Sea surface Fresnel reflections difference driven de-glint algorithm for airborne optical images.

This paper presents a glint correction algorithm for high spatial resolution optical remote sensing imagery captured by the ER-2 Airborne Visual Infrared Imaging Spectrometer (AVIRIS). The algorithm employs linear and differential techniques to mitigate sun glint and sky glint effects, encompassing statistical glint reflections resulting from variations in imaging angles within strips and inter-strip variations due to Fresnel reflectance disparities. It aims to diminish Fresnel reflectance diversity on water surfaces and mitigate the distortions induced by glint reflectance during spectral and ocean color inversion. A comparative analysis of spectral and ocean color information in AVIRIS images before and after correction reveals enhanced accuracy following the glint correction. By systematically addressing multiple glint reflections and their ramifications, this method offers a valuable framework for correcting water surface glint in diverse high spatial resolution optical imagery.

Extraction of eutrophic and green ponds from segmentation of high-resolution imagery based on the EAF-Unet algorithm.

Inland ponds exhibit remarkable ubiquity across the globe, playing a vital role in the sustainability of global continental freshwater resources and contributing significantly to their biodiversity. Numerous ponds are eutrophic and experience recurrent seasonal or year-round algal blooms or persistent duckweed cover, conferring a characteristic green hue. Here, we denote these eutrophic and green ponds as EGPs. The excessive proliferation of algal blooms and duckweed within these EGPs poses a significant threat to the ecological functioning of these aquatic systems, which can lead to hypoxia or the release of microcystins. To identify these EGPs automatically, we constructed an Efficient Attention Fusion Unet (EAF-Unet) algorithm using Gaofen-2 (GF2) panchromatic and multispectral imagery. The attention mechanism was incorporated in Unet to help better detect EGPs. Using the first EGP labeled dataset, we determined the best input feature combination (RGB, NIR, NDVI, and Bright) and the most effective encoding (Rasnet50) for EAF-Unet for distinguishing EGPs from other ground cover types. The evaluation indices - Precision (0.81), Recall (0.79), F1-Score (0.80), and Intersection over Union (IoU, 0.67) - indicate that EAF-Unet can accurately and robustly extract EGPs from GF2 images without relying on pond water masks. Remote-sensing EGP products can assist in identifying ponds with severe eutrophication. Moreover, these products can serve as references for identifying high-risk areas prone to improper sewage discharge or inadequate sewer construction.

A systematic review and quantitative meta-analysis of the relationships between driving forces and cyanobacterial blooms at global scale.

The global expansion of cyanobacterial blooms poses a major risk to the safety of freshwater resources. As a result, many explorations have been performed at a regional scale to determine the underlying impact mechanism of cyanobacterial blooms for one or several waterbodies. However, two questions still need to be answered quantitatively at a global scale to assist the water management. One is to specify which factors were often selected as the driving forces of cyanobacterial blooms, and the other is to estimate their quantitative relationships. For that, this paper applied a systematic literature review for 41 peer-reviewed studies published before May 2021 and a statistical meta-analysis based on the Pearson's or Spearman's correlation coefficients from 27 studies. These results showed that the water quality, hydraulic conditions, meteorological conditions and nutrient levels were often considered the driving forces of cyanobacterial blooms in global freshwater systems. Among these, meteorological conditions and nutrient level had the highest probability of being chosen as the driving force. In addition, knowledge of the quantitative relationships between these driving forces and cyanobacterial blooms was newly synthesized based on the correlation coefficients. The results indicated that, at a global scale, meteorological conditions were negatively related to cyanobacterial blooms, and other driving forces, such as water quality, hydraulic conditions and nutrient levels, were positively related to cyanobacterial blooms. In addition, the measurement indicators of these driving forces had diverse forms. For example, the nutrient level can be measured by the concentration of different forms of nitrogen or phosphorus, which may lead to different results in correlation analysis. Thus, a subgroup meta-analysis was necessary for the subdivided driving forces and cyanobacterial blooms, which had a better accuracy. Overall, the synthesized knowledge can help guide advanced cyanobacteria-centered water management, especially when the necessary cyanobacterial data of targeting waterbodies are inaccessible.

