Integrated ground and vertical measurement techniques to characterize overhead atmosphere: Case studies of local versus transboundary pollution.

Much attention has been found to the long-range transport (LRT) of air pollutants and their adverse effects on downwind air qualities resulting from the Chinese haze, which frequently occurs in association with winter monsoon. This study integrates ground-based measurements, unmanned aerial vehicles (UAVs), and model simulations to characterize the meteorological, chemical, and particulate matter (PM) properties comprehensively for the events that were LRT or local pollution (LP) dominated in northern Taiwan during the wintertime of 2017. During the two types of episodes, various approaches were made to investigate the vertical mixing conditions and PM properties with UAV flights. A confined and PM accumulated feature near ground level with a temperature inversion was found during the LP event. In contrast, a vertically homogeneous atmospheric structure with strong winds was suggested during the LRT event. Independent measurements of criteria air pollutants, meteorological variables, volatile organic compounds (VOCs), and micropulse lidar (MPL) made at the ground level were closely supported by the vertical measurements. When synchronizing all these observational and numerical tools in a three-dimensional manner, the characterization of air masses and possible origins of pollution, such as LP vs. LRT, has now become more versatile and capable of gaining a complete picture of atmospheric conditions that define air quality.

Embedded information of aerosol type, hygroscopicity and scattering enhancement factor revealed by the relationship between PM2.5 and aerosol optical depth.

Satellite aerosol optical depth (AOD) provides an alternative way to depict the spatial distribution of near-surface PM2.5. In this study, a mathematical formulation of how PM2.5 is related to AOD is presented. When simplified to a linear equation, a functional dependence of the slope on the aerosol type, scattering enhancement factor f(RH), and boundary layer height is revealed, while the influence of the vertical aerosol profile is embedded in the intercept. Specifically, we focus on the effects of aerosol properties and employ a new aerosol index (Normalized Gradient Aerosol Index, NGAI) for classifying aerosol subtypes. The combination of AOD difference at shorter wavelengths over longer-wavelength AOD from AERONET data could distinguish and subclassify aerosol types previously indistinguishable by AE (i.e., urban-industrial pollution, U/I, and biomass burning, BB). AOD-PM2.5 regressions are performed on these aerosol subtypes at various relative humidity (RH) levels. The results suggest that BB aerosols are nearly hydrophobic until the RH exceeds 80 %, while the AOD-PM2.5 regressions for U/I depend on RH levels. Moreover, the scattering enhancement factor f(RH) can be calculated by taking the ratio of intercepts between dry and humidity conditions, which is proposed and tested for the first time in this study. Our results show an f(RH ≥ 80 %) of ∼2.6 for U/I-dominated aerosols, whereas the value is not over 1.5 for BB aerosols. The f(RH) can be further used to derive the optical hygroscopicity parameter (κsca), demonstrating that the NGAI can be used to exploit differences in aerosol hygroscopicity and improve the AOD-PM2.5 relationship.

Sources, transport, and visibility impact of ambient submicrometer particle number size distributions in an urban area of central Taiwan.

This study applied positive matrix factorization (PMF) to identify the sources of size-resolved submicrometer (10-1000 nm) particles and quantify their contributions to impaired visibility based on the particle number size distributions (PNSDs), aerosol light extinction (bp), air pollutants (PM10, PM2.5, SO2, O3, and NO), and meteorological parameters (temperature, relative humidity, wind speed, wind direction, and ultraviolet index) measured hourly over an urban basin in central Taiwan between 2017 and 2021. The transport of source-specific PNSDs was evaluated with wind and back trajectory analyses. The PMF revealed six sources to the total particle number (TPN), surface (TPS), volume (TPV), and bp. Factor 1 (F1), the key contributor to TPN (35.0 %), represented nucleation (<25 nm) particles associated with fresh traffic emission and secondary new particle formation, which were transported from the west-southwest by stronger winds (>2.2 m s-1). F2 represented the large Aitken (50-100 nm) particles transported regionally via northerly winds, whereas F3 represented large accumulation (300-1000 nm) particles, which showed elevated concentrations under stagnant conditions (<1.1 m s-1). F4 represented small Aitken (25-50 nm) particles arising from the growth and transport of the nucleation particles (F1) via west-southwesterly winds. F5 represented large Aitken particles originating from combustion-related SO2 sources and carried by west-northwesterly winds. F6 represented small accumulation (100-300 nm) particles emitted both by local sources and by the remote SO2 sources found for F5. Overall, large accumulation particles (F3) played the greatest role in determining the TPV (66.4 %) and TPS (34.8 %), and their contribution to bp increased markedly from 17.3 % to 40.7 % as visibility decreased, indicating that TPV and TPS are better metrics than TPN for estimating bp. Furthermore, slow-moving air masses-and therefore stagnant conditions-facilitate the build-up of accumulation mode particles (F3 + F6), resulting in the poorest visibility.

