Exposure-Response to High PM 2.5 Levels for Cardiovascular Events in High-risk Older Adults in Taiwan.

Background: Multiple studies from countries with relatively lower PM 2.5 level demonstrated that acute and chronic exposure even at lower than recommended level, e.g., 9 µg/m 3 in the US increased the risk of cardiovascular (CV) events. However, limited studies using individual level data exist from countries with a wider range of PM levels to illustrate shape of the exposure-response curve throughout the range including > 20 µg/m 3 PM 2·5 concentrations. Taiwan with its policies reduced PM 2.5 over time provide opportunities to illustrate the dose response curves and how reductions of PM 2.5 over time correlated with CV events incidence in a nationwide sample. Methods: Using data from the 2009-2019 Taiwan National Health Insurance Database linked to nationwide PM2.5 data. We examined the shape and magnitude of the exposure-response curve between seasonal average PM 2·5 level and CV events-related hospitalizations among older adults at high-risk for CV events. We used history-adjusted marginal structural models including potential confounding by individual demographic factors, baseline comorbidities, and health service measures. To quantify the risk below and above 20 µg/m 3 we conducted stratified Cox regression. We also plotted PM 2.5 and CV events from 2009-2019 as well as average temperature as a comparison. Findings: Using the PM 2.5 concentration <15 µg/m 3 (Taiwan regulatory standard) as a reference, the seasonal average PM 2.5 concentration (15-23.5µg/m 3 and > 23.5 µg/m 3 ) were associated with hazard ration of 1.13 (95%CI 1.09-1.18) and 1.19 (95%CI 1.14-1.24), 1.07 (95%CI 1.03-1.11) and 1.14 (95%CI 1.10-1.18), 1.22 (95%CI 1.08-1.38) and 1.31 (95%CI 1.16-1.48), 1.04 (95%CI 0.98-1.10) and 1.10 (95%CI 1.04-1.16) respectively for HF, IS/TIA,PE/DVT and MI/ACS. A nonlinear relationship between PM 2·5 and CV events outcomes was observed at PM 2·5 levels above 20 µg/m 3 . Interpretation: A nonlinear exposure-response relationship between PM2·5 concentration and the incidence of cardiovascular events exists when PM2.5 is higher than the levels recommended by WHO Air Quality Guidelines. Further lowering PM2·5 levels beyond current regulatory standards may effectively reduce the incidence of cardiovascular events, particularly HF and DVT, and can lead to tangible health benefits in high-risk elderly population.

Ambient Heat and Risk of Serious Hypoglycemia in Older Adults With Diabetes Using Insulin in the U.S. and Taiwan: A Cross-National Case-Crossover Study.

OBJECTIVE: To measure the association between ambient heat and hypoglycemia-related emergency department visit or hospitalization in insulin users. RESEARCH DESIGN AND METHODS: We identified cases of serious hypoglycemia among adults using insulin aged ≥65 in the U.S. (via Medicare Part A/B/D-eligible beneficiaries) and Taiwan (via National Health Insurance Database) from June to September, 2016-2019. We then estimated odds of hypoglycemia by heat index (HI) percentile categories using conditional logistic regression with a time-stratified case-crossover design. RESULTS: Among ∼2 million insulin users in the U.S. (32,461 hypoglycemia case subjects), odds ratios of hypoglycemia for HI >99th, 95-98th, 85-94th, and 75-84th percentiles compared with the 25-74th percentile were 1.38 (95% CI, 1.28-1.48), 1.14 (1.08-1.20), 1.12 (1.08-1.17), and 1.09 (1.04-1.13) respectively. Overall patterns of associations were similar for insulin users in the Taiwan sample (∼283,000 insulin users, 10,162 hypoglycemia case subjects). CONCLUSIONS: In two national samples of older insulin users, higher ambient temperature was associated with increased hypoglycemia risk.

Prenatal and postnatal exposure to heavy metals in PM2.5 and autism spectrum disorder.

