cancer in Taiwan.

PATIENTS AND METHODS

A total of 384 128 adults (≥18 years of age) were recruited for a medical screening programme between 2001 and 2016, yielding 842 384 medical-examination records. All participants were followed up until 31 May 2019. Vital data were obtained from the National Death Registry of Taiwan and the ambient PM2.5 exposure was estimated using a satellite-based spatiotemporal model. Information on habitual exercise was collected using a standard self-administered questionnaire. The time-dependent Cox-regression model was used to evaluate the combined effects.

RESULTS

A greater amount of habitual exercise was associated with lower risk of death from cancer, whilst a higher level of PM2.5 exposure was associated with a higher risk of death from cancer. The inverse associations of habitual exercise with death from cancer were not modified by chronic exposure to PM2.5. The participants in the group with a high level of exercise and a low level of PM2.5 exposure exhibited a 35% lower risk of death from cancer than those in the group with a low level of exercise and a high level of PM2.5 exposure (95% confidence interval: 28%, 42%).

CONCLUSIONS

Increased levels of exercise and reduced exposure levels of PM2.5 are associated with a lower risk of death from cancer. Habitual exercise reduces the risk of death from cancer regardless of the levels of chronic PM2.5 exposure. Our results indicate that habitual exercise is a suitable health-promotion strategy even for people who reside in moderately polluted regions.

Associations of Reduced Ambient PM2.5 Level With Lower Plasma Glucose Concentration and Decreased Risk of Type 2 Diabetes in Adults: A Longitudinal Cohort Study

It remains unknown whether reduced air pollution levels can prevent type 2 diabetes mellitus. In this study, we investigated the associations between dynamic changes in long-term exposure to ambient fine particulate matter, defined as particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5), and changes in fasting plasma glucose (FPG) levels and incidence of type 2 diabetes. A total of 151,398 adults (ages ≥18 years) were recruited in Taiwan between 2001 and 2014. All participants were followed up for a mean duration of 5.0 years. Change in PM2.5 (ΔPM2.5) was defined as the value at a follow-up visit minus the corresponding value at the immediately preceding visit. The PM2.5 concentration in Taiwan increased during 2002-2004 and began to decrease in 2005. Compared with participants with little or no change in PM2.5 exposure, those with the largest decrease in PM2.5 had a decreased FPG level (β = -0.39, 95% confidence interval: -0.47, -0.32) and lower risk of type 2 diabetes (hazard ratio = 0.86, 95% confidence interval: 0.80, 0.93). The sensitivity analysis and analyses stratified by sex, age, body mass index, smoking, alcohol drinking, and hypertension generally yielded similar results. Improved PM2.5 air quality is associated with a better FPG level and a decreased risk of type 2 diabetes development.

Physical distancing implementation, ambient temperature and Covid-19 containment: An observational study in the United States

Governments may relax physical distancing interventions for coronavirus disease 2019 (Covid-19) containment in warm seasons/areas to prevent economic contractions. However, it is not clear whether higher temperature may offset the transmission risk posed by this relaxation. This study aims to investigate the associations of the effective reproductive number (R_t) of Covid-19 with ambient temperature and the implementation of physical distancing interventions in the United States (US). This study included 50 states and one territory of the US with 4,532,650 confirmed cases between 29 January and 31 July 2020. We used an interrupted time-series model with a state-level random intercept for data analysis. An interaction term of 'physical distancing×temperature' was included to examine their interactions. Stratified analyses by temperature and physical distancing implementation were also performed to analyse the modifying effects. The overall median (interquartile range) R_t was 1.2 (1.0-2.3). The implementation of physical distancing was associated with a 12% decrease in the risk of R_t (relative risk [RR]: 0.88, 95% confident interval [CI]: 0.86-0.89), and each 5 °C increase in temperature was associated with a 2% decrease (RR: 0.98, 95%CI: 0.97-0.98). We observed a statistically significant interaction between temperature and physical distancing implementation, but all the RRs were small (close to one). The containing effects of high temperature were attenuated by 5.1% when physical distancing was implemented. The association of COVID-19 R_t with physical distancing implementation was more stable (0.88 vs. 0.89 in days when temperature was low and high, respectively). Increased temperature did not offset the risk of Covid-19 R_t posed by the relaxation of physical distancing implementation. Our study does not recommend relaxing the implementation of physical distancing interventions in warm seasons/areas.

Effects of air pollution and habitual exercise on the risk of death: a longitudinal cohort study

Background:

Exercise may exacerbate the adverse health effects of air pollution by increasing the inhalation of air pollutants. We investigated the combined effects of long-term exposure to fine particle matter (PM_2.5) and habitual exercise on deaths from natural causes in Taiwan.

Methods:

We recruited 384 130 adults (aged ≥ 18 yr) with 842 394 medical examination records between 2001 and 2016, and followed all participants until May 31, 2019. We obtained vital data from the National Death Registry of Taiwan. We estimated PM_2.5 exposure using a satellite-based spatiotemporal model, and collected information on exercise habits using a standard self-administered questionnaire. We analyzed the data using a Cox regression model with time-dependent covariates.

Results:

A higher level of habitual exercise was associated with a lower risk of death from natural causes, compared with inactivity (hazard ratio [HR] 0.84, 95% confidence interval [CI] 0.80–0.88 for the moderate exercise group; HR 0.65, 95% CI 0.62–0.68 for the high exercise groups), whereas a higher PM_2.5 exposure was associated with a higher risk of death from natural causes compared with lower exposure (HR 1.02, 95% CI 0.98–1.07, and HR 1.15, 95% CI 1.10–1.20, for the moderate and high PM_2.5 exposure groups, respectively). Compared with inactive adults with high PM_2.5 exposure, adults with high levels of habitual exercise and low PM_2.5 exposure had a substantially lower risk of death from natural causes. We found a minor, but statistically significant, interaction effect between exercise and PM_2.5 exposure on risk of death (HR 1.03 95% CI 1.01–1.06). Subgroup analyses, stratified by PM_2.5 categories, suggested that moderate and high levels of exercise were associated with a lower risk of death in each PM_2.5 stratum, compared with inactivity.