Human activities changed organic carbon transport in Chinese rivers during 2004-2018.

Rivers serve as regulators of global climate by releasing greenhouse gases, burying particulate carbon, and connecting different ecosystem carbon pools. However, long-term organic carbon (OC) transport features across different Asian rivers are not well known due to unavailable data. Based on routinely monitored environmental and hydrological data during 2004-2018, this study investigated the spatiotemporal variations in dissolved (DOC) and particulate OC (POC) transport across 41 rivers in China. Across different rivers, both DOC (1.35 - 16.8 mg/L) and POC (0.27 - 4.48 mg/L) concentrations covered wide ranges. The DOC content was high in the north and low in the south, with significantly higher (t test, p < 0.01) values for rivers north of 30°N (5.39 ± 3.66 mg/L vs. 2.39 ± 1.14 mg/L). Human activities greatly influenced the riverine DOC and POC distributions. The riverine ammonia nitrogen (NH+ 4-N) content was positively correlated with DOC (r = 0.81 and p < 0.01) and explained 85.59% of its spatial variation. High vegetation coverage had significant effects on decreasing the riverine POC content, with r = -0.55 and p < 0.05. During 2004-2018, water pollution prevention and control strategies decreased DOC concentrations in 60.98% of rivers; meanwhile, anthropogenic vegetation restoration and dam construction led to POC content decreases in 90.48% of rivers. Importantly, along with DOC and POC changes, increasing DOC/POC ratios were found in 90.48% of the rivers, with 42.86% being significant, which indicated that Chinese rivers are losing their Asian features of low DOC/POC ratios due to artificial disturbance. This study is significant for accurately quantifying greenhouse gas emissions, carbon burial, and OC export to estuaries by Chinese rivers.

Chlorination of soil-derived dissolved organic matter: Long term nitrogen deposition does not increase terrestrial precursors of toxic disinfection byproducts.

Terrestrial dissolved organic matter (DOM) in forested watersheds is a known precursor of disinfection byproducts (DBPs) in drinking water. Although the characteristics of terrestrial DOM may change with increasing nitrogen (N) deposition in forests, how these changes alter formation potential and toxicity of DBPs remains unexplored. We analyzed the speciation and toxicity of DBPs from chlorination of DOM derived from soils (O, A, and B horizons) in an experimental temperate forest with 22 years of N addition. With long-term N addition, the DOM reactivity toward the formation of trihalomethanes (from 27.7-51.8 to 22.8-31.1 µg/mg-dissolved organic carbon (DOC)) and chloral hydrate (from 1.25-1.63 to 1.14-1.36 µg/mg-DOC) decreased, but that toward the formation of haloketones increased (from 0.23-0.26 to 0.26-0.33 µg/mg-DOC). The DOM reactivity toward the formation of haloacetonitriles was increased in the deeper soil but reduced in the surface soil. The DBP formation potential of DOM draining from a certain area of forest soils (in µg-DBP/m2-soil) was estimated to be reduced by 20.3% for trihalomethanes and increased by 37.5% for haloketones and have minor changes for haloacetonitriles and chloral hydrate (both <7%). Furthermore, the DBPs from chlorination of the soil-derived DOM showed lowered microtoxicity with N addition possibly due to reduced brominated DBP formation. Overall, this study highlights that N deposition may not increase drinking water toxicity through altering terrestrial DOM characteristics.

Long-term biochar addition alters the characteristics but not the chlorine reactivity of soil-derived dissolved organic matter.

