Variations Of Meteorological Factors Research Articles

Observation of ozone deposition flux and its contribution to stomatal uptake over a winter wheat field in eastern China

Ground-level ozone (O3) poses a significant threat to food security in China. Therefore, it is imperative to conduct a comprehensive scientific evaluation of the potential hazards posed by O3 to agricultural crops. This study continuously observed variation in meteorological factors, O3 concentration, O3 deposition rate and flux, and quantified the distribution characteristics of O3 deposition flux in stomatal and non-stomatal pathways. Results suggested that the O3 dry deposition rate and flux in winter wheat fields exhibited relatively stable variations at night but pronounced fluctuations during the day. Their mean values were 0.31 cm s−1 and -0.0044 μmol m−2·s−1, respectively, with peak values occurring at 08:30 and 14:00. The cumulative O3 total flux during the main growth season of winter wheat was 26.1 mmol m−2, with stomatal and non-stomatal fluxes accounting for 7.7 mmol m−2 and 18.4 mmol m−2, respectively. The proportions of total O3 flux in stomatal and non-stomatal channels were 29.5% and 70.5%, respectively, with daytime proportions being 39.7% and 60.3%, respectively. These findings provide crucial insights for future accurate assessments of crop yield loss due to O3 at the earth's surface.

Air quality forecasting‐driven cloud resource allocation for sustainable energy consumption: An ensemble classifier approach

AbstractIn recent times, air quality prediction is turned out to be one of the important research topics among research communities to prevent lives from negative health impacts. Random fluctuations of PM2.5 level brought about by frequent variations in meteorological factors create difficulties air pollution management. Forecasting the quality of air using time series data serves as a defense mechanism against threatening hazards by providing immense support to take preventive measures. Besides, handling dynamic real time workloads, forecasted by the prediction model requires appropriate computing resources to distribute workloads based on demands. To achieve this goal, this paper proposes a new Air Quality Prediction‐enabled Resource Allocation scheme for cloud‐based software services, which offers dynamic adjustment of resources based on workload demands with high energy efficiency. The proposed system is a two phase system that executes both air quality prediction and resource allocation processes consecutively. A new weighted average ensemble classifier is designed by combining support vector machine (SVM), artificial neural network (ANN), and gradient boosting machine (GBM) techniques to measure PM2.5 level on time series information of Beijing PM2.5 dataset. The system then dynamically allocates appropriate computing resources using crossover particle swarm optimization (CPSO) algorithm based on the forecasted results of PM2.5 level. This system has the potential to contribute significantly to reducing energy consumption and improving air quality in cities worldwide. The experimental results conducted to determine the efficiency of the proposed system in terms of different metrics proves that it achieves greater performance with less error functions for PM2.5 level prediction as well as minimizes energy consumption for resource allocation when compared with existing methods.

Impacts of land use and land cover changes on local meteorology and PM2.5 concentrations in Changchun, Northeast China

Land use and land cover (LULC) changes have a considerable influence on the surface energy balance, altering regional meteorology and air quality. However, this impact is not quantified in Changchun, an important city in the old industrial base of Northeast China. In this study, based on the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model, the LULC2017 (LULC data in 2017) and LULC2001 (LULC data in 2001) scenarios were simulated for January and July 2017, respectively, to assess the impact of LULC changes on meteorology and fine particulate matter (PM2.5) concentrations in Changchun. The results show that the sensible heat flux in the urban expansion area (UEA) increased during the daytime, reaching a maximum value of 154 W/m2 and 162 W/m2, respectively, while the latent heat flux decreased during the daytime, reaching a maximum value of 22.84 W/m2 and 180.75 W/m2, respectively. Consequently, 2 m temperature (T2) increased by 4 °C and 3 °C, respectively; 10 m wind speed (WS10) increased by 1.05 m/s and 1.60 m/s, respectively; and planetary boundary layer height (PBLH) increased by 100 m and 117 m, respectively. These variations in meteorological factors can substantially impact the spatial distribution of air pollutants. In the UEA, PM2.5 concentrations decreased by 34 μg/m3 and 20 μg/m3 in January and July, respectively. The change in SO42− accounted for approximately 25% of the total concentration change of PM2.5, with a decrease of approximately 5–6 μg/m3 during the nighttime in January. Secondary organic aerosol (SOA) formed from biogenic volatile organic compounds (BVOC) precursors (BSOA) slightly decreased owing to the reduction in croplands dominated by green vegetation. Meanwhile, PM2.5 concentrations in the surrounding areas of the UEA increased significantly in January. The results of the process analysis based on the CMAQ model indicate that the main reason for the spatial variation of PM2.5 concentrations is the enhancement of transport and diffusion in the horizontal and vertical directions in the UEA. In January, the negative contribution of vertical advection (ZADV) and horizontal advection (HADV) processes to PM2.5 in the UEA increased by 25 μg/m3 and 40 μg/m3, respectively. Vertical diffusion (VDIF) process caused an increase in PM2.5 diffusion by 40 μg/m3 and 16 μg/m3 during the daytime and nighttime in the UEA, respectively. In July, the negative contribution of VDIF and HADV processes to PM2.5 increased by 40 μg/m3 and 32 μg/m3 during the nighttime in the UEA, respectively.