Interpretation:

Increased levels of exercise and reduced PM_2.5 exposure are associated with a lower risk of death from natural causes. Habitual exercise can reduce risk regardless of the levels of PM_2.5 exposure. Our results suggest that exercise is a safe health improvement strategy, even for people residing in relatively polluted regions.

Combined effects of chronic PM2.5 exposure and habitual exercise on renal function and chronic kidney disease: A longitudinal cohort study

BACKGROUND

We investigated the combined effects of chronic PM_2.5 exposure and habitual exercise on the decline of renal function and the incidence of chronic kidney disease (CKD) in a large cohort in Taiwan.

METHODS

The present data analysis included a total of 108,615 participants aged 18 years or above who were recruited between 2001 and 2016. All participants underwent at least two medical examinations. Estimated glomerular filtration rate (eGFR) was calculated using the Modification of Diet in Renal Disease (MDRD) equation. The incident of eGFR decline ≥30% was defined as a decline in eGFR of ≥30% during the study period, while the incident CKD was defined as an eGFR <60 mL/min/1.73 m² or a newly self-reported physician-diagnosed CKD in the subsequent visits. The satellite-based spatiotemporal model was used to estimate PM_2.5 exposure at each participant's address. Information on habitual exercise was collected using a standard self-administered questionnaire. The Cox regression model with time-dependent covariates was used for data analyses.

RESULTS

Higher habitual exercise was associated with lower risks of renal function decline and CKD development, whereas higher PM_2.5 exposure was associated with higher risks of renal function decline and CKD development. We found no significant interaction effect between PM_2.5 and habitual exercise, with an HR (95% CI) of 1.02 (0.97, 1.07) for incident eGFR decline ≥30% and 1.00 (0.95, 1.05) for CKD development. Compared to participants with inactive-exercise and high-PM_2.5, participants with high-exercise and low-PM_2.5 had 74% and 61% lower risks of renal function decline and CKD development, respectively.

CONCLUSION

Increased habitual exercise and reduced PM_2.5 exposures are associated with lower risks of renal function decline and CKD development. Habitual exercise reduces risks of renal function decline and CKD development regardless of the levels of chronic PM_2.5 exposure. Our study suggests that habitual exercise is a safe approach for kidney health improvement even for people residing in relatively polluted areas and should be promoted.

Habitual exercise is associated with reduced risk of diabetes regardless of air pollution: a longitudinal cohort study

AIMS/HYPOTHESIS

Physical activity may increase a person's inhalation of air pollutants and exacerbate the adverse health effects. This study aimed to investigate the combined associations of chronic exposure to particulate matter with an aerodynamic diameter less than 2.5 μm (PM_2.5) and habitual physical activity with the incidence of type 2 diabetes in Taiwan.

METHODS

We selected 156,314 non-diabetic adults (≥18 years old) who joined an ongoing longitudinal cohort between 2001 and 2016. Incident type 2 diabetes was identified at the follow-up medical examinations. Two-year mean PM_2.5 exposure was estimated at each participant's address using a satellite-based spatiotemporal model. Information on physical activity and a wide range of covariates was collected using a standard self-administered questionnaire. We analysed the data using a Cox regression model with time-varying covariates. An interaction term between PM_2.5 and physical activity was included to examine the overall interaction effects.

RESULTS

Compared with high physical activity, moderate and inactive/low physical activity were associated with a higher risk of diabetes (HR [95% CI] 1.31 [1.22, 1.41] and 1.56 [1.46, 1.68], respectively). Participants with moderate/high PM_2.5 had a higher risk of type 2 diabetes than the participants exposed to low PM_2.5 (HR 1.31 [1.22, 1.40] and 1.94 [1.76, 2.14], respectively). The participants with high physical activity and low PM_2.5 had a 64% lower risk of type 2 diabetes than those with inactive/low physical activity and high PM_2.5.

CONCLUSIONS/INTERPRETATION

Higher physical activity and lower PM_2.5 exposure are associated with lower risk of type 2 diabetes. Habitual physical activity can reduce the risk of diabetes regardless of the levels of PM_2.5 exposure. Our results indicate that habitual physical activity is a safe diabetes prevention strategy for people residing in relatively polluted regions.

A proposed population-health based metric for evaluating representativeness of air quality monitoring in cities: Using Hong Kong as a demonstration

City air quality monitoring (AQM) network are typically sparsely distributed due to high operation costs. It is of the question of how well it can reflect public health risks to air pollution given the diversity and heterogeneity in pollution, and spatial variations in population density. Combing high-resolution air quality model, spatial population distribution and health risk factors, we proposed a population-health based metric for AQM representativeness. This metric was demonstrated in Hong Kong using hourly modelling data of PM10, PM2.5, NO2 and O3 in 2019 with grid cells of 45m * 48m. Individual and total hospital admission risks (%AR) of these pollutants were calculated for each cell, and compared with those calculated at 16 monitoring sites using the similarity frequency (SF) method. AQM Representativeness was evaluated by SF and a population-health based network representation index (PHNI), which is population-weighted SF over the study-domain. The representativeness varies substantially among sites as well as between population- and area-based evaluation methods, reflecting heterogeneity in pollution and population. The current AQM network reflects population health risks well for PM10 (PHNI = 0.87) and PM2.5 (PHNI = 0.82), but is less able to represent risks for NO2 (PHNI = 0.59) and O3 (PHNI = 0.78). Strong seasonal variability in PHNI was found for PM, increasing by >11% during autumn and winter compared to summer due to regional transport. NO2 is better represented in urban than rural, reflecting the heterogeneity of urban traffic pollution. Combined health risk (%ARtotal) is well represented by the current AQM network (PHNI = 1), which is more homogenous due to the dominance and anti-correlation of NO2 and O3 related %AR. The proposed PHNI metric is useful to compare the health risk representativeness of AQM for individual and multiple pollutants and can be used to compare the effectiveness of AQM across cities.