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders, and its incidence is increasing over time. Although several environmental factors have been suspected to be risk factors for ASD, studies on the effects of airborne heavy metals on newly developed ASD are still limited. We conducted a large birth cohort study of 168,062 live term births in Taichung during 2004-2011 to assess the association of heavy metals in particulate matter with an aerodynamic diameter less than 2.5 µm (PM2.5) with ASD, and identify sensitive time windows during prenatal and postnatal periods. Heavy metals, including arsenic (As), cadmium (Cd), mercury (Hg), and lead (Pb) in PM2.5, were estimated using the Weather Research and Forecasting/Chem (WRF/Chem), inserted from the top 75 emission sources for the module. The association between childhood ASD and 4 metals were analyzed from pregnancy to 9 months after birth. The Cox proportional hazard model with a distributed lag nonlinear model (DLNM) was used to estimate the association between heavy metals in PM2.5 and ASD. We identified 666 incident ASD cases in 168,062 participants. A positive association between Hg and ASD was found at 9 months after birth (Hazard Ratio: 1.63; 95% CI: 1.13-2.36). According to the DLNM, there was an increased risk of exposure to Hg during 10-25 weeks after birth, and decreased risk of exposure to Hg during gestational weeks 4-6. Exposure to As and Hg on the risk of ASD were significantly stronger in low birth weight infants (<2500 g) than in those of birth weight ≥2500 g during postnatal period. Postnatal exposure to Hg in PM2.5 may associate with increased ASD incidence. Infants with low birth weight and exposure to As and Hg in PM2.5 are more likely to develop ASD.

A numerical study of reducing the concentration of O3 and PM2.5 simultaneously in Taiwan.

Since the 24-hr PM2.5 (particle aerodynamic diameter less than 2.5 µm) concentration standard was regulated in Taiwan in 2012, the PM2.5 concentration has been decreasing year by year, but the ozone (O3) concentration remains almost the same. In particular, the daily maximum 8-hr average O3 (MDA8 O3) concentration frequently exceeds the standard. The goal of this study is to find a solution for reducing PM2.5 and O3 simultaneously by numerical modeling. After the Volatile Organic Compounds (VOCS)-limited and nitrogen oxides (NOX)-limited areas were defined in Taiwan, then, in total, 50 scenarios are simulated in this study. In terms of the average in Taiwan, the effect of VOCS emission reduction is better than that of NOX on the decrease in PM2.5 concentration, when the same reduction proportion (20%, 40%) is implemented. While the effect of further NOX emission reduction (60%) will exceed that of VOCS. The decrease in PM2.5 is proportional to the reduction in precursor emissions such as NOX, VOCS, sulfur dioxides (SO2), and ammonia (NH3). The lower reduction of NOX emission for whole Taiwan caused O3 increases on average but higher reduction can ease the increase, which suggests the implement of NOX emission reductions must be cautious. When comparing administrative jurisdictions in terms of grids, districts/towns, and cities/counties, it was found that controlling NOX and VOCS at a finer spatial resolution of control units did not benefit the decrease in PM2.5 but did benefit the decrease in O3. The enhanced O3 control strategies obviously cause a higher decrease of O3 throughout Taiwan due to NOX and VOCS emission changes when they are implemented in the right places. Finally, three sets of short-term and long-term goals of controlling PM2.5 and O3 simultaneously are drawn from the comprehensive rankings for all simulated scenarios, depending on whether PM2.5 or O3 control is more urgent. In principle, the short-term scenarios could be ordinary or enhanced version of O3 decrease with lower NOX/VOCS emissions, while the long-term scenario is enhanced version of O3 decrease plus high emission reductions for all precursors.

Deep neural networks for spatiotemporal PM2.5 forecasts based on atmospheric chemical transport model output and monitoring data.

Reliable long-horizon PM2.5 forecasts are crucial and beneficial for health protection through early warning against air pollution. However, the dynamic nature of air quality makes PM2.5 forecasts at long horizons very challenging. This study proposed a novel machine learning-based model (MCNN-BP) that fused multiple convolutional neural networks (MCNN) with a back-propagation neural network (BPNN) for making spatiotemporal PM2.5 forecasts for the next 72 h at 74 stations covering the whole Taiwan simultaneously. Model configuration involved an ensemble of massive hourly air quality and meteorological monitoring datasets and the existing publicly-available PM2.5 simulated (forecasted) datasets from an atmospheric chemical transport (ACT) model. The proposed methodology collaboratively constructed two CNNs to mine the observed data (the past) and the forecasted data from ACT (the future) separately. The results showed that the MCNN-BP model could significantly improve the accuracy of spatiotemporal PM2.5 forecasts and substantially reduce the forecast biases of the ACT model. We demonstrated that the proposed MCNN-BP model with effective feature extraction and good denoising ability could overcome the curse of dimensionality and offer satisfactory regional long-horizon PM2.5 forecasts. Moreover, the MCNN-BP model has considerably shorter computational time (5 min) and lower computational load than the compute-intensive ACT model. The proposed approach hits a milestone in multi-site and multi-horizon forecasting, which significantly contributes to early warning against regional air pollution.