Quantitative influences of interannual variations in meteorological factors on surface ozone concentration in the hot summer of 2018 in Japan

In this study, the high surface O 3 episodes in the hot summer in Japan in July 2018 are studied using two models, NHM-Chem and ASUCA-Chem. The model performances are similar to each other with both models tending to overestimate the observed surface O 3 by ∼5–10 ppbv. The meteorological factors causing the interannual changes of surface O 3 are investigated through sensitivity tests of NHM-Chem using meteorological fields of different years, i.e., July 2007 and 2012. July 2007 and 2012 represent cold and normal summers, respectively, with respect to the monthly mean surface temperature in Japan. The hot summer provides favorable conditions for the O 3 formation, such as a higher temperature and a higher solar radiation. However, the monthly mean surface wind speed in July 2018 is greater than that of the other periods, causing a negative effect on the monthly surface O 3 concentrations because of faster dilution and diffusion in certain locations. Over the Kanto plain, which is the most populated region of Japan, the monthly mean surface temperature is ∼2 K higher than the normal values; however, both observation and simulation demonstrate that the monthly mean surface O 3 is lower than the normal temperature summer (July 2012) by 4–6 ppbv. The sensitivity tests indicate that the enhanced biogenic volatile organic compound emissions increase surface O 3 by 4–5 ppbv, but the wind field changes decrease surface O 3 by 9–10 ppbv. Heat wave is associated with high surface O 3 episodes; however, the monthly mean value is a mixed result of many other meteorological events in addition to the heat wave. The interannual changes in the monthly surface O 3 can vary depending on magnitude of the positive and negative effects at each location. • Monthly surface O 3 in hot summer is studied by ASUCA-Chem and NHM-Chem. • Increased BVOC emission due to higher temperature enhanced monthly surface O 3 . • Greater wind speed during the period results in decreased monthly surface O 3 .

Simulated net ecosystem productivity of subtropical forests and its response to climate change in Zhejiang Province, China.

Net ecosystem productivity (NEP) is an important index that indicates the carbon sequestration capacity of forest ecosystems. However, the effect of climate change on the spatiotemporal variability in NEP is still unclear. Using the Integrated Terrestrial Ecosystem Carbon-budget (InTEC) model, this study takes the typical subtropical forests in the Zhejiang Province, China as an example, simulated the spatiotemporal patterns of forest NEP from 1979 to 2079 based on historically observed climate data (1979-2015) and data from three representative concentration pathway (RCP) scenarios (RCP2.6, RCP4.5, and RCP8.5) provided by the Coupled Model Intercomparison Project 5 (CMIP5). We analyzed the responses of NEP at different forest age classes to the variation in meteorological factors. The NEP of Zhejiang's forests decreased from 1979 to 1985 and then increased from 1985 to 2015, with an annual increase rate of 9.66 g C·m-2·yr-1 and a cumulative NEP of 364.99 Tg·C. Forest NEP decreased from 2016 to 2079; however, the cumulative NEP continued to increase. The simulated cumulative NEP under the RCP2.6, RCP4.5, and RCP8.5 scenarios was 750 Tg·C, 866 Tg·C, and 958 Tg·C, respectively, at the end of 2079. Partial correlation analysis between forest NEP at different age stages and meteorological factors showed that temperature is the key climatic factor that affects the carbon sequestration capacity of juvenile forests (1979-1999), while precipitation is the key climatic factor that affects middle-aged forests (2000-2015) and mature forests (2016-2079). Adopting appropriate management strategies for forests, such as selective cutting of different ages, is critical for the subtropical forests to adapt to climate change and maintain their high carbon sink capacity.

The Impact of Meteorological Factors and Air Pollutants on Acute Coronary Syndrome.