Biochar is widely and increasingly applied to farmlands. However, it remains unclear how long-term biochar addition alters the characteristics and chlorine reactivity of soil-derived dissolved organic matter (DOM), an important terrestrial disinfection byproduct (DBP) precursor in watersheds. Here, we analyzed the spectroscopic and molecular-level characteristics of soil-derived DOM and the formation and toxicity of DBP mixtures from DOM chlorination for two long-term (5 and 11 years) biochar addition experimental farmlands. As indicated by spectroscopic indices and Fourier transform ion cyclotron resonance mass spectrometry analyses, 11 years of biochar addition could increase the humic-like and aromatic and condensed aromatic DOM and decrease the microbial-derived DOM, while 5 years of biochar addition at the other site did not. The response of condensed aromatic dissolved black carbon did not increase with increasing cumulative biochar dose but appeared to be affected by biochar aging time. Despite the possible increase in aromatic DOM, biochar addition neither increased the reactivity of DOM in forming trihalomethanes, haloacetonitriles, chloral hydrates, or haloketones nor significantly increased the microtoxicity or genotoxicity of the DBP mixture. This study indicates that biochar addition in watersheds may not deteriorate the drinking water quality via the export of terrestrial DBP precursors like wildfire events.

Design and Experiments of a Water Color Remote Sensing-Oriented Unmanned Surface Vehicle.

Integrated and intelligent in situ observations are important for the remote sensing monitoring of dynamic water environments. To meet the field investigation requirements of ocean color remote sensing, we developed a water color remote sensing-oriented unmanned surface vehicle (WC-USV), which consisted of an unmanned surface vehicle platform with ground control station, data acquisition, and transmission modules. The WC-USV was designed with functions, such as remote controlling, status monitoring, automatic obstacle avoidance, and water and meteorological parameter measurement acquisition, transmission, and processing. The key data acquisition module consisted of four parts: A floating optical buoy (FOBY) for collecting remote sensing reflectance ( R r s ) via the skylight-blocked approach; a water sample autocollection system that can collect 12 1-L bottles for analysis in the laboratory; a water quality measurement system for obtaining water parameters, including Chlorophyll-a (Chl-a), turbidity, and water temperature, among others; and meteorological sensors for measuring wind speed and direction, air pressure, temperature, and humidity. Field experiments were conducted to validate the performance of the WC-USV on 23-28 March 2018 in the Honghu Lake, which is the seventh largest freshwater lake in China. The tests proved the following: (1) The WC-USV performed well in terms of autonomous navigation and obstacle avoidance; (2) the mounted FOBY-derived R r s showed good precision in terms of the quality assurance score (QAS), which was higher than 0.98; (3) the Chl-a and suspended matters (SPM) as ocean color parameters measured by the WC-USV were highly consistent with laboratory analysis results, with determination coefficients (R2) of 0.71 and 0.77, respectively; and (4) meteorological parameters could be continuously and stably measured by WC-USV. Results demonstrated the feasibility and practicability of the WC-USV for automatic in situ observations. The USV provided a new way of thinking for the future development of intelligent automation of the aquatic remote sensing ground verification system. It could be a good option to conduct field investigations for ocean color remote sensing and provide an alternative for highly polluted and/or shallow high-risk waters which large vessels have difficulty reaching.

Short-term Effect of Air Pollution on Tuberculosis Based on Kriged Data: A Time-series Analysis.

Tuberculosis (TB) has a very high mortality rate worldwide. However, only a few studies have examined the associations between short-term exposure to air pollution and TB incidence. Our objectives were to estimate associations between short-term exposure to air pollutants and TB incidence in Wuhan city, China, during the 2015-2016 period. We applied a generalized additive model to access the short-term association of air pollution with TB. Daily exposure to each air pollutant in Wuhan was determined using ordinary kriging. The air pollutants included in the analysis were particulate matter (PM) with an aerodynamic diameter less than or equal to 2.5 micrometers (PM2.5), PM with an aerodynamic diameter less than or equal to 10 micrometers (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ground-level ozone (O3). Daily incident cases of TB were obtained from the Hubei Provincial Center for Disease Control and Prevention (Hubei CDC). Both single- and multiple-pollutant models were used to examine the associations between air pollution and TB. Seasonal variation was assessed by splitting the all-year data into warm (May-October) and cold (November-April) seasons. In the single-pollutant model, for a 10 µg/m3 increase in PM2.5, PM10, and O3 at lag 7, the associated TB risk increased by 17.03% (95% CI: 6.39, 28.74), 11.08% (95% CI: 6.39, 28.74), and 16.15% (95% CI: 1.88, 32.42), respectively. In the multi-pollutant model, the effect of PM2.5 on TB remained statistically significant, while the effects of other pollutants were attenuated. The seasonal analysis showed that there was not much difference regarding the impact of air pollution on TB between the warm season and the cold season. Our study reveals that the mechanism linking air pollution and TB is still complex. Further research is warranted to explore the interaction of air pollution and TB.