Secondary inorganic aerosol chemistry and its impact on atmospheric visibility over an ammonia-rich urban area in Central Taiwan.

This study investigated the hourly inorganic aerosol chemistry and its impact on atmospheric visibility over an urban area in Central Taiwan, by relying on measurements of aerosol light extinction, inorganic gases, and PM2.5 water-soluble ions (WSIs), and simulations from a thermodynamic equilibrium model. On average, the sulfate (SO42-), nitrate (NO3-), and ammonium (NH4+) components (SNA) contributed ∼90% of WSI concentrations, which in turn made up about 50% of the PM2.5 mass. During the entire observation period, PM2.5 and SNA concentrations, aerosol pH, aerosol liquid water content (ALWC), and sulfur and nitrogen conversion ratios all increased with decreasing visibility. In particular, the NO3- contribution to PM2.5 increased, whereas the SO42- contribution decreased, with decreasing visibility. The diurnal variations of the above parameters indicate that the interaction and likely mutual promotion between NO3- and ALWC enhanced the hygroscopicity and aqueous-phase reactions conducive for NO3- formation, thus led to severely impaired visibility. The high relative humidity (RH) at the study area (average 70.7%) was a necessary but not sole factor leading to enhanced NO3- formation, which was more directly associated with elevated ALWC and aerosol pH. Simulations from the thermodynamic model depict that the inorganic aerosol system in the study area was characterized by fully neutralized SO42- (i.e. a saturated factor in visibility reduction) and excess NH4+ amidst a NH3-rich environment. As a result, PM2.5 composition was most sensitive to gas-phase HNO3, and hence NOx, and relatively insensitive to NH3. Consequently, a reduction of NOx would result in instantaneous cuts of NO3-, PM2.5, and ALWC, and hence improved visibility. On the other hand, a substantial amount of NH3 reduction (>70%) would be required to lower the aerosol pH, driving more than 50% of the particulate phase NO3- to the gas phase, thereby making NH3 a limiting factor in shifting PM2.5 composition.

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.

Quantifying the impacts of PM2.5 constituents and relative humidity on visibility impairment in a suburban area of eastern Asia using long-term in-situ measurements.

The deterioration of visibility due to air pollutants and relative humidity has been a serious environmental problem in eastern Asia. In most previous studies, chemical compositions of atmospheric particles were provided using filter-based offline analyses, which were unable to provide long-term and in-situ measurements that resolve sufficient temporal variations of air pollution and meteorology, hindering the resolution of the relationship between air quality and visibility. Here, we present a year-long continuously measured data from a comprehensive suite of online instruments to investigate diurnal and seasonal impacts of the aerosol chemical compositions in PM2.5 on visibility seasonally and diurnally. The measured dry aerosol extinction at λ = 550 nm reached a closure with that predicted by aerosol compositions within 12%. However, the hygroscopic growth of particles under ambient RH could enhance the aerosol extinction by a factor of 2-6, matching the perceptive visibility of the public. Particulate ammonium nitrate was most sensitive to reducing visibility, while ammonium sulfate contributed the most to the light extinction. In spring and winter, the monsoon and stagnant air masses reduced the visibility and increased PM2.5 (>35 µg m-3). The moisture was found to substantially enhance the light extinction under RH = 60-90%, reducing visibility by approximately 15 km, largely attributed to hygroscopic inorganic salts. This study serves as a metric to highlight the need to consider the influence of RH, and aqueous reactions in producing secondary inorganic aerosols on atmospheric visibility, underpinning the more accurate mitigation strategies of air pollution.

Estimating monthly PM2.5 concentrations from satellite remote sensing data, meteorological variables, and land use data using ensemble statistical modeling and a random forest approach.