Purpose of ReviewSeveral studies have found that air pollution and climate change can have an impact on acute coronary syndromes (ACS), the leading cause of death worldwide. We synthesized the latest information about the impact of air pollution and climate change on ACS, the latest data about the pathophysiological mechanisms of meteorological factors and atmospheric pollutants on atherosclerotic disease, and an overall image of air pollution and coronary heart disease in the context of the COVID-19 pandemic.Recent FindingsThe variation of meteorological factors in different seasons increased the risk of ACS. Both the increase and the decrease in apparent temperature were found to be risk factors for ACS admissions. It was also demonstrated that exposure to high concentrations of air pollutants, especially particulate matter, increased cardiovascular morbidity and mortality.SummaryClimate change as well as increased emissions of air pollutants have a major impact on ACS. The industrialization era and the growing population cause a constant increase in air pollution worldwide. Thus, the number of ACS favored by air pollution and the variations in meteorological factors is expected to increase dramatically in the next few years.

Sensitivity of PM2.5 and O3 pollution episodes to meteorological factors over the North China Plain

The Comprehensive Air-quality Model with extensions (CAMx) was used to explore the sensitivity of PM2.5 and O3 concentrations to four selected meteorological factors: wind speed, temperature, water vapor mixing ratio (Q), and planetary boundary layer height (PBLH) during two pollution episodes over the North China Plain (NCP). We also investigated the impact pathways of different meteorological factors on the formation of PM2.5 and O3. It is found that PM2.5 was more sensitive to the selected meteorological factors in the southeastern NCP, where high anthropogenic emissions and severe air pollution occur. Large variations were observed along the Taihang Mountains, where the height of the terrain changes dramatically. The sensitivity of O3 to wind speed, PBLH, temperature, and Q was mainly determined by the inhibition effects of PM2.5 in winter, while in summer, the complex chemical reactions were dominant. Significant diurnal variations of process analysis (PA) results were observed under various meteorological conditions. Higher temperature generally enhance heterogeneous chemistry and transport of NO3− through the top boundary layer during night-time in winter, however, in summer, the heterogeneous chemistry of NO3− and NH4+ during daytime were the major pathways to the increased PM2.5 due to increased temperature. Moreover, temperature alter PM2.5 concentrations through affecting vertical diffusivity and relative humidity, and alter O3 concentrations by affecting the gas phase chemistry and mass fluxes through the top boundary layer. Q mainly affects the rate of chemical reactions of PM2.5 and O3. The different impact pathways suggest that it is essential to consider variations in meteorological factors, in addition to the direct impacts of wind speed and PBLH, more attention should be paid to the complex impacts of temperature and Q, when developing emission control strategies.

Analysis of PM10 dispersion models from coal-fired power plant activities in North Sumatera by using CALPUFF

Nearly 35% of electricity generation in the North Sumatra region comes from coal-fired steam power plants. The existence of coal-fired power plants also has a negative impact in the form of a decrease in ambient air quality. To determine the pollutant dispersing concentration from the chimney, it can be done by modelling the pollutant disperse pattern. This study uses the CALPUFF model because this model is non-steady state and follows variations in meteorological factors. The research location is in Pangkalan Susu coal-fired power plants with PM10 parameters. The research aims to calculate the concentration of PM10 with CALPUFF and to validate modelling. The results showed that the concentration of the PM10 model obtained was 0.07-0.86 μg/m3, and the observation was 12.77 - 56.45 μg/m3. The CALPUFF model show that the impact distribution area is in the direction of the wind direction of the wind rose and the affected area is in the southwest of the Pangkalan Susu coal-fired power plants. The model validation for d = 0.968, r = 0.922 and FB = 1.962, which means that the CALPUFF model is valid and can be applied to estimate the impact distribution area at Pangkalan Susu coal-fired power plants.

Ozone variability induced by synoptic weather patterns in warm seasons of 2014–2018 over the Yangtze River Delta region, China