Impact of Ambient Temperature and Relative Humidity on the Incidence of Hand-Foot-Mouth Disease in Wuhan, China.

Background: Few studies have previously explored the relationship between hand, foot, and mouth disease (HFMD) and meteorological factors with the effect modification of air pollution, and these studies had inconsistent findings. We therefore applied a time-series analysis assessing the effects of temperature and humidity on the incidence of HFMD in Wuhan, China to deepen our understanding of the relationship between meteorological factors and the risk of HFMD. Methods: Daily HFMD cases were retrieved from Hubei Provincial Center for Disease Control and Prevention from 1 February 2013 to 31 January 2017. Daily meteorological data including 24 h average temperature, relative humidity, wind velocity, and atmospheric pressure were obtained from Hubei Meteorological Bureau. Data on Air pollution was collected from 10 national air-monitoring stations in Wuhan city. We adopted a distributed lag non-linear model (DLNM) combined with Poisson regression and time-series analysis to estimate the effects of temperature and relative humidity on the incidence HFMD. Results: We found that the association between temperature and HFMD incidence was non-linear, exhibiting an approximate "M" shape with two peaks occurring at 2.3 °C (RR = 1.760, 95% CI: 1.218-2.542) and 27.9 °C (RR = 1.945, 95% CI: 1.570-2.408), respectively. We observed an inverted "V" shape between relative humidity and HFMD. The risk of HFMD reached a maximum value at a relative humidity of 89.2% (RR = 1.553, 95% CI: 1.322-1.824). The largest delayed cumulative effects occurred at lag 6 for temperature and lag 13 for relative humidity. Conclusions: The non-linear relationship between meteorological factors and the incidence of HFMD on different lag days could be used in the early targeted warning system of infectious diseases, reducing the possible outbreaks and burdens of HFMD among sensitive populations.

An Automatic Stationary Water Color Parameters Observation System for Shallow Waters: Designment and Applications.

Measurements of the above-water spectrum and concerned water color parameters (WCPs) are crucial for research and applications in water environment remote sensing. Due to the lack of system integration and automatization, conventional methods are labor-intensive, time-consuming, and prone to subjective influences. To obtain a highly accurate and long-term consistent spectrum and concurrent WCPs (Chl-a (chlorophyll-a), turbidity, and CDOM (Colored Dissolved Organic Matter)) data with a relatively low cost, an Automatic Stationary Water Color Parameters Observation System (AFWCPOS) was developed. Controlled by an automatic platform, the spectral and WCPs data were collected by TriOS RAMSES hyperspectral spectroradiometers and WETLabs ECO (Environmental Characterization Optics) fluorometers following the measurement protocol. Experiment and initial validations of AFWCPOS were carried out in Poyang Lake, the largest freshwater lake in China, from 20 to 28 July 2013. Results proved that the spectral data from AFWCPOS were highly consistent with the commonly used portable SVC (Spectra Vista Corporation) HR-1024 field spectroradiometer, with the coefficient of determination (R2) of 0.96, unbiased percent difference (UPD) of 0.14, and mean relative difference (MRD) of 0.078. With advantages of continuous and high degrees of automation monitoring, the AFWCPOS has great potential in capture diurnal and inter-diurnal variations in the test site of Poyang Lake, as well as another high-dynamic shallow coastal and inland waters, which will benefit routine water quality monitoring with high quality and high-frequency time-series observations. In addition, a successful case based on Landsat 8 OLI (Operational Land Imager) image and in-situ data collected by AFWCPOS showed it's potential in remote sensing applications. The spatial distribution of Chl-a, turbidity, and CDOM were mapped, which were explainable and similar to previous researches. These results showed our system was able to obtain reliable and valuable data for water environment monitoring.