Isotopic signatures and source apportionment of Pb in ambient PM2.5.

Particulate lead (Pb) is a primary air pollutant that affects society because of its health impacts. This study investigates the source sectors of Pb associated with ambient fine particulate matter (PM2.5) over central-western Taiwan (CWT) with new constraints on the Pb-isotopic composition. We demonstrate that the contribution of coal-fired facilities is overwhelming, which is estimated to reach 35 ± 16% in the summertime and is enhanced to 57 ± 24% during the winter monsoon seasons. Moreover, fossil-fuel vehicles remain a major source of atmospheric Pb, which accounts for 12 ± 5%, despite the current absence of a leaded gasoline supply. Significant seasonal and geographical variations in the Pb-isotopic composition are revealed, which suggest that the impact of East Asian (EA) pollution outflows is important in north CWT and drastically declines toward the south. We estimate the average contribution of EA outflows as accounting for 35 ± 15% (3.6 ± 1.5 ng/m3) of the atmospheric Pb loading in CWT during the winter monsoon seasons.

Impacts of offshore wind farms on the atmospheric environment over Taiwan Strait during an extreme weather typhoon event.

Wind is one of the cleanest renewable energy resources. Through the "Thousand Wind Turbines Project", Taiwan is planning to increase the proportion of power generation from renewable energy and has set a target of 5.7 GW for offshore wind by 2025. The effects of future offshore wind farms (OWFs) over the Taiwan Strait on the atmospheric environment have not been evaluated. This study examined the potential effects of proposed OWFs on the atmospheric environment if the OWFs had existed during Tropical Storm Haitang (2017) by using Weather Research and Forecasting (WRF) model. A small set of ensemble simulations was conducted for studying the sensitivity of the ambient conditions in the region to the wind farm locations, the number and density of the turbines, and the initial time of simulations. Following the landfall and northward movement of Tropical Storm Haitang, a series of complex interactions between the typhoon circulation and the wind farm emerged, including small time slots of wake effect and mountain blocking effect. The combination of these rapidly changing OWFs-related effects contributed to a weak reduction in precipitation (- 1.08 mm) and hub-height wind speed (- 0.25 m s-1), as well as minimal warming near the surface (+ 0.13 °C) over southern Taiwan.

Ambient viral and bacterial distribution during long-range transport in Northern Taiwan.

Long-range transport (LRT) reportedly carries air pollutants and microorganisms to downwind areas. LRT can be of various types, such as dust storm (DS) and frontal pollution (FP); however, studies comparing their effects on bioaerosols are lacking. This study evaluated the effect of LRT on viral and bacterial concentrations in Northern Taiwan. When LRT occurred and possibly affected Taiwan from August 2013 to April 2014, air samples (before, during, and after LRT) were collected in Cape Fugui (CF, Taiwan's northernmost point) and National Taiwan University (NTU). Reverse-transcription quantitative polymerase chain reaction (RT-qPCR) was applied to quantify influenza A virus. qPCR and qPCR coupled with propidium monoazide were, respectively, used to quantify total and viable bacteria. Types and occurrence of LRT were confirmed according to the changing patterns of meteorological factors and air pollution, air mass sources (HYSPLIT model), and satellite images. Two Asian DS and three FP cases were included in this study. Influenza A virus was detected only on days before and during FP occurred on January 3-5, 2014, with concentrations of 0.87 and 10.19 copies/m3, respectively. For bacteria, the increase in concentrations of total and viable cells during Asian DSs (17-19 and 25-29 November 2013) was found at CF only (from 3.13 to 3.40 and from 2.62 to 2.85 log copies/m3, respectively). However, bacterial levels at NTU and CF both increased during FP and lasted for 2 days after FP. In conclusion, LRT increased the levels of influenza A virus and bacteria in the ambient air of Northern Taiwan, particularly at CF. During and 2 days (at least) after LRT, people should avoid outdoor activities, especially in case of FP.