Abstract. Ozone (O3) pollution is of great concern in the Yangtze River Delta (YRD) region of China, and the regional O3 pollution is closely associated with dominant weather systems. With a focus on the warm seasons (April–September) from 2014 to 2018, we quantitatively analyze the characteristics of O3 variations over the YRD, the impacts of large-scale and synoptic-scale circulations on the O3 variations and the associated meteorological controlling factors, based on observed ground-level O3 and meteorological data. Our analysis suggests an increasing trend of the regional mean O3 concentration in the YRD at 1.8 ppb per year over 2014–2018. Spatially, the empirical orthogonal function analysis suggests the dominant mode accounting for 65.7 % variation in O3, implying that an increase in O3 is the dominant tendency in the entire YRD region. Meteorology is estimated to increase the regional mean O3 concentration by 3.1 ppb at most from 2014 to 2018. In particular, relative humidity (RH) plays the most important role in modulating the inter-annual O3 variation, followed by solar radiation (SR) and low cloud cover (LCC). As atmospheric circulations can affect local meteorological factors and O3 levels, we identify five dominant synoptic weather patterns (SWPs) in the warm seasons in the YRD using the t-mode principal component analysis classification. The typical weather systems of SWPs include the western Pacific Subtropical High (WPSH) under SWP1, a continental high and the Aleutian low under SWP2, an extratropical cyclone under SWP3, a southern low pressure and WPSH under SWP4 and the north China anticyclone under SWP5. The variations of the five SWPs are all favorable to the increase in O3 concentrations over 2014–2018. However, crucial meteorological factors leading to increases in O3 concentrations are different under different SWPs. These factors are identified as significant decreases in RH and increases in SR under SWP1, 4 and 5, significant decreases in RH, increases in SR and air temperature (T2) under SWP2 and significant decreases in RH under SWP3. Under SWP1, 4 and 5, significant decreases in RH and increases in SR are predominantly caused by the WPSH weakening under SWP1, the southern low pressure weakening under SWP4 and the north China anticyclone weakening under SWP5. Under SWP2, significant decreases in RH, increases in SR and T2 are mainly produced by the Aleutian low extending southward and a continental high weakening. Under SWP3, significant decreases in RH are mainly induced by an extratropical cyclone strengthening. These changes in atmospheric circulations prevent the water vapor in the southern and northern sea from being transported to the YRD and result in RH significantly decreasing under each SWP. In addition, strengthened descending motions (behind the strengthening trough and in front of the strengthening ridge) lead to decreases in LCC and significant increases in SR under SWP1, 2, 4 and 5. The significant increases in T2 would be due to weakening cold flow introduced by a weakening continental high. Most importantly, the changes in the SWP intensity can make large variations in meteorological factors and contribute more to the O3 inter-annual variation than the changes in the SWP frequency. Finally, we reconstruct an empirical orthogonal function (EOF) mode 1 time series that is highly correlated with the original O3 time series, and the reconstructed time series performs well in defining the change in SWP intensity according to the unique feature under each of the SWPs.

The Short-term Effects of Temperature on Infectious Diarrhea among Children under 5 Years Old in Jiangsu, China: A Time-series Study (2015\u20132019)

SummaryThe association between meteorological factors and infectious diarrhea has been widely studied in many countries. However, investigation among children under 5 years old in Jiangsu, China remains quite limited. Data including infectious diarrhea cases among children under five years old and daily meteorological indexes in Jiangsu, China from 2015 to 2019 were collected. The lag-effects up to 21 days of daily maximum temperature (Tmax) on infectious diarrhea were explored using a quasi-Poisson regression with a distributed lag non-linear model (DLNM) approach. The cases number of infectious diarrhea was significantly associated with seasonal variation of meteorological factors, and the burden of disease mainly occurred among children aged 0–2 years old. Moreover, when the reference value was set at 16.7°C, Tmax had a significant lag-effect on cases of infectious diarrhea among children under 5 years old in Jiangsu Province, which was increased remarkably in cold weather with the highest risk at 8°C. The results of DLNM analysis implicated that the lag-effect of Tmax varied among the 13 cities in Jiangsu and had significant differences in 8 cities. The highest risk of Tmax was presented at 5 lag days in Huaian with a maximum RR of 1.18 (95% CI: 1.09, 1.29). Suzhou which had the highest number of diarrhea cases (15830 cases), had a maximum RR of 1.04 (95% CI:1.03, 1.05) on lag 15 days. Tmax is a considerable indicator to predict the epidemic of infectious diarrhea among 13 cities in Jiangsu, which reminds us that in cold seasons, more preventive strategies and measures should be done to prevent infectious diarrhea.