The association between short-term exposure to ambient air pollution and the incidence of mumps in Wuhan, China: A time-series study.

BACKGROUND: Previous studies have estimated the association between meteorological factors and mumps outbreaks without assessing the influence of air pollution. In this research, we explored the effects of short-term exposure to air pollution on the incidence of mumps. METHODS: Our time-series analysis was conducted using data collected in Wuhan, China from 2015 to 2017. Daily number of mumps cases was obtained from Disease Reporting System in Hubei Provincial Center for Disease Control and Prevention. Data on air pollution was obtained from 10 national air quality monitoring stations, including nitrogen dioxide (NO2), sulfur dioxide (SO2), ground-level ozone (O3), particulate matter less than or equal to 10 µm in aerodynamic diameter (PM10), and particulate matter less than or equal to 2.5 µm in aerodynamic diameter (PM2.5). Daily meteorological data including temperature and relative humidity were obtained from Hubei Meteorological Bureau. We performed a Poisson regression in generalized additive models (GAM) to explore the association between the incidence of mumps and exposure to air pollution. RESULTS: We observed that the effects of air pollutants were statistically significant mainly in two periods, lag 0 to lag 5 and lag 20 to lag 25, with the strongest effects appearing at lag 2 and lag 23. The cumulative effects were stronger than single-day lag effects. The stratified analysis showed the effect of pollutants during the hot season was stronger than that during the cold season, especially for NO2 and SO2. CONCLUSIONS: We found that exposure to NO2 and SO2 was significantly associated with higher risk of developing mumps. Our findings could help deepen the understanding of how air pollution exposure affects the incidence of mumps.

Temporal Variation of Chlorophyll-a Concentrations in Highly Dynamic Waters from Unattended Sensors and Remote Sensing Observations.

Monitoring of water quality changes in highly dynamic inland lakes is frequently impeded by insufficient spatial and temporal coverage, for both field surveys and remote sensing methods. To track short-term variations of chlorophyll fluorescence and chlorophyll-a concentrations in Poyang Lake, the largest freshwater lake in China, high-frequency, in-situ, measurements were collected from two fixed stations. The K-mean clustering method was also applied to identify clusters with similar spatio-temporal variations, using remote sensing Chl-a data products from the MERIS satellite, taken from 2003 to 2012. Four lake area classes were obtained with distinct spatio-temporal patterns, two of which were selected for in situ measurement. Distinct daily periodic variations were observed, with peaks at approximately 3:00 PM and troughs at night or early morning. Short-term variations of chlorophyll fluorescence and Chl-a levels were revealed, with a maximum intra-diurnal ratio of 5.1 and inter-diurnal ratio of 7.4, respectively. Using geostatistical analysis, the temporal range of chlorophyll fluorescence and corresponding Chl-a variations was determined to be 9.6 h, which indicates that there is a temporal discrepancy between Chl-a variations and the sampling frequency of current satellite missions. An analysis of the optimal sampling strategies demonstrated that the influence of the sampling time on the mean Chl-a concentrations observed was higher than 25%, and the uncertainty of any single Terra/MODIS or Aqua/MODIS observation was approximately 15%. Therefore, sampling twice a day is essential to resolve Chl-a variations with a bias level of 10% or less. The results highlight short-term variations of critical water quality parameters in freshwater, and they help identify specific design requirements for geostationary earth observation missions, so that they can better address the challenges of monitoring complex coastal and inland environments around the world.

Remote sensing of early-stage green tide in the Yellow Sea for floating-macroalgae collecting campaign.