Combined exposure to heavy metals in PM2.5 and pediatric asthma.

BACKGROUND: Asthma is the most common chronic allergic disease in children; it affects more than 300 million people worldwide. Information on the association between exposure to ambient heavy metals and incidence of pediatric asthma is limited. OBJECTIVE: We sought to evaluate the effects of heavy metals during pregnancy and infancy periods with asthma and identify a sensitive time window, clarifying the effect of ambient heavy metals on lung development. METHODS: A total of 171,281 children, who were born from 2004 to 2011 in Taichung City, were followed until 2014. Concentrations of ambient heavy metals such as arsenic (As), cadmium (Cd), mercury (Hg), and lead (Pb) were obtained from the Weather Research and Forecasting/Chem model, considering the top 75 emission sources in Taiwan. The distributed lag nonlinear model was used to investigate the relationship between combined exposure to heavy metals in 2.5 µm particulate matter and asthma in pregnant women and 1-year-old infants. RESULTS: We identified 31,277 new asthma cases from the birth cohort. After adjustment for socioeconomic status, maternal age, maternal atopy, maternal anemia, and maternal kidney disease, distributed lag nonlinear model results revealed positive associations of asthma with exposure to Pb during gestational weeks 1 to 14 and 21 to 40, and 1 to 3 weeks after birth. Regarding the sensitivity analyses, coexposure to Pb and As, coexposure to Pb and Cd, and coexposure to Pb and Hg were positively associated with asthma onset as well. CONCLUSIONS: Our study suggested that combined exposure to Pb with As, Cd, and Hg during early and late gestational weeks was associated with the incidence of pediatric asthma.

The 2018 summer heatwaves over northwestern Europe and its extended-range prediction.

This study investigated the drivers and extended-range prediction of the mid-July to early August 2018 heatwaves over northwestern Europe, focusing on regional heatwave events over Scandinavia (SC) and Western Europe (WE). The persistent blocking regime (BL) was the most influential contributor for the 2018 heatwave over SC, and both the Atlantic Low regime (AL) and North Atlantic Oscillation (NAO) were secondary contributors for the heatwave, but with different effect directions. The major contributor to the heatwave over WE was AL. These causal relationships remained valid when the evolution of warm spells was considered. A multi-model ensemble of real-time forecasts from the subseasonal to seasonal (S2S) database captured the evolution of the warm spells over SC and WE up to 3 weeks in advance. However, the predictions of heatwave occurrence and significance for the two regions are unsatisfactory. BL and AL can be predicted 2 weeks in advance, resulting in the successful predictions of warm spells over SC and WE. Although variations in Azores High and NAO were captured in the forecasts, their contribution to the warm spells remains unclear.

Epidemiologic features of shigellosis and associated climatic factors in Taiwan.

The consistent, sporadic transmission of shigellosis in Taiwan necessitates an exploration of risk factors for the occurrence of shigellosis. The purpose of this study was to study the epidemiologic characteristics and the relationship between climatic factors and the incidence of shigellosis in Taiwan. We collected data from cases of shigellosis reported to the Taiwan Centers for Disease Control (Taiwan CDC) from 2001 to 2016. Climatic data were obtained from the Taiwan Central Weather Bureau. The relationships between weather variability and the incidence of shigellosis in Taiwan were determined via Poisson regression analyses. During the 16-year study period, a total of 4171 clinical cases of shigellosis were reported to the Taiwan CDC. Among them, 1926 (46.2%) were classified as confirmed cases. The incidence of shigellosis showed significant seasonality, with the majority of cases occurring in summertime (for oscillation, P < .001). The number of shigellosis cases started to increase when temperatures reached 21°C (r = 0.88, P < .001). Similarly, the number of shigellosis cases began to increase at a relative humidity of 70-74% (r = 0.75, P < .005). The number of shigellosis cases was positively associated with the mean temperature and relative humidity in the period preceding the infection. In conclusion, the occurrence of shigellosis is significantly associated with increasing temperature and relative humidity in Taiwan. Therefore, these factors could be regarded as warning signals indicating the need to implement preventive measures.

Association of long-term exposure to fine particulate matter and incident dyslipidaemia: A longitudinal cohort study.