Reduced Ambient PM2.5 Was Associated with a Decreased Risk of Chronic Kidney Disease: A Longitudinal Cohort Study

Many countries have dedicated to the mitigation of air pollution in the past several decades. However, evidence of beneficial effects of air quality improvement on chronic kidney disease (CKD) remains limited. We thus investigated the effects of dynamic changes (including deterioration and improvement) in air quality on the incidence of CKD in a longitudinal study in Taiwan. During 2001-2016, this study recruited a total of 163,197 Taiwanese residents who received at least two standard physical examinations. The level of fine particle matter (PM_2.5) was estimated using a high-resolution (1 km²) satellite-based spatio-temporal model. We defined changes of PM_2.5 concentrations (ΔPM_2.5) as the difference between the two-year average measurements during follow-up and during the immediately preceding visit. The time-dependent Cox regression model was adopted to evaluate the relationships between ΔPM_2.5 and the incidence of CKD after adjusting for a series of covariates. The concentrations of PM_2.5 in Taiwan peaked around 2004 and began to decrease since 2005. We observed an approximate linear concentration-response relationship of ΔPM_2.5 with CKD incidence. Every 5 μg/m³ decrease in the ambient concentration of PM_2.5 was associated with a 25% reduced risk of CKD development [hazard ratio (HR): 0.75; 95% CI: 0.73, 0.78]. In conclusion, this study demonstrated that the improvement of PM_2.5 air quality might be associated with a lower risk of CKD development. Our findings indicate that reducing air pollution may effectively prevent the development of CKD.

An improved decomposition method to differentiate meteorological and anthropogenic effects on air pollution: A national study in China during the COVID-19 lockdown period

Although the effects of meteorological factors on severe air pollution have been extensively investigated, quantitative decomposition of the contributions of meteorology and anthropogenic factors remains a big challenge. The novel coronavirus disease 2019 (COVID-19) pandemic affords a unique opportunity to test decomposition method. Based on a wind decomposition method, this study outlined an improved method to differentiate complex meteorological and anthropogenic effects. The improved method was then applied to investigate the cause of unanticipated haze pollution in China during the COVID-19 lockdown period. Results from the wind decomposition method show that weakened winds increased PM_2.5 concentrations in the Beijing-Tianjin area and northeastern China (e.g., by 3.19 μg/m³ in Beijing). Using the improved decomposition method, we found that the combined meteorological effect (e.g., drastically elevated humidity levels and weakened airflow) substantially increased PM_2.5 concentrations in northern China: the most substantial increases were in the Beijing-Tianjin-Hebei region (e.g., by 26.79 μg/m³ in Beijing). On excluding the meteorological effects, PM_2.5 concentrations substantially decreased across China (e.g., by 21.84 μg/m³ in Beijing), evidencing that the strict restrictions on human activities indeed decreased PM_2.5 concentrations. The unfavorable meteorological conditions, however, overwhelmed the beneficial effects of emission reduction, causing the severe haze pollution. These results indicate that the integrated meteorological effects should be considered to differentiate the meteorological and anthropogenic effects on severe air pollution.

Air quality and synergistic health effects of ozone and nitrogen oxides in response to China's integrated air quality control policies during 2015-2019

O₃ pollution had been worsening in mainland China in the past decade, posing significant human health challenges. The NO_x control would trigger increasing O₃ concentrations in response to a series of released China emission reduction policies. This study used sensitivity analysis methodology to explore the effectiveness of integrated sectoral emission control policies that have been expanded throughout China. Air quality and synergistic health effects of O₃ and NO₂ were investigated to obtain an in-depth understanding of the O₃ control, especially under a VOC-limited regime. The findings demonstrated that although the NO_x-titration effect triggered an increase in O₃, the combined health effects of two pollutants tended to improve in most regions of China under a VOC-limited regime. The region-based annual average NO₂ concentrations exhibited a larger reduction in Hong Kong (HK) than in the Pearl River Delta Economic Zone (PRD EZ). The short-term measures led to substantial health benefits for Shenzhen and HK. The sectoral emission controls demonstrated a considerable health improvement for the major PRD EZ cities. Joint national control efforts confined the domain-wide health risks below the safety line in China. National cooperative efforts in China could avoid more than 1.5-2% of the emergency hospital admissions for cardiovascular and respiratory diseases attributed to NO₂ and O₃ exposure. The observed O₃ increases due to the NO_x-titration effect for calculating the integral health effects of emission control on concentration reduction called for simultaneously strengthened controls on both NO_x and VOC in areas subject to a VOC-limited regime.

Sensitivity analysis of influence factors on multi-zone indoor airflow CFD simulation

Computational fluid dynamics (CFD) is a powerful tool for performing indoor airflow analysis. The simulation results are usually validated with measurement results for accuracy in reflecting reality. When conducting CFD for simulating air flow in a multiple-zone indoor environment with different boundary conditions in different regions, the validation of the CFD model becomes sophisticated. To improve the accuracy of the simulation, boundary conditions need to be adjusted based on how significant the influence factors are affecting the multi-zone CFD model, which few studies have been conducted on. The objective of this study is to investigate the impact of influence factors on temperature and carbon dioxide concentration distribution of a validated CFD model of a typical office floor using ANSYS Fluent. This study provides insights on how to fine-tune a complex model to reflect the actual air flow and how the air quality and human comfort in different zones on the same floor could be affected by influence factors. The influence factors investigated are: (1) size of door gaps, (2) solar radiation and (3) number and orientation of occupants. The velocity variations caused by different door gap sizes were studied for improving multi-zone simulation accuracy by adjusting door gap sizes. To study the significant impact of solar heat on multi-zone environment, the sensitivity of different regions of the office floor to solar heat amount and distribution was analyzed by conducting solar analysis under different weather conditions. Impact of occupants on temperature and carbon dioxide concentration distributions in multi-zone environment were investigated by considering different numbers and facing directions of occupants in different regions of the office floor. In addition, this study demonstrates how to modify the influence factors efficiently using building information modeling (BIM).