Fine particulate matter (PM2.5) is associated with various adverse health outcomes and poses serious concerns for public health. However, ground monitoring stations for PM2.5 measurements are mostly installed in population-dense or urban areas. Thus, satellite retrieved aerosol optical depth (AOD) data, which provide spatial and temporal surrogates of exposure, have become an important tool for PM2.5 estimates in a study area. In this study, we used AOD estimates of surface PM2.5 together with meteorological and land use variables to estimate monthly PM2.5 concentrations at a spatial resolution of 3 km2 over Taiwan Island from 2015 to 2019. An ensemble two-stage estimation procedure was proposed, with a generalized additive model (GAM) for temporal-trend removal in the first stage and a random forest model used to assess residual spatiotemporal variations in the second stage. We obtained a model-fitting R2 of 0.98 with a root mean square error (RMSE) of 1.40 µg/m3. The leave-one-out cross-validation (LOOCV) R2 with seasonal stratification was 0.82, and the RMSE was 3.85 µg/m3, whereas the R2 and RMSE obtained by using the pure random forest approach produced R2 and RMSE values of 0.74 and 4.60 µg/m3, respectively. The results indicated that the ensemble modeling approach had a higher predictive ability than the pure machine learning method and could provide reliable PM2.5 estimates over the entire island, which has complex terrain in terms of land use and topography.

Analysis of Pneumonia Occurrence in Relation to Climate Change in Tanga, Tanzania.

In 2018, 70% of global fatalities due to pneumonia occurred in about fifteen countries, with Tanzania being among the top eight countries contributing to these deaths. Environmental and individual factors contributing to these deaths may be multifaceted, but they have not yet been explored in Tanzania. Therefore, in this study, we explore the association between climate change and the occurrence of pneumonia in the Tanga Region, Tanzania. A time series study design was employed using meteorological and health data of the Tanga Region collected from January 2016 to December 2018 from the Tanzania Meteorological Authority and Health Management Information System, respectively. The generalized negative binomial regression technique was used to explore the associations between climate indicators (i.e., precipitation, humidity, and temperature) and the occurrence of pneumonia. There were trend differences in climate indicators and the occurrence of pneumonia between the Tanga and Handeni districts. We found a positive association between humidity and increased rates of non-severe pneumonia (incidence rate ratio (IRR) = 1.01; 95% CI: 1.01-1.02; p ≤ 0.05) and severe pneumonia (IRR = 1.02; 95% CI: 1.01-1.03; p ≤ 0.05). There was also a significant association between cold temperatures and the rate of severe pneumonia in Tanga (IRR = 1.21; 95% CI: 1.11-1.33; p ≤ 0.001). Other factors that were associated with pneumonia included age and district of residence. We found a positive relationship between humidity, temperature, and incidence of pneumonia in the Tanga Region. Policies focusing on prevention and control, as well as promotion strategies relating to climate change-related health effects should be developed and implemented.

Impacts of discriminated PM2.5 on global under-five and maternal mortality.

Globally, it was estimated that maternal and under-five deaths were high in low-income countries than that of high-income countries. Most studies, however, have focused only on the clinical causes of maternal and under-five deaths, and yet there could be other factors such as ambient particulate matter (PM). The current global estimates indicate that exposure to ambient PM2.5 (with ≤ 2.5 microns aerodynamic diameter) has caused about 7 million deaths and over 100 million disability-adjusted life-years. There are also several health risks that have been linked PM2.5, including mortality, both regionally and globally; however, PM2.5 is a mixture of many compounds from various sources. Globally, there is little evidence of the health effects of various types of PM2.5, which may uniquely contribute to the global burden of disease. Currently, only two studies had estimated the effects of discriminated ambient PM2.5, that is, anthropogenic, biomass and dust, on under-five and maternal mortality using satellite measurements, and this study found a positive association in Africa and Asia. However, the study area was conducted in only one region and may not reflect the spatial variations throughout the world. Therefore, in this study, we discriminated different ambient PM2.5 and estimated the effects on a global scale. Using the generalized linear mixed-effects model (GLMM) with a random-effects model, we found that biomass PM2.5 was associated with an 8.9% (95% confidence interval [CI] 4.1-13.9%) increased risk of under-five deaths, while dust PM2.5 was marginally associated with 9.5% of under-five deaths. Nevertheless, our study found no association between PM2.5 type and global maternal deaths. This result may be because the majority of maternal deaths could be associated with preventable deaths that would require clinical interventions. Identification of the mortality-related types of ambient PM2.5 can enable the development of a focused intervention strategy of placing appropriate preventive measures for reducing the generation of source-specific PM2.5 and subsequently diminishing PM2.5-related mortality.