BACKGROUND: Evidence of the effects of long-term exposure to fine particulate matter (PM2.5) air pollution on the development of dyslipidaemia is limited. This study aimed to investigate the association between long-term exposure to ambient PM2.5 and incident dyslipidaemia in a large cohort. METHODS: We studied 66,702 participants aged ≥18 years belonging to a cohort from a standard medical examination programme conducted in Taiwan between 2001 and 2014. The PM2.5 concentration at each participant's address was estimated using a satellite-based spatiotemporal model at a high resolution (1 km2). A time-varying Cox regression model was used to examine the association between long-term exposure to ambient PM2.5 and the development of dyslipidaemia. Additionally, sensitivity analyses were conducted to examine the stability of these associations. RESULTS: Compared with participants exposed to the 1st tertile of PM2.5, participants exposed to the 2nd and 3rd tertiles of PM2.5 had respective hazard ratios of 1.02 [95% confidence interval (CI): 0.98-1.06] and 1.08 (95%CI: 1.04-1.13) for incident dyslipidaemia. Sensitivity analyses generally yielded similar results. CONCLUSION: Long-term exposure to ambient PM2.5 is associated with a higher risk of dyslipidaemia. Global strategies for reducing air pollution are needed to prevent the development of dyslipidaemia.

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; PM2.5) 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 PM2.5 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 PM2.5 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 PM2.5 concentrations (i.e. the year of and the year before the medical examination) was treated as an indicator of long-term exposure to ambient PM2.5 air pollution. We performed Cox regression models with time-dependent covariates to analyse the long-term effects of exposure to PM2.5 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 PM2.5, participants exposed to the second, third and fourth quartiles of ambient PM2.5 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 PM2.5. CONCLUSIONS/INTERPRETATION: Long-term exposure to ambient PM2.5 appears to be associated with a higher risk of developing type 2 diabetes in this Asian population experiencing high levels of air pollution.

Unusual Roles of Discharge, Slope and SOC in DOC Transport in Small Mountainous Rivers, Taiwan.

Riverine dissolved organic carbon (DOC), responsible for riverine productivity, is rarely documented in subtropical small mountainous rivers (SMRs) where high rainfall and steep slopes are the main features. This study investigated the DOC export at eight sites in three Taiwan SMRs to characterize the dynamics and controlling factors of DOC transport. Results showed that the mean DOC concentration of ~0.78 mg L-1 is much lower than the global average of ~5.29 mg L-1. However, the mean DOC yield, ~22.51 kg-C ha-1 yr-1, is higher than the global average of 14.4-19.3 kg-C ha-1 yr-1. Comparing with worldwide rivers from literature, the annual discharge, slope, and SOC (soil organic carbon) are controlling factors as expected, though they influence in different ways. SOC stock likely regulated by elevation-dependent biomes dominate the DOC supply, while slope restrains the DOC generation due to shallow soil depth and fast runoff velocity. However, the abundant discharge flushing this persistent low supply leads to a large DOC export in the SMRs. Furthermore, the DOC dynamics during typhoon periods showed a clockwise hysteresis, suggesting that the DOC is mainly from the riparian zone or downslope area during the rising limb of the hydrograph. This study elucidates the DOC transport in SMRs and provides an atypical yet significant piece of understanding on DOC transport in a global context.

Seasonal Patterns of Japanese Encephalitis and Associated Meteorological Factors in Taiwan.

The persistent transmission of Japanese encephalitis virus (JEV) in Taiwan necessitates exploring the risk factors of occurrence of Japanese encephalitis (JE). The purpose of this study was to assess the relationship between meteorological factors and the incidence of JE in Taiwan. We collected data for cases of JE reported to the Taiwan Centers for Disease Control (Taiwan CDC) from 2000 to 2014. Meteorological data were obtained from the Taiwan Central Weather Bureau. The relationships between weather variability and the incidence of JE in Taiwan were determined via Poisson regression analysis and a case-crossover methodology. During the 15-year study period, a total of 379 cases of JE were reported. The incidence of JE showed significant seasonality, with the majority of cases occurring in summertime (for oscillation, p < 0.001). The number of JE cases started to increase at temperatures of 22 °C (r² = 0.88, p < 0.001). Similarly, the number of JE cases began to increase at a relative humidity of 70-74% (r² = 0.75, p < 0.005). The number of JE cases was positively associated with mean temperature and relative humidity in the period preceding the infection. In conclusion, the occurrence of JE is significantly associated with increasing temperature and relative humidity in Taiwan. Therefore, these factors could be regarded as warning signals indicating the need to implement preventive measures.