Comparison of the differences of sensible heat flux observation methods at different spatial scales in North China Plain

Understanding the estimation of sensible heat flux on heterogeneous underlying surface of farmland is of great environmental importance for alleviating ecological pollution and adapting agricultural water management. Data measurements were conducted to evaluate the difference of sensible heat flux under large aperture scintillometer (H-las) and eddy covariance (H-ec) under various underlying surfaces in North China Plain. Four typical periods represented as the crop periods (January, March, May, and August) were selected to investigate the correlation between the H-las and H-ec as well as relative error assessment. Results showed that the H-las and H-ec were consistent on the non-uniform underlying surface as time; the correlation coefficient (R2) were 0.75 in January, 0.65 in March, 0.65 in May, and 0.60 in August, respectively; the coverage of LAS footprints was 45 times that of single-point observations. In the prevailing wind direction, most of the EC source areas were homogeneous farmland, while the LAS source areas also include residential areas and woodland; the H-las was slightly higher than H-ec by 1.61–21.21%, which results from the non-uniformity of underlying surface, the variation of meteorological factors, the inconsistency source areas, and the deviation of EC. The method of LAS is recommended for measuring average sensible heat flux in this study area accordingly.

Analysis distribution sulfur dioxide and nitrogen dioxide concentration from PLTU Pangkalan susu with callpuff method

Coal-fired power plants will emit several types of pollutants into the ambient air such as particulates and gases. One way to estimate the extent of the impact distribution of these pollutants is by using air quality modeling. The model used in this study is Calpuff, where this model is a non-steady state model and is influenced by variations in meteorological factors. The research location is PLTU Pangkalan Susu (2x200 MW) with SO2 and NO2 parameters. The purpose of this study was to calculate the concentrations of SO2 and NO2 with Calpuff, to validate modeling with field observations and to simulate the distribution of impacts. The results showed that the concentration of SO2 model obtained was 0.32 - 3.57 µg/m3 and NO2 was 0.51 - 5.15 µg/m3. Meanwhile, the observation results showed that the SO2 concentration was 27 - 39.88 µg/m3 and NO2 was 19.77 - 29.73 µg/m3. The simulation results of the distribution of SO2 and NO2 concentrations with the Calpuff model show that the impact distribution area is in the direction of the wind in the windrose and the affected area is in the southwest of the PLTU Pangkalan Susu. The results of model validation for the values ​​of d = 0.97, r = 0.616 - 0.665 and FB = -1.719 - -1.849, which means that the Calpuff model is quite valid and can be applied to predict the impact distribution area at PLTU Pangkalan Susu.

Effects of variations in meteorological factors on daily hospital visits for asthma: A time-series study

Few studies have explored the relationships between meteorological factors and asthma. This study explored the associations between daily variations in meteorological factors and hospital visits for asthma among different ages, genders, and asthma subtypes in Shenyang, China. A distributed lag non-linear model with Poisson regression was used; confounding factors included day of the week, holidays, and seasonal patterns, and long-term trends and air pollutants were adjusted using natural cubic splines. The meteorological factor with the largest cumulative effect was barometric pressure, which increased the risk of hospital visits for adult asthma (relative risk [RR] = 2.414), followed by maximum wind speed, which increased hospital visits for asthma for children aged 0–5 years old (RR = 1.47), and pressure, which increased hospital visits for bronchial asthma (RR = 1.298). Meteorological factors showed stronger associations with asthma than air pollutants. Further research should focus more on the effects of meteorological factors on asthma.

Effect of meteorological factors on influenza-like illness from 2012 to 2015 in Huludao, a northeastern city in China.

BackgroundThis study aims to describe the epidemiological patterns of influenza-like illness (ILI) in Huludao, China and seek scientific evidence on the link of ILI activity with weather factors.MethodsSurveillance data of ILI cases between January 2012 and December 2015 was collected in Huludao Central Hospital, meteorological data was obtained from the China Meteorological Data Service Center. Generalized additive model (GAM) was used to seek the relationship between the number of ILI cases and the meteorological factors. Multiple Smoothing parameter estimation was made on the basis of Poisson distribution, where the number of weekly ILI cases was treated as response, and the smoothness of weather was treated as covariates. Lag time was determined by the smallest Akaike information criterion (AIC). Smoothing coefficients were estimated for the prediction of the number of ILI cases.ResultsA total of 29, 622 ILI cases were observed during the study period, with children ILI cases constituted 86.77%. The association between ILI activity and meteorological factors varied across different lag periods. The lag time for average air temperature, maximum air temperature, minimum air temperature, vapor pressure and relative humidity were 2, 2, 1, 1 and 0 weeks, respectively. Average air temperature, maximum air temperature, minimum air temperature, vapor pressure and relative humidity could explain 16.5%, 9.5%, 18.0%, 15.9% and 7.7% of the deviance, respectively. Among the temperature indexes, the minimum temperature played the most important role. The number of ILI cases peaked when minimum temperature was around −13 °C in winter and 18 °C in summer. The number of cases peaked when the relative humidity was equal to 43% and then began to decrease with the increase of relative humidity. When the humidity exceeded 76%, the number of ILI cases began to rise.ConclusionsThe present study first analyzed the relationship between meteorological factors and ILI cases with special consideration of the length of lag period in Huludao, China. Low air temperature and low relative humidity (cold and dry weather condition) played a considerable role in the epidemic pattern of ILI cases. The trend of ILI activity could be possibly predicted by the variation of meteorological factors.