Long-range air pollution transport in East Asia during the first week of the COVID-19 lockdown in China.

Long-range transport (LRT) of air pollutants from East Asia during the northeast monsoon season impacts several downwind locations. In 2020, the initial COVID-19 lockdowns in China overlapped with Week 3 of the Chinese New Year (CNY) holiday, and an Asian outflow event. Thus, movement of the Chinese populace from city to city was already greatly reduced by the time of the LRT episode, although the reductions in industrial output are less clear. We found NO2 column concentrations were reduced by 24% during the CNY Week 3 this year compared to previous years. The attenuated transport event arrived to northern Taiwan with a PM2.5 concentration <45 µg m-3 and most often <35 µg m-3, which is 2-3 times lower than LRT episodes of similar back-trajectory and synoptic patterns. The whole episode persisted for about 60 h, longer than most LRT episodes from China to Taiwan. CMAQ v5.2.1 modeling of the LRT event with 100% emission and reduced emission scenarios, revealed emissions in China were approximately 50% less than normal periods. Due to the length of the episode and the significant reduction in emissions, Taiwan avoided a PM2.5 surplus of 19.2 µg m-3 on average during the episode, equivalent to a 0.5 µg m-3 reduction for the whole 3-month winter season. Employing the 100% emission model scenario and scaling up to the average episode hours each winter, the PM2.5 surplus delivered via plumes on the northeast monsoon is equivalent to a 0.5 µg m-3 surplus for the whole year.

External Cesium-137 doses to humans from soil influenced by the Fukushima and Chernobyl nuclear power plants accidents: a comparative study.

External exposure to gamma-photon irradiation from soil contamination due to nuclear power plant (NPP) accidents has significant contribution to human radiation exposure in the proximity of the NPP. Detailed absorbed doses in human organs are rarely reported in the literature. We applied the Monte Carlo Neutron Particle (MCNP) transport code to calculate and compare the absorbed doses in different human organs. The absorbed doses by gamma-photon radiation were from cesium-137 (137Cs) in soil contaminated by the two major NPP accidents. More serious and wide-spread impacts of the Chernobyl NPP accident on soil contamination in Ukraine, Belarus, Russia and countries as far as Sweden and Greece were due to the inland location, radiative plume transport pathway and high 137Cs emission strength (9 times the Fukushima emission). Based on our MCNP calculations, the largest absorbed dose was found in skin. The maximum calculated external 137Cs annual effective dose received from the Chernobyl accident was 10 times higher relative to the Fukushima accident. Our calculated effective doses at various influenced areas were comparable to those available in the literature. The calculated annual effective doses at areas near the Fukushima and Chernobyl NPPs exceeded the ICRP recommendation of 1 mSv yr-1.

Ambient Particulate Matter Exposure and Under-Five and Maternal Deaths in Asia.

The Asian region is one of the major emission sources of air pollution. Although ambient PM2.5 has been linked to several health risks in high-, low-, and middle-income countries, the further analysis of type impact is still rare but significant. The PM2.5 distribution retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) aerosol optical depth products within 16 years thus explored the associations between under-five and maternal mortality for 45 countries in Asia. Both the nonparametric (Generalized Additive Mixed-Effect) and parametric (Generalized Linear Mixed-Effect) models were employed to analyze the collected datasets. The results show that the levels of PM2.5 in Asian sub-regions were higher than the Global Air Quality Standards. Biomass PM2.5 concentrations was associated with increased the rate of under-five (Incidence Rate Ratio, IRR = 1.29, 95% CI, 1.13-1.47) and maternal (IRR = 1.09, 95% CI: 1.08-1.10) deaths in Asia. Anthropogenic PM2.5 was associated with increased rate of under-five deaths in Asia by 12%. The nonparametric method revealed that dust PM2.5 was positively associated with the under-five (ß = 0.04, p < 0.001) and maternal (ß = 0.07, p < 0.001) deaths in Asia. The rate of maternal deaths was increased by biomass/dust (IRR = 1.64, 95% CI: 1.63-1.65) and anthropogenic/dust (IRR = 1.22, 95% CI: 1.19-1.26) mixture types. In summary, long-term exposure to different types of ambient PM2.5 in high concentration increased the rate of under-five and maternal deaths, suggesting that policies focusing on preventive and control measures is imperative for developing an improved maternal, newborn, and child health in Asia.