Long-term monitoring of atmospheric PCDD/Fs at Mount Lulin during spring season: PCDD/F source apportionment through a simultaneous measurement in Southeast Asia.

A long term assessment of atmospheric polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) at Mt. Lulin, located in center of Taiwan was carried out from 2008 to 2013 (n = 81) assuming Mt. Lulin to be background area. During monitoring processes, PCDD/F samples collected in the field occasionally reached high concentration. To investigate this situation, simultaneous sample collection was carried out in Southeast Asia countries (i.e., Vietnam and Thailand) and Taiwan in 2013. The average concentration of atmospheric PCDD/Fs in biomass-burning source regions, namely Son La and Doi Ang Khang were 19.8 ± 12.1 fg I-TEQ m-3 (n = 19) and 17.8 ± 12.4 fg I-TEQ m-3 (n = 20), respectively. In the downwind area of Mt. Lulin, the average concentration of PCDD/Fs was found to be 4.64 ± 3.77 fg I-TEQ m-3 (n = 18). PCDD/F concentration in the source region was much higher than that in the downwind region. On March 19, 2013, the atmospheric PCDD/F concentrations increased dramatically from 7.71 to 484 fg I-TEQ m-3 at Mt. Lulin, which many times exceeded that of assumed source region in Southeast Asia. Moreover, mainland Southeast Asia and the southeast coast of China was suspected to be the main contributors of atmospheric PCDD/Fs and biomass markers, such as nonsea-salt K+ and NH4+, during the spring. WRF-Chem and Potential Source Contribution Function (PSCF) simulations have confirmed this correlation. It can be concluded that atmospheric PCDD/Fs observed at Mt. Lulin during spring mostly derived from the air mass transport not only from Southeast Asia but also the southeast coast of China.

Estimation of anthropogenic heat emissions in urban Taiwan and their spatial patterns.

High energy consumption in the urban environment impacts the urban surface energy budget and causes the emission of anthropogenic heat fluxes (AHFs) into the atmosphere. AHFs vary over time and space. Thus, a reliable estimation of AHF is needed for mesoscale meteorological modeling. This study used a statistical regression method to estimate the annual mean gridded AHF with high spatial (1-km) resolution. Compared with current methods for AHF estimation, the statistical regression method is straightforward and can be easily incorporated with meteorological modeling. AHF of the highly populated urban areas in Taiwan were estimated using data from the anthropogenic pollutant emission inventory of CO and NOx for year 2010. Over 40% of the total AHF values in Taiwan main island fell within the range of 10-40 Wm(-2). When the study domain was confined to urban land, the percentage contributions from AHF values were increased, with over 68% of the total AHF values within the range of 10-40 Wm(-2). AHF values > 40 Wm(-2) were more abundant in the Southern region, followed by the Central and Northern regions. An assessment of the heat emissions by the large scale urban consumption of energy (LUCY) model revealed that the mean AHFs are reasonably close to those produced while the maximum AHFs are underestimated. The results obtained evidence the impact of spatial distribution of land use types, particularly population densities, main highways and industries on AHF generation in Taiwan.

The association between the incidence of mumps and meteorological parameters in Taiwan.

Mumps is caused by a paramyxovirus. It is an acute, but mild infectious disease. However, approximately 10% of patients with mumps can develop severe meningoencephalitis, disability, and death. Seasonal patterns in mumps vary across countries, but the reasons for this phenomenon remain unclear. The aim of this study was to assess the role of meteorological factors on mumps infection. We investigated the relationships between weather variability and the incidence of mumps in Taiwan using a Poisson regression analysis and case-crossover methodology. Between 2006 and 2011, 6,612 cases of mumps were reported to the Centers for Disease Control, Taiwan (Taiwan CDC). The incidence of mumps showed a significant seasonality in summertime (for oscillation, P < 0.001). The number of mumps started to increase at temperatures of 20°C (r(2) = 0.73, P < 0.001), and the case count of mumps began to decline when the temperatures were higher than approximately 25°C (r(2) = 0.24, p = 0.04), producing an inverted V-shaped relationship. Similarly, the number of mumps began to increase at a vapor pressure of 5-9 hPa (r(2) = 0.87, P < 0.005) and decreased at a vapor pressure higher than 25-29 hPa (r(2) = 0.21, p = 0.05). The number of mumps cases was positively associated with temperature and vapor pressure in the preceding period of the infection. In conclusion, this study showed that the occurrence of mumps is significantly associated with increasing temperature and vapor pressure in Taiwan. Therefore, these factors could be regarded as warning signals indicating the need to implement preventive measures.