Meteorological factors and COVID-19 incidence in 190 countries: An observational study

Novel corona virus disease 2019 (COVID-19), which first emerged in December 2019, has become a pandemic. This study aimed to investigate the associations between meteorological factors and COVID-19 incidence and mortality worldwide. This study included 1,908,197 confirmed cases of and 119,257 deaths from COVID-19 from 190 countries between 23 January and 13 April, 2020. We used a distributed lag non-linear model with city-/country-level random intercept to investigate the associations between COVID19 incidence and daily temperature, relative humidity, and wind speed. A series of confounders were considered in the analysis including demographics, socioeconomics, geographic locations, and political strategies. Sensitivity analyses were performed to examine the robustness of the associations. The COVID-19 incidence showed a stronger association with temperature than with relative humidity or wind speed. An inverse association was identified between the COVID-19 incidence and temperature. The corresponding 14-day cumulative relative risk was 1.28 [95% confidence interval (CI), 1.20-1.36] at 5 °C, and 0.75 (95% CI, 0.65-0.86) at 22 °C with reference to the risk at 11 °C. An inverse J-shaped association was observed between relative humidity and the COVID-19 incidence, with the highest risk at 72%. A higher wind speed was associated with a generally lower incidence of COVID-19, although the associations were weak. Sensitivity analyses generally yielded similar results. The COVID-19 incidence decreased with the increase of temperature. Our study suggests that the spread of COVID-19 may slow during summer but may increase during winter.

Combined effects of increased O3 and reduced NO2 concentrations on short-term air pollution health risks in Hong Kong

The reduction of NO_x emissions in a VOC-limited region can lead to an increase of the local O₃ concentration. An evaluation of the net health effects of such pollutant changes is therefore important to ascertain whether the emission control measures effectively improve the overall protection of public health. In this study, we use a short-term health risk (added health risk or AR) model developed for the multi-pollutant air quality health index (AQHI) in Hong Kong to examine the overall health impacts of these pollutant changes. We first investigate AR changes associated with NO₂ and O₃ changes, followed by those associated with changes in all four AQHI pollutants (NO₂, O₃, SO₂, and particulate matter (PM)). Our results show that for the combined health effects of NO₂ and O₃ changes, there is a significant reduction in AR in urban areas with dense traffic, but no statistically significant changes in other less urbanized areas. The increase in estimated AR for higher O₃ concentrations is offset by a decrease in the estimated AR for lower NO₂ concentrations. In areas with dense traffic, the reduction in AR as a result of decreased NO₂ is substantially larger than the increase in AR associated with increased O₃. When additionally accounting for the change in ambient SO₂ and PM, we found a statistically significant reduction in total AR everywhere in Hong Kong. Our results show that the emission control measures resulting in NO₂, SO₂, and PM reductions over the past decade have effectively reduced the AR over Hong Kong, even though these control measures may have partially contributed to an increase in O₃ concentrations. Hence, efforts to reduce NOx, SO₂, and PM should be continued.

Effect of bromine and iodine chemistry on tropospheric ozone over Asia-Pacific using the CMAQ model

Recent studies have focused on the chemistry of tropospheric halogen species which are able to deplete tropospheric ozone (O₃). In this study, the effect of bromine and iodine chemistry on tropospheric O₃ within the annual cycle in Asia-Pacific is investigated using the CMAQ model with the newly embedded bromine and iodine chemistry and a blended and customized emission inventory considering marine halogen emission. Results indicate that the vertical profiles of bromine and iodine species show distinct features over land/ocean and daytime/nighttime, related to natural and anthropogenic emission distributions and photochemical reactions. The halogen-mediated O₃ loss has a strong seasonal cycle, and reaches a maximum of -15.9 ppbv (-44.3%) over the ocean and -13.4 ppbv (-38.9%) over continental Asia among the four seasons. Changes in solar radiation, dominant wind direction, and nearshore chlorophyll-a accumulation all contribute to these seasonal differences. Based on the distances to the nearest coastline, the onshore and offshore features of tropospheric O₃ loss caused by bromine and iodine chemistry are studied. Across a coastline-centric 400-km-wide belt from onshore to offshore, averaged maximum gradient of O₃ loss reaches 1.1 ppbv/100 km at surface level, while planetary boundary layer (PBL) column mean of O₃ loss is more moderate, being approximately 0.7 ppbv/100 km. Relative high halogen can be found over Tibetan Plateau (TP) and the largest O₃ loss (approximately 4-5 ppbv) in the PBL can be found between the western boundary of the domain and the TP. Halogens originating from marine sources can potentially affect O₃ concentration transported from the stratosphere over the TP region. As part of efforts to improve our understanding of the effect of bromine and iodine chemistry on tropospheric O₃, we call for more models and monitoring studies on halogen chemistry and be considered further in air pollution prevention and control policy.

Factors affecting variability in gaseous and particle microenvironmental air pollutant concentrations in Hong Kong primary and secondary schools

School-age children are particularly susceptible to exposure to air pollutants. To quantify factors affecting children's exposure at school, indoor and outdoor microenvironmental air pollutant concentrations were measured at 32 selected primary and secondary schools in Hong Kong. Real-time PM₁₀ , PM_2.5 , NO_2, and O₃ concentrations were measured in 76 classrooms and 23 non-classrooms. Potential explanatory factors related to building characteristics, ventilation practice, and occupant activities were measured or recorded. Their relationship with indoor measured concentrations was examined using mixed linear regression models. Ten factors were significantly associated with indoor microenvironmental concentrations, together accounting for 74%, 61%, 46%, and 38% of variations observed for PM_2.5 , PM₁₀ , O_3, and NO₂ microenvironmental concentrations, respectively. Outdoor concentration is the single largest predictor for indoor concentrations. Infiltrated outdoor air pollution contributes to 90%, 70%, 75%, and 50% of PM_2.5 , PM₁₀ , O_3, and NO₂ microenvironmental concentrations, respectively, in classrooms during school hours. Interventions to reduce indoor microenvironmental concentrations can be prioritized in reducing ambient air pollution and infiltration of outdoor pollution. Infiltration factors derived from linear regression models provide useful information on outdoor infiltration and help address the gap in generalizable parameter values that can be used to predict school microenvironmental concentrations.

Effectiveness of non-pharmaceutical interventions on COVID-19 transmission in 190 countries from 23 January to 13 April 2020

BACKGROUND

To evaluate and compare the effectiveness of four types of non-pharmaceutical interventions (NPIs) to contain the time-varying effective reproduction number (Rt) of coronavirus disease-2019 (COVID-19).