A Novel Approach to Relative Radiometric Calibration on Spatial and Temporal Variations for FORMOSAT-5 RSI Imagery.

Radiometric calibration for imaging sensors is a crucial procedure to ensure imagery quality. One of the challenges in relative radiometric calibration is to correct detector-level artifacts due to the fluctuation in discrepant responses (spatial) and electronic instability (temporal). In this paper, the integration of the empirical mode decomposition (EMD) with Hilbert⁻Huang transform (HHT) in relative radiometric calibration was explored for a new sensor, FS-5 RSI (remote sensing instrument onboard the FORMOSAT-5 satellite). The key intrinsic mode functions (IMFs) analyzed by HHT were examined with the pre-flight datasets of the FS-5 RSI in temporal and spatial variations. The results show that the EMD⁻HHT method can stabilize and improve the radiometric quality of the FS-5 imagery as well as boost its application ability to a new level. It is noticed that the IMFs of the spatial variation would be disturbed by the instability of the temporal variation. The relative response discrepancies among detector chips can be well calibrated after considering the temporal effect. Taking a test imagery dataset of gain setting G2 as an example, the standard deviation (STD) of the discrepancy in the digital number after calibration was dramatically scaled down compared to the original ones (e.g. , PAN: 66.31 to 1.85; B1: 54.19 to 1.90; B2: 36.50 to 1.49; B3: 32.43 to 1.56; B4: 37.67 to 1.20). The good performance of pre-flight imagery indicates that the EMD⁻HHT approach could be highly practical to the on-orbit relative radiometric calibration of the FS-5 RSI sensor and is applicable to other optical sensors. To our knowledge, the proposed EMD⁻HHT approach is used for the first time to explore relative radiometric calibration for optical sensors.

Critical low temperature for the survival of Aedes aegypti in Taiwan.

BACKGROUND: Taiwan is geographically located in a region that spans both tropical and subtropical climates (22-25°N and 120-122°E). The Taiwan Centers for Disease Control have found that the ecological habitat of Aedes aegypti appears only south of 23.5°N. Low temperatures may contribute to this particular habitat distribution of Ae. aegypti under the influence of the East Asian winter monsoon. However, the threshold condition related to critically low temperatures remains unclear because of the lack of large-scale spatial studies. This topic warrants further study, particularly through national entomological surveillance and satellite-derived land surface temperature (LST) data. METHODS: We hypothesized that the distribution of Ae. aegypti is highly correlated with the threshold nighttime LST and that a critical low LST limits the survival of Ae. aegypti. A mosquito dataset collected from the Taiwan Centers for Disease Control was utilized in conjunction with image data obtained from the moderate resolution imaging spectroradiometer (MODIS) during 2009-2011. Spatial interpolation and phi coefficient methods were used to analyze the correlation between the distributions of immature forms of Ae. aegypti and threshold LST, which was predicted from MODIS calculations for 348 townships in Taiwan. RESULTS: According to the evaluation of the correlation between estimated nighttime temperatures and the occurrence of Ae. aegypti, winter had the highest peak phi coefficient, and the corresponding estimated threshold temperatures ranged from 13.7 to 14 °C in the ordinary kriging model, which was the optimal interpolation model in terms of the root mean square error. The mean threshold temperature was determined to be 13.8 °C, which is a critical temperature to limit the occurrence of Ae. aegypti. CONCLUSIONS: An LST of 13.8 °C was found to be the critical temperature for Ae. aegypti larvae, which results in the near disappearance of Ae. aegypti during winter in the subtropical regions of Taiwan under the influence of the prevailing East Asian winter monsoon.

Differentiating between local and remote pollution over Taiwan.