Aerosol characteristics of different types of episode.

Daily and hourly average data from nine air-quality monitoring stations distributed across central Taiwan, which include ten items (i.e., PM10, PM2.5, wind direction, wind speed, temperature, relative humidity, SO2, NO2, NO, and CO), were collected from 2005 to 2009. Four episode types: long-range transport with dust storms (DS), long-range transport with frontal pollution (FP), river dust (RD), and stagnant weather (SW), and one mixed type of episode were identified. Of these four episode types, the SW was the dominant type, averaging about 70%. The mean ratio of PM2.5/PM10 was the lowest during the RD episodes (0.42), while the mean ratio of PM2.5/PM10 was the highest during the SW episodes (0.64). Fine aerosol (PM2.5) and coarse aerosol (PM10-2.5) samples were collected by high-volume samplers for chemical composition analysis, from only three stations (Douliou, Lunbei, and Siansi) during the days of SW, RD, DS, and FP. The concentrations of PM2.5 and three ionic species (NH4⁺, NO3⁻, and SO4²â») all showed significant differences among the four episode types. The highest levels of NO3⁻ (12.1 µg/m(3)) and SO4²â» (20.5 µg/m(3)) were found during the SW and FP episodes, respectively. A comparison on the spatial similarity of aerosol compositions among the episodes and/or non-episodes (control) was characterized by the coefficient of divergence (CD). The results showed higher CD values in PM10-2.5 than in PM2.5, and the CD values between RD episodes and the other three episodes were higher than those between two types of episode for the other three episodes. The ratios of SOR (sulfur oxidation ratio), SO4²â»/EC (elemental carbon), NOR (nitrogen oxidation ratio), and NO3⁻/EC showed that sulfate formation was most rapid during the FP, while nitrate formation was most rapid during the SW.

Analysis of the major factors affecting the visibility degradation in two stations.

UNLABELLED: There are four types of PM10 (particulate matter with an aerodynamic diameter <10 microm) episodes that occur frequently in central Taiwan: long-range transport with dust storms (DS), long-range transport with frontal pollution (FP), river dust (RD), and stagnant weather (SW). During the periods of the four episodes, poor visibility usually results. Multiple linear regression was applied to visibility using eight potential influential variables (temperature, relative humidity, wind speed, PM2.5, PM2.5-10, SO2, NO2, and NO) as independent variables. Of the eight variables, PM2.5 showed the greatest explainable percentage of about 48.6% and 58.1% for Taichung and Wuchi stations, respectively. This suggested that PM2.5 was the most important contributor to reduced visibility. Compared with other type of episodes, the aerosols tended to be offine size during the SWepisodes. This is the main reason that the poorest visibility occurred during the SWepisodes. Good correlation between visibility and secondary inorganic salts (NH4+, NO3, and SO4(2-)) were found at Taichung station (r = 0.71) and Wuchi station (r = 0.81), suggesting that secondary inorganic salts did contribute significantly to the degradation ofvisibility. The visibility degradation due to the effects ofNO3- was much higher than that due to SO4(2-) and NH4+ in the urban area, whereas the visibility degradation due to the effects of NO3 , SO42-, and NH4+ did not show significant diference in the rural area. IMPLICATIONS: Of the eight potential influential variables, PM2.5 showed the greatest effects on reduced visibility. Compared with other type of episodes, the aerosols tend to be fine size during the episodes of stagnant weather. This is the main reason why the poorest visibility occurred during the SW episodes. Good correlations between visibility and secondary inorganic salts (NH4+, NO3-, and SO4(2-)) suggested that secondary inorganic salts did contribute significantly to the degradation of visibility. Among the three inorganic salts, nitrates played a leading role for visibility degradation in urban areas in central Taiwan.