METHODS

This study included 1,908,197 confirmed COVID-19 cases from 190 countries between 23 January and 13 April 2020. The implemented NPIs were categorised into four types: mandatory face mask in public, isolation or quarantine, social distancing and traffic restriction (referred to as mandatory mask, quarantine, distancing and traffic hereafter, respectively).

RESULTS

The implementations of mandatory mask, quarantine, distancing and traffic were associated with changes (95% confidence interval, CI) of -15.14% (from -21.79% to -7.93%), -11.40% (from -13.66% to -9.07%), -42.94% (from -44.24% to -41.60%) and -9.26% (from -11.46% to -7.01%) in the Rt of COVID-19 when compared with those without the implementation of the corresponding measures. Distancing and the simultaneous implementation of two or more types of NPIs seemed to be associated with a greater decrease in the Rt of COVID-19.

CONCLUSION

Our study indicates that NPIs can significantly contain the COVID-19 pandemic. Distancing and the simultaneous implementation of two or more NPIs should be the strategic priorities for containing COVID-19.

A mechanism-based parameterisation scheme to investigate the association between transmission rate of COVID-19 and meteorological factors on plains in China

The novel coronavirus disease 2019 (COVID-19), which first emerged in Hubei province, China, has become a pandemic. However, data regarding the effects of meteorological factors on its transmission are limited and inconsistent. A mechanism-based parameterisation scheme was developed to investigate the association between the scaled transmission rate (STR) of COVID-19 and the meteorological parameters in 20 provinces/municipalities located on the plains in China. We obtained information on the scale of population migrated from Wuhan, the world epicentre of the COVID-19 outbreak, into the study provinces/municipalities using mobile-phone positioning system and big data techniques. The highest STRs were found in densely populated metropolitan areas and in cold provinces located in north-eastern China. Population density had a non-linear relationship with disease spread (linearity index, 0.9). Among various meteorological factors, only temperature was significantly associated with the STR after controlling for the effect of population density. A negative and exponential relationship was identified between the transmission rate and the temperature (correlation coefficient, -0.56; 99% confidence level). The STR increased substantially as the temperature in north-eastern China decreased below 0 °C (the STR ranged from 3.5 to 12.3 when the temperature was between -9.41 °C and -13.87 °C), whilst the STR showed less temperature dependence in the study areas with temperate weather conditions (the STR was 1.21 ± 0.57 when the temperature was above 0 °C). Therefore, a higher population density was linearly whereas a lower temperature (<0 °C) was exponentially associated with an increased transmission rate of COVID-19. These findings suggest that the mitigation of COVID-19 spread in densely populated and/or cold regions will be a great challenge.

Estimations of Long-Term nss-SO42- and NO3- Wet Depositions over East Asia by Use of Ensemble Machine-Learning Method

Wet deposition of non-sea-salt sulfate (nss-SO₄^2-) and nitrate (NO₃^-), derived from anthropogenic emissions of SO₂ and NO_x, exerts adverse effects on ecosystems. In this work, an ensemble back-propagation neural network was proposed to estimate the long-term wet depositions of nss-SO₄^2- (2005-2017) and NO₃^- (2001-2014) over East Asia in 10 km resolution. The R² values for the 10-fold cross-validation of annual wet depositions of nss-SO₄^2- and NO₃^- were 0.90 and 0.85, respectively. The hotspots of the wet deposition of these two acidic species span southwestern, central, and eastern China. The molar ratio of NO₃^- to nss-SO₄^2- increased in 10 out of 12 analyzed East Asian countries from 2005 to 2014, which indicates that the acidity in rainwater shifts from the sulfur type to nitrogen type over most of the regions. The wet deposition on the four ecosystems (forest, grassland, cropland, and freshwater body) was also analyzed. Results showed that the nss-SO₄^2- wet deposition on 25.5% of freshwater bodies in 2015 and NO₃^- wet deposition on 21.7% of grassland in 2014 exceeded the ecosystem empirical critical loads (25 kg/ha sulfate and 2 kg N/ha) in East Asia. Thus, more stringent and regionally collaborative sulfur and nitrogen emission-control measures are urgently needed to protect the ecosystem of East Asia.

Assessing PM2.5 emissions in 2020: The impacts of integrated emission control policies in China

Problems with PM_2.5 pollution in the Pearl River Delta (PRD) have been significantly reduced since the Chinese government released a series of emission control policies including the strengthened controls in the 13^th Five-Year Plan. This study assessed the efficacy of emission control measures using the Community Multiscale Air Quality (CMAQ) model to provide data-driven support to government decision making, which is becoming increasingly important. This study aimed to quantitatively evaluate the integrated results of proposed policies for controlling PM_2.5 concentrations. Accordingly, the regional 2015 emission inventory was modified with recently released government data for the PRD, and scenarios for four dynamical emission-reduction policies (S1-S4) were explored. The results show that all four proposed control measures can help to reduce PM_2.5 concentrations throughout Hong Kong (HK), Macao, and the PRD economic zone (PRD EZ) by 2020. In all cases, reductions in PM_2.5 concentrations were larger over PRD EZ than over HK. For HK, the predicted annual concentrations of PM_2.5 were less than 20 μg/m³ for S1-S3 and less than 15 μg/m³ for S4. For Macao, the predicted annual concentrations of PM_2.5 were less than 25 μg/m³ for S1 and less than 15 μg/m³ up to S3. Regionally, HK had the lowest PM_2.5 levels, and the area around Foshan had the highest. Controlling the sources of air pollution (i.e., industry, transport, power production, and other sources) within PRD can get most of the PRD EZ region to below 35 μg/m³. Similar national air quality management efforts could reduce PM_2.5 levels to less than 25 μg/m³ in the PRD EZ and less than 15 μg/m³ in HK. Control measures in S1 led to significant improvement in Shenzhen and HK, but the S3 option brought the greatest improvement for PRD EZ and Macao. The S4 policy option led to substantial reductions, particularly for HK.