In this study, an approach has been developed for differentiating between local and remote pollution over Taiwan, based on homogeneity perspective (variations of the standard deviation) of both AERONET measurements and NASA MERRA aerosol reanalysis (version 2, MERRA-2) over a 15-year period (2002 - 2017). The analysis of seasonal variations of the standard deviation of aerosol optical depth (AOD) measurements at six AERONET sites and MERRA AOD data in Taiwan showed that, in spring when remote aerosols dominate, the standard deviation is almost three times lower than that in autumn, when aerosols from local sources dominate. This finding was supported by MERRA AOD over the open ocean area: total AOD data were used to differentiate between local and remote pollution over both Taiwan and the open ocean area in the vicinity of Taiwan. Over Taiwan, MERRA total AOD showed a primary maximum in spring and a secondary one in autumn. Over the open ocean area, where there are no local sources of anthropogenic aerosols, MERRA total AOD showed only one maximum in spring and no maximum in autumn. This suggests that, in Taiwan, the maximum in autumn is attributed to local air pollution, while the pronounced maximum in spring is mainly caused by air pollution from continental Asia. The analyses of spatial distribution of 15-year monthly mean MERRA winds confirmed the above-mentioned results. Furthermore, similar to total AOD, MERRA sulfate AOD peaked in autumn over Taiwan, but not over the oceanic area: this indicates the contribution of local emissions of anthropogenic aerosols from the industrial sector. The standard deviation of MERRA sulfate AOD in spring is two-three times lower than the standard deviation in autumn: this is additional evidence that, in spring, sulfate aerosols from remote sources are predominant; while in autumn sulfate aerosols from local sources dominate.

Aerosol pollution and its potential impacts on outdoor human thermal sensation: East Asian perspectives.

Aerosols affect the insolation at ground and thus the Aerosol Optical Depth (AOD, a measure of aerosol pollution) plays an important role on the variation of the Physiological Equivalent Temperature (PET) at locations with different aerosol climatology. The aerosol effects upon PET were studied for the first time at four East Asian cities by coupling a radiative transfer model and a human thermal comfort model which were previously well evaluated. Evident with the MODIS and AERONET AOD observations, the aerosol pollution at Beijing and Seoul was higher than at Chiayi (Taiwan) and Hong Kong. Based on the AERONET data, with background AOD levels the selected temperate cities had similar clear-sky PET values especially during summertime, due to their locations at similar latitudes. This also applied to the sub-tropical cities. Increase in the AOD level to the seasonal average one led to an increase in diffuse solar radiation and in turn an increase in PET for people living in all the cities. However, the heavy aerosol loading environment in Beijing and Seoul in summertime (AODs > 3.0 in episodic situations) reduced the total radiative flux and thus PET values in the cities. On the contrary, relatively lower episodic AOD levels in Chiayi and Hong Kong led to strong diffuse and still strong direct radiative fluxes and resulted in higher PET values, relative to those with seasonal averaged AOD levels. People tended to feel from "hot" to "very hot" during summertime when the AOD reached their average levels from the background level. This implies that in future aerosol effects add further burden to the thermal environment apart from the effects of greenhouse gas-induced global warming. Understanding the interaction between ambient aerosols and outdoor thermal environment is an important first step for effective mitigation measures such as urban greening to reduce the risk of human heat stress. It is also critical to make cities more attractive and enhancing to human well-being to achieve enhancing sustainable urbanization as one of the principal goals for the Nature-based Solutions.

The Associations between Types of Ambient PM2.5 and Under-Five and Maternal Mortality in Africa.

Exploring the effects of different types of PM2.5 is necessary to reduce associated deaths, especially in low- and middle-income countries (LMICs). Hence we determined types of ambient PM2.5 before exploring their effects on under-five and maternal mortality in Africa. The spectral derivate of aerosol optical depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) products from 2000 to 2015 were employed to determine the aerosol types before using Generalized Linear and Additive Mixed-Effect models with Poisson link function to explore the associations and penalized spline for dose-response relationships. Four types of PM2.5 were identified in terms of mineral dust, anthropogenic pollutant, biomass burning and mixture aerosols. The results demonstrate that biomass PM2.5 increased the rate of under-five mortality in Western and Central Africa, each by 2%, and maternal mortality in Central Africa by 19%. Anthropogenic PM2.5 increased under-five and maternal deaths in Northern Africa by 5% and 10%, respectively, and maternal deaths by 4% in Eastern Africa. Dust PM2.5 increased under-five deaths in Northern, Western, and Central Africa by 3%, 1%, and 10%, respectively. Mixture PM2.5 only increased under-five deaths and maternal deaths in Western (incidence rate ratio = 1.01, p < 0.10) and Eastern Africa (incidence rate ratio = 1.06, p < 0.01), respectively. The findings indicate the types of ambient PM2.5 are significantly associated with under-five and maternal mortality in Africa where the exposure level usually exceeds the World Health Organization's (WHO) standards. Appropriate policy actions on protective and control measures are therefore suggested and should be developed and implemented accordingly.