The world's largest green tide originated from the Jiangsu Shoal of the Yellow Sea was due to fast reproduction of floating green macroalgae (Ulva prolifera). It brought significant impacts on marine environment and ecosystem in the Yellow Sea. In this study, we examined the expansion of green tide from the Jiangsu Shoal during the period from 29 April to 25 June 2016. Using high-resolution satellite images, we revealed a declined growth rate during the northward drifting of early-stage green tide for the first time, i.e., the green tide had higher growth rate (up to 25% per day) in the turbid waters of the Jiangsu Shoal in May and a lower growth rate (low to 3% per day) in the relatively clear waters in the middle of the western Yellow Sea in June, which suggests that water clarity might not be the key factor controlling the growth rate of the floating macroalgae in the surface waters under natural conditions. The high growth rate led to shortened time windows for controlling the green tide by employing macroalgae collecting campaigns at the initial sites of the green tide, which was no more than 14 days in the 2016 case.

Analysis of short-term and sub-chronic effects of ambient air pollution on preterm birth in central China.

Recently, an increasing number of studies have reported the possible linkage between maternal exposure to ambient air pollution and adverse birth outcomes. This retrospective cohort study aimed to evaluate the effect of short-term and sub-chronic exposure to air pollutants on preterm birth occurred in Shiyan and Jingzhou, Hubei province, China from 2014 to 2016. General additive models (GAM) were performed to examine the impact of the daily and cumulative weekly air pollutants exposure. The non-linear patterns between adverse birth outcomes and weather condition were assessed by including penalized smoothing splines in the model. The demographic characteristics of pregnant women were also included in the model as covariates. A total of 16,035 cases were analyzed. Significant short-term effects of air pollution exposure at lag 1 day on preterm birth were observed. In adjusted single-pollutant city-specific model, the association between acute air pollutant exposure and preterm birth was significant in Shiyan (PM2.5: OR = 1.066, 95% CI 1.027, 1.106; PM10: OR = 1.048, 95% CI 1.022, 1.076; O3: OR = 1.029, 95% CI 1.004, 1.056) and Jingzhou (PM2.5: OR = 1.037, 95% CI 1.008, 1.068; PM10: OR = 1.025, 95% CI 1.007, 1.043; SO2: OR = 1.082, 95% CI 1.023, 1.144; NO2: OR = 1.211, 95% CI 1.098, 1.335) per 10 µg/m3 increment. Also, weekly average cumulative air pollution exposure was significantly associated with preterm birth in both areas.

Birds in the Himalayas: What drives beta diversity patterns along an elevational gradient?

Beta diversity patterns along elevational gradients have become a hot topic in the study of biogeography and can help illuminate the processes structuring mountain ecosystems. Although elevational species richness patterns have been well documented, there remains much uncertainty over the causes of beta diversity patterns across elevational gradients. We conducted bird surveys and obtained high-resolution climatic data along an elevational gradient in Gyirong Valley in the central Himalayas, China, between 1,800 and 5,400 m elevation. In total, we recorded 182 bird species (including 169 breeding birds). We simulated beta diversity patterns with the mid-domain effect (MDE) null model and conducted distance-based redundancy analyses (db-RDA) to relate beta diversity to dispersal limitations, spatial constraints, habitat complexity, contemporary climate, and historical climate. Mantel tests and variation partitioning were employed to identify the magnitude of independent statistical associations of environmental factors with beta diversity. Patterns of empirical and simulated beta diversity were both hump-shaped, peaking at intermediate elevations. The db-RDA indicated that beta diversity was correlated with changes in spatially structured environmental factors, especially with contemporary climate and habitat complexity. Mantel tests and variation partitioning also suggested that climate dissimilarity was the major independent correlate of beta diversity. The random community structure and spatial constraints may also contribute to the overall hump-shaped pattern. Beta diversity of bird communities in Gyirong Valley could be explained by the combination of different factors but is mainly shaped by the spatially structured environmental factors, especially contemporary climate.

Association between ambient fine particulate matter and preterm birth or term low birth weight: An updated systematic review and meta-analysis.