Does fine particulate matter (PM2.5) affect the benefits of habitual physical activity on lung function in adults: a longitudinal cohort study

BACKGROUND

Physical activity (PA) increases a person's inhalation of air pollutants due to greater ventilation, possibly leading to larger adverse health effects. This study aims to investigate the combined effects of long-term exposure to fine particulate matter (PM_2.5) and habitual PA on lung function in adults.

METHODS

This was a longitudinal cohort study that included 278,065 Taiwan residents with an age of 20 years old or above who joined a standard medical screening programme between 2001 and 2014. Each participant received at least one medical examination (including spirometric, blood, and urinary tests and a standard self-administered questionnaire survey) during the study period. We estimated the 2-year average PM_2.5 concentrations at each participant's address using a new physical model based on observational data. Information on the participants' PA was collected using the standard self-administrated questionnaire. Generalised linear mixed models were used to investigate the combined effects of PM_2.5 and PA on pulmonary function. We also performed stratified analyses by different levels of PM_2.5 exposure and habitual PA.

RESULTS

Each 10 MET-h increase in PA was associated with a higher level of 0.20%, 0.16%, and 0.19% in forced vital capacity (FVC), forced expiratory volume in the first second (FEV₁), and maximum mid-expiratory flow (MMEF), respectively, after adjusting for PM_2.5 exposure and a wide range of covariates including age, sex education, body mass index, lifestyles, and health conditions. Each 10 μg/m³ increase in PM_2.5 was associated with a lower FVC, FEV₁, and MMEF (2.43%, 2.78% and 3.10%, respectively). Negative interactions were observed, and PM_2.5 exposure was associated with a greater reduction in lung function among the participants with higher PA levels.

CONCLUSIONS

We found significant negative interaction effects between long-term exposure to PM_2.5 and habitual PA, suggesting that the increased intake of PM_2.5 due to PA may attenuate the benefits of habitual PA on lung function. However, the PA benefits generally remained stable at different stratum of PM_2.5 in the stratified analyses, and habitual PA may still be recommended to people residing in relatively polluted regions.

Long-term exposure to ambient fine particles and gastrointestinal cancer mortality in Taiwan: A cohort study

BACKGROUND

Information on the association between long-term exposure to PM_2.5 and gastrointestinal cancer mortality is scarce.

OBJECTIVES

This study investigated the association between long-term exposure to PM_2.5 and deaths from gastrointestinal cancer and its subtypes in adults in Taiwan.

METHODS

A total of 385,650 Taiwanese adults (≥18 years old) jointed a standard medical examination program between 2001 and 2014 and were followed up until 2016. Their vital data were obtained from the National Death Registry maintained by the Ministry of Health and Welfare in Taiwan. We estimated the ambient PM_2.5 concentration at individual's address utilising a satellite-based spatiotemporal model at a resolution of 1 km². Cox proportional hazard regression model was used to investigate the associations between ambient PM_2.5 and deaths from gastrointestinal, stomach, colorectal and liver cancers.

RESULTS

We found that each 10 µg/m³ increase in PM_2.5 was associated with an increased hazard risk (HR) of 1.09 (95% confidence interval (CI): 1.03-1.16) and 1.13 (95%CI: 1.02-1.24) in deaths from gastrointestinal and liver cancers, respectively. The association between PM_2.5 and death from colorectal cancer was marginally statistically significant [HR: 1.13 (95%CI: 1.00-1.26)]. We did not find significant associations between PM_2.5 and mortality from stomach cancer.

CONCLUSIONS

Long-term exposure to ambient PM_2.5 was associated with an increased risk of deaths from gastrointestinal cancers, liver cancer and also potentially colorectal cancer. Air pollution control strategies are necessary to reduce the burden of gastrointestinal cancer.

A novel framework for decomposing PM2.5 variation and demographic change effects on human exposure using satellite observations

Human exposure to PM_2.5, represented by population-weighted mean PM_2.5 concentration (c_ρ), declines under three conditions: (1) mean PM_2.5 concentration declines, (2) PM_2.5 concentration within urban areas goes through more of a decrease than within rural areas, or (3) city planning relocates people into cleaner areas. Decomposing these effects on human exposure is essential to guide future environmental policies. The lack of ground PM_2.5 observations limits the assessment of human exposure to PM_2.5 over China. This study proposed a novel diagnostic framework using satellite observations to decompose the variation in c_ρ resulting from change in the mean PM_2.5 concentration, spatial difference in PM_2.5 change, and demographic change. In this framework, we decomposed c_ρ into mean PM_2.5 concentration (c₀) and pollution-population-coincidence induced PM_2.5 exposure (PPCE). We then used this framework to decompose the variation in c_ρ over China within three recent Five-Year Plans (FYPs) (2001-2015). The results showed that the decline in c₀ reduced c_ρ in most provinces within the eleventh and twelfth FYPs. The spatial difference in PM_2.5 change reduced the PPCE and c_ρ in most provinces within the tenth and twelfth FYPs, with the most substantial reduction rate of -3.64 μg m^-3·yr^-1 in Tianjin within the twelfth FYP. Rural-to-urban migration resulting from rapid urbanization, however, increased the PPCE and c_ρ (by as much as 0.22 μg m^-3·yr^-1) in all provinces except Taiwan within all three FYPs. The demographic change reduced c_ρ in Taiwan because of the migration of population into less polluted areas. To better reduce human exposure, it is recommended that control efforts further target populous residential areas and urbanization planning relocates people into less polluted areas. Our decomposition framework paves a new way to decompose the human exposure to other air pollutants in China and other regions.

Long-Term Exposure to Ambient Fine Particulate Matter (PM2.5) and Lung Function in Children, Adolescents, and Young Adults: A Longitudinal Cohort Study

BACKGROUND

The association between long-term exposure to ambient fine particulate matter with aerodynamic diameter ≤2.5μm (PM2.5) and lung function in young people remains uncertain, particularly in Asia, where air pollution is generally a serious problem.

OBJECTIVES

This study investigated the association between long-term exposure to ambient PM2.5 and lung function in Taiwanese children, adolescents, and young adults.