An increasing number of studies have been conducted to determine a possible linkage between maternal exposure to ambient fine particulate matter and effects on the developing human fetus that can lead to adverse birth outcomes, but, the present results are not consistent. A total of 23 studies published before July 2016 were collected and analyzed and the mean value of reported exposure to fine particulate matter (PM2.5) ranged from 1.82 to 22.11 We found a significantly increased risk of preterm birth with interquartile range increase in PM2.5 exposure throughout pregnancy (odds ratio (OR) = 1.03; 95% conditional independence (CI): 1.01-1.05). The pooled OR for the association between PM2.5 exposure, per interquartile range increment, and term low birth weight throughout pregnancy was 1.03 (95% CI: 1.02-1.03). The pooled ORs for the association between PM2.5 exposure per 10 increment, and term low birth weight and preterm birth were 1.05 (95% CI: 0.98-1.12) and 1.02 (95% CI: 0.93-1.12), respectively throughout pregnancy. There is a significant heterogeneity in most meta-analyses, except for pooled OR per interquartile range increase for term low birth weight throughout pregnancy. We here show that maternal exposure to fine particulate air pollution increases the risk of preterm birth and term low birth weight. However, the effect of exposure time needs to be further explored. In the future, prospective cohort studies and personal exposure measurements needs to be more widely utilized to better characterize the relationship between ambient fine particulate exposure and adverse birth outcomes.

The short-term effects of air pollutants on respiratory disease mortality in Wuhan, China: comparison of time-series and case-crossover analyses.

Few studies have compared different methods when exploring the short-term effects of air pollutants on respiratory disease mortality in Wuhan, China. This study assesses the association between air pollutants and respiratory disease mortality with both time-series and time-stratified-case-crossover designs. The generalized additive model (GAM) and the conditional logistic regression model were used to assess the short-term effects of air pollutants on respiratory disease mortality. Stratified analyses were performed by age, sex, and diseases. A 10 µg/m3 increment in SO2 level was associated with an increase in relative risk for all respiratory disease mortality of 2.4% and 1.9% in the case-crossover and time-series analyses in single pollutant models, respectively. Strong evidence of an association between NO2 and daily respiratory disease mortality among men or people older than 65 years was found in the case-crossover study. There was a positive association between air pollutants and respiratory disease mortality in Wuhan, China. Both time-series and case-crossover analyses consistently reveal the association between three air pollutants and respiratory disease mortality. The estimates of association between air pollution and respiratory disease mortality from the case-crossover analysis displayed greater variation than that from the time-series analysis.

Tracking radiometric responsivity of optical sensors without on-board calibration systems-case of the Chinese HJ-1A/1B CCD sensors.

The radiometric stability of satellite sensors is crucial for generating highly consistent remote sensing measurements and products. We have presented a radiometric responsivity tracking method designed especially for optical sensors without on-board calibration systems. Using a temporally stable desert site with high reflectance, the sensor responsivity was simulated using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative transfer model (RTM) with information from validated MODIS atmospheric data. Next, radiometric responsivity drifting was identified using a linear regression of the time series bidirectional reflectance distribution function (BRDF) normalized coefficients. The proposed method was applied to Chinese HJ-1A/1B charge-coupled device (CCD) sensors, which have been on-orbit operations for more than 5 years without continuous assessment of their radiometric performance. Results from the Dunhuang desert site between 2008 and 2013 indicated that the CCD sensors degraded at various rates, with the most significant degradation occurring in the blue bands, ranging from 2.8% to 4.2% yr-1. The red bands were more stable, with a degradation rate of 0.7-3.1% yr-1. A cross-sensor comparison revealed the least degradation for the HJ-1A CCD1 (blue: 2.8%; green: 2.8%; red: 0.7%; and NIR: 0.9% yr-1), whereas the degradation of HJ-1B CCD1 was most pronounced (blue: 3.5%; green: 4.1%; red: 2.3%; and NIR: 3.4% yr-1). The uncertainties of the method were evaluated theoretically based on the propagation of uncertainties from all possible sources of the RT simulations. In addition, a cross comparison with matchup ground-based absolute calibration results was conducted. The comparison demonstrated that the method was useful for continuously monitoring the radiometric performance of remote sensors, such as HJ-1A/1B CCD and GaoFen (GF) series (China's latest high-definition Earth observation satellite), and indicated the potential use of the method for high-precision absolute calibration.