METHODS

This study comprised 24,544 participants 6-24 years of age, with 33,506 medical observations made between 2000 and 2014. We used a spatiotemporal model to estimate PM2.5 concentrations at participants' addresses. Spirometry parameters, i.e., forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), and maximum midexpiratory flow (MMEF), were determined. A generalized linear mixed model was used to examine the associations between long-term exposure to ambient PM2.5 and lung function. The odds ratios (ORs) of poor lung function were also calculated after adjusting for a range of covariates.

RESULTS

Every 10-μg/m3 increase in the 2-y average PM2.5 concentration was associated with decreases of 2.22% [95% confidence interval (CI): -2.60, -1.85], 2.94 (95% CI: -3.36, -2.51), and 2.79% (95% CI: -3.15, -2.41) in the FVC, FEV1, and MMEF, respectively. Furthermore, it was associated with a 20% increase in the prevalence of poor lung function (OR: 1.20; 95% CI: 1.12, 1.29).

CONCLUSIONS

Two-year ambient PM2.5 concentrations were inversely associated with lung function and positively associated with the prevalence of poor lung function in children, adolescents, and young adults in Taiwan. https://doi.org/10.1289/EHP5220.

A feasible experimental framework for field calibration of portable light-scattering aerosol monitors: Case of TSI DustTrak

Portable light-scattering aerosol monitors (PLSAMs) can supplement existing air quality monitoring networks through measuring air pollutant exposure concentrations at high spatiotemporal resolution. However, data collected by PLSAMs are often subject to the simplicity of measurement principle which may lead to errors compared to the regulatory data observed at fixed-site air quality monitoring stations. The main objective of this study was to develop a feasible experimental framework to assess the influence of key factors (e.g., relative humidity (RH)) on the performance of PLSAMs in the real-world conditions. Following the proposed framework, the accuracy and precision of the TSI DustTrak aerosol monitor were evaluated through side-by-side comparison with the stationary reference instruments (SRIs) while taking characteristics of particles, RH, and the concentration range into consideration. DustTrak generally demonstrated low accuracy but high precision in measuring PM_2.5 concentrations at the two selected stations. Three calibration models between DustTrak and the SRIs were used to bias correct the DustTrak PM_2.5 measurements. The RH-adjusted linear regression calibration method led to better calibration results than the simple linear regression method and the RH-adjusted empirical method, with CV R² values higher than 0.97, root mean square error less than 1.0 μg/m³, and accuracy values at 3% for two DustTraks. The proposed experimental framework can be extended to field calibration of various types of PLSAMs, and the obtained calibration results can promote a more accurate investigation of particle air pollution using these PLSAMs.

To what extent can the below-cloud washout effect influence the PM2.5? A combined observational and modeling study

The below-cloud washout (BCW) effect on PM_2.5 concentration during periods of rain is still a subject of debate. Existing BCW schemes for PM_2.5 have large deficiencies that influence its simulation in 3D chemical transport models (CTMs). In this study, a 7-year dataset with high temporal resolution (in minutes) sampled from a pristine rural site is used to calculate the BCW coefficient during the rain events. The data used for the BCW coefficient calculation cover a wide range of rain intensity from 2 mm h^-1 to 60 mm h^-1. The BCW coefficient linearly correlates with the rain intensity, with a correlation coefficient of 0.82. The coefficient has a magnitude of 10^-5 to 10^-4 s^-1 when the rain intensity ranges from 1 to 40 mm h^-1. After implementing the updated BCW scheme into the Comprehensive Air Quality Model with Extensions (CAMx) model, the performance of PM_2.5 simulation improves for the two months of heavy rain. Apart from the CAMx model, our scheme can be easily implemented into other 3D CTMs to improve PM_2.5 simulation during rainy days. The BCW effect can clean around 10-40% of the PM_2.5 over our study region, which can help to reduce the PM_2.5 exposure level for residents, and the health burdens caused by this pollutant can thus be reduced. Rainmaking is a potential way to decrease PM_2.5 concentration, but it cannot be the key method to reduce the PM_2.5 level to the standard during episodic cases (e.g., >200 μg/m³).

Dynamic Changes in Long-Term Exposure to Ambient Particulate Matter and Incidence of Hypertension in Adults

Many countries dedicated in mitigation of air pollution in the past several decades. However, little is known about how air quality improvement affects health. Therefore, we conducted current study to investigate dynamic changes in long-term exposure to ambient particulate matter (PM_2.5) and incidence of hypertension in a large longitudinal cohort. We recruited 134 978 adults aged 18 years or above between 2001 and 2014. All the participants received a series of standard medical examinations, including measurements of blood pressure. The PM_2.5 concentration was estimated using a satellite-based spatiotemporal model at a high resolution (1×1 km²). The change in long-term exposure to PM_2.5 (ΔPM_2.5) was defined as the difference between the values measured during follow-up and during the immediately preceding visit, and a negative value indicated an improvement in PM_2.5 air quality. Time-varying Cox model was used to examine the associations between ΔPM_2.5 and the development of hypertension. The results show that PM_2.5 concentrations increased in 2002, 2003, and 2004, but began to decrease in 2005. Every 5 µg/m³ change in exposure to PM_2.5 (ie, a ΔPM_2.5 of 5 µg/m³) was associated with a 16% change in the incidence of hypertension (hazard ratio, 0.84; 95% CI, 0.82-0.86). Both stratified and sensitivity analyses generally yielded similar results. We found that an improvement in PM_2.5 exposure is associated with a decreased incidence of hypertension. Our findings demonstrate that air pollution mitigation is an effective strategy to reduce the risk of cardiovascular disease.

Differences in concentration and source apportionment of PM2.5 between 2006 and 2015 over the PRD region in southern China

During China's 11th Five Year Plan (FYP) and 12th FYP (2006-2015), a series of air pollution control measures was implemented in the Pearl River Delta (PRD) region. Therefore, it is vital to determine how the concentration and sources of fine particulate matter (PM_2.5) in this region changed between 2006 and 2015. In this work, using 2006 and 2015 emission inventories, the concentration and source apportionment of PM_2.5 were simulated using the Weather Research and Forecast - Comprehensive Air Quality Model with Extensions (WRF-CAMx) for January, April, July and October in the PRD region. The PM_2.5 in 10 cities and the contributions made by sources in six major categories were tracked using the Particulate Source Apportionment Technology (PSAT) module. The results showed that the PM_2.5 concentration was lower across the entire PRD region in the 2015 emission scenario than in the 2006 scenario, and that the degree of this reduction exceeded 40 μg/m³ in some places. The PM_2.5 contributed by mobile emissions decreased the most, especially in Guangzhou, Foshan and Shenzhen, where mobile contributions decreased from 15.0, 17.9 and 13.0 μg/m³ in 2006 to 2.6, 3.1 and 4.1 μg/m³ in 2015, respectively. The PM_2.5 contributed by power plants also decreased, and in Dongguan and Guangzhou, the extent of this reduction reached 2.5 and 3.4 μg/m³ respectively. However, due to an increase in industrial production and population size, the PM_2.5 from industrial point sources and area sources also increased between 2006 and 2015 in some of the cities. Investigation of the source apportionment for city centers yielded similar results. In addition to emissions within the PRD region, outside-PRD non-local contribution is still an important PM_2.5 contributor. Hence, more stringent policies for controlling industrial and area sources and deepening province-to-province cooperation are urgently needed as the next step in PM_2.5 control.

Long-term exposure to ambient fine particulate matter (PM2.5) and incident type 2 diabetes: a longitudinal cohort study

AIMS/HYPOTHESIS

Information on the associations of long-term exposure to fine particulate matter (with an aerodynamic diameter less than 2.5 μm; PM_2.5) with the development of type 2 diabetes is scarce, especially for south-east Asia, where most countries are experiencing serious air pollution. This study aimed to investigate the long-term effects of exposure to ambient PM_2.5 on the incidence of type 2 diabetes in a population of Taiwanese adults.

METHODS

A total of 147,908 participants without diabetes, at least 18 years of age, were recruited in a standard medical examination programme between 2001 and 2014. They were encouraged to take medical examinations periodically and underwent at least two measurements of fasting plasma glucose (FPG). Incident type 2 diabetes was identified as FPG ≥7 mmol/l or self-reported physician-diagnosed diabetes in the subsequent medical visits. The PM_2.5 concentration at each participant's address was estimated using a satellite-based spatiotemporal model with a resolution of 1 × 1 km². The 2 year average of PM_2.5 concentrations (i.e. the year of and the year before the medical examination) was treated as an indicator of long-term exposure to ambient PM_2.5 air pollution. We performed Cox regression models with time-dependent covariates to analyse the long-term effects of exposure to PM_2.5 on the incidence of type 2 diabetes. A wide range of covariates were introduced in the models to control for potential effects, including age, sex, education, season, year, smoking status, alcohol drinking, physical activity, vegetable intake, fruit intake, occupational exposure, BMI, hypertension and dyslipidaemia (all were treated as time-dependent covariates except for sex).

RESULTS

Compared with the participants exposed to the first quartile of ambient PM_2.5, participants exposed to the second, third and fourth quartiles of ambient PM_2.5 had HRs of 1.28 (95% CI 1.18, 1.39), 1.27 (95% CI 1.17, 1.38) and 1.16 (95% CI 1.07, 1.26), respectively, for the incidence of type 2 diabetes. Participants who drank occasionally or regularly (more than once per week) or who had a lower BMI (<23 kg/m²) were more sensitive to the long-term effects of exposure to ambient PM_2.5.

CONCLUSIONS/INTERPRETATION

Long-term exposure to ambient PM_2.5 appears to be associated with a higher risk of developing type 2 diabetes in this Asian population experiencing high levels of air pollution.

Application of air parcel residence time analysis for air pollution prevention and control policy in the Pearl River Delta region

In this study, the concept of air parcel residence time was raised and the APRT was investigated to study its potential application in air pollution prevention and control in the Pearl River Delta (PRD) region. The APRT in the PRD region was defined as the total period for which an air parcel stays within the PRD region. The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used to calculate the hourly APRT in 2012, 2014, and 2015 based on forward trajectories from 16,720 starting locations. The seasonal APRT results revealed that long APRT was mainly distributed in southern PRD in the summer half year, but in northeastern PRD in the winter half year. This is related to the prevailing wind directions in the summer and winter monsoons. Moreover, the comparison of APRT in different years revealed that the dispersion condition was relatively poor in fall in 2012 and throughout 2014 but was relatively favorable in 2015, which also corresponded to the pollutant concentrations. The APRT calculated from regional air pollution days indicated that the emission reduction strategy should be implemented in the key areas, namely the eastern and central Guangzhou, western Huizou, and the border between Foshan and Jiangmen, and the construction of new factories should not be allowed in these areas. Compared to the APRT, which was investigated to trace the air pollution source, population exposure to air parcels (PEAP) was investigated to orient the influence of path-and-time-weighted sources to population. Consequently, a high PEAP was found to be distributed mainly in the central Guangzhou and Shenzhen and scattered in other urban areas.

Assessing the Effect of the Long-Term Variations in Aerosol Characteristics on Satellite Remote Sensing of PM2.5 Using an Observation-Based Model

Variations in aerosol characteristics play an essential role in satellite remote sensing of PM_2.5 concentrations. The lack of measurement of aerosol characteristics, however, limits the assessment of their effects. This study presented an observation-based model that directly considered the effects of aerosol characteristics. In this model, we used an integrated humidity coefficient (γ') and an integrated reference value ( K) to delineate the effects of aerosol characteristics. We then investigated the effects of the long-term variations in aerosol characteristics on satellite remote sensing of PM_2.5 concentration in Hong Kong from 2004 to 2012. The results show that the γ' value peaked in 2009 because the percentages of highly hygroscopic components (e.g., sulfate and nitrate) in aerosols reached their peaks. The K value increased from 2004 to 2011 because of the increasing percentages of strong light-extinction components (e.g., organic matter) and the decreasing fine mode fraction in aerosols. The accuracy of PM_2.5 retrieval improved greatly after accounting for the long-term variations in aerosol characteristics (e.g., correlation coefficient increased from 0.56 to 0.80). The results underscore the need to incorporate the variations in aerosol characteristics in the PM_2.5 estimation models.