Association between air pollutants and cardiovascular disease mortality in Wuhan, China.

We examined the associations of daily mean concentrations of ambient air pollutants (particulate matter (PM10), sulfur dioxide (SO2), nitric oxide (NO2)) and daily cardiovascular diseases (CVD) mortality in Wuhan, China using a case-crossover design to analyze four years of data (2006-2009) collected from the Hubei Provincial Center for Disease Control and Prevention and the Wuhan Environmental Protection Bureau. From 2006 to 2009, daily average concentrations of PM10, SO2 and NO2 were 115.60 µg/m3, 53.21 µg/m3 and 53.08 µg/m3, respectively. After adjusting for temperature and relative humidity, a 10 µg/m3 increase in SO2 and NO2 over a 24-h period was associated with CVD mortality relative risk (R.R.) of 1.010 (95% CI: 1.000, 1.020) for SO2 and 1.019 (95% CI: 1.005, 1.033) for NO2, but there was no significant association between increases in PM10 and mortality. Subgroup analysis on by gender showed a significant association of 1.026 (95% CI: 1.007, 1.045) between NO2 and CVD among males, while no significant statistical effect was shown among females. Subgroup analysis by age showed that for those older than 65 years, every 10 µg/m3 increase in NO2 was associated with a 1.6% (95% CI: 0.1%, 3.1%) increase in CVD mortality. Subgroup analysis on different types of CVD showed that every 10 µg/m3 increase in PM10 and SO2 were significantly associated with an approximately 1.012 (95% CI: 1.002, 1.022) and 1.021 (95% CI: 1.002, 1.040) increase, respectively, in ischemic heart disease (ICH) mortality. In conclusion, exposure to NO2 is significantly associated with CVD mortality. Larger, multi-center studies in Chinese cities are being currently conducted to validate these findings.

[Evaluation on the atmospheric correction methods for water color remote sensing by using HJ-1A/1B CCD image-taking Poyang Lake in China as a case].

HJ-1A/1B satellite CCD images have higher spatial and temporal resolution, making them of great potential in quantitatively monitoring the water quality of inland lakes. However, the atmospheric correction of the images restricts their application. Therefore, taking Poyang Lake, the biggest freshwater lake in China as study area , and using the in-situ data collected in 2009 and 2011, this paper compares the atmospheric correction results done by the four methods: FLAASH, 6S, COST and QUAC, and analyzes the influence of these atmospheric correction methods on the inversion accuracy of the total suspended sediments (TSS) concentration. The results indicate: (1) the band 1 (blue band) of HJ-1A/1B CCD satellite images should be recalibrated while being applied into water quality remote sensing. The accuracy of atmospheric correction done from band 2 (green band) and band 3 (red band) is higher than that of others , especially that of the correction done by FLAASH, 6S and COST is much higher while that of correction done by QUAC is lower. So the algorithms of QUAC should be pointedly improved. (2) The ratios done from band 2 and band 3 have a good match with in-situ data , with an average relative error of 8.2%, 9.5%, 7.6% and 11.6% respectively for FLAASH, 6S, COST and QUAC. Therefore, it would be better to use the ratio done from band 2 and band 3 as inversion factors in Poyang Lake. (3) It is found that the accuracy of directly building models by using the four atmospheric corrected results and the TSS concentration is higher than the models built by the in-situ remote sensing reflectance and the TSS concentration. The accuracy of the TSS concentration inverted by FLAASH, 6S and COST is much high with an average error of only 10.0%, 10.2% and 8.0% respectively, while the error inverted by QUAC is a little bit higher of being 18.6%. So it is suggested to build model with atmospheric correction results and the TSS concentration data, because it can avoid the cumulate error resulted from modeling by using the in-situ spectrum data. (4) Under a low requested situation, these four atmospheric correction algorithms can all be adopted; otherwise, the COST should be used in the case of lacking supplementary information.