Temporal variations in the diversity of airborne fungal spores in a Mediterranean high altitude site

Relationships between meteorological factors and airborne fungal spore concentrations at high altitudes are virtually unknown. We used cross-correlation analyses to test the relationships between daily variation in meteorological factors (i.e., temperature, humidity and wind speed) and airborne spore concentration, diversity (Shannon and Simpson indices) and evenness (Pielou index) in an Apennine high altitude site (Gran Sasso Massif, 2117 m elevation). Daily average concentration of spores in this high altitude site was much lower than that observed at a low altitude site in the same area, which can be explained by the environmental conditions at high altitudes. We found that diversity and evenness tended to be negatively correlated with temperature and positively with humidity and wind speed with some delay, whereas abundance tended to be positively correlated with temperature and wind, but negatively with humidity. These relationships can be explained by the fact that rain increases turnover by removing dry spores of Cladosporium (the most abundant taxon) and aerosolizing wet ones. The high dominance of the most abundant taxon is a reflection of the extreme climatic conditions at high altitudes.

Responses of the hydrological regime to variations in meteorological factors under climate change of the Tibetan plateau

Meteorological factors and the hydrologic cycle of the Tibetan plateau (TP) significantly influence the water resource supply, ecology, and social economy of wide downstream areas in Asia. This study evaluates changes in meteorological factors (e.g., precipitation, air temperature, and snowfall) and corresponding responses in the hydrological regime under future climate change scenarios in both the TP and the downstream areas. The Lancang River basin (LRB), located in the southeast TP and known as the upper Mekong River basin, is selected as the case study area. Future climate change projections are derived from five independent GCMs of CMIP5 and their multi-model ensemble. The variable infiltration capacity (VIC) distributed hydrological model is used to generate streamflow projections in future scenarios. Results show that precipitation and air temperature in both the lower LRB (representing the downstream area of TP) and upper LRB (representing the area in TP) are expected to increase substantially in the future, with higher increments in air temperature found in the upper LRB under high-emission scenarios. Snowfall, snow water equivalent (SWE), and snowmelt are commonly found to decrease with increasing air temperature, and the snow melt time tends to be earlier. Significantly increasing mean and extreme streamflow caused by increasing precipitation are anticipated in the future. The low flow shows much higher relative increments at the upstream of TP, which is mainly caused by changes in snow regulating (decreased snowfall and earlier snowmelt). However, those effects show weak influence on the streamflow in the downstream area, which would be more largely impact by the local precipitation change. In the future, irrigation, hydropower, and navigation in the TP could benefit from increased low flow in the TP, but the consistently increasing extreme high flow may indicate greater flood risk in the TP and downstream areas.

Climatic Factors and Influenza Transmission, Spain, 2010-2015.

The spatio-temporal distribution of influenza is linked to variations in meteorological factors, like temperature, absolute humidity, or the amount of rainfall. The aim of this study was to analyse the association between influenza activity, and meteorological variables in Spain, across five influenza seasons: 2010–2011 through to 2014–2015 using generalized linear negative binomial mixed models that we calculated the weekly influenza proxies, defined as the weekly influenza-like illness rates, multiplied by the weekly proportion of respiratory specimens that tested positive for influenza. The results showed an association between influenza transmission and dew point and cumulative precipitation. In increase in the dew point temperature of 5 degrees produces a 7% decrease in the Weekly Influenza Proxy (RR 0.928, IC: 0.891–0.966), and while an increase of 10 mm in weekly rainfall equates to a 17% increase in the Weekly Influenza Proxy (RR 1.172, IC: 1.097–1.251). Influenza transmission in Spain is influenced by variations in meteorological variables as temperature, absolute humidity, or the amount of rainfall.

Correlations between weather conditions and airborne pollen concentration and diversity in a Mediterranean high-altitude site disclose unexpected temporal patterns

Relationships between meteorological factors and airborne pollen concentrations at high altitudes are virtually unknown. We used cross-correlation analyses to test the relationships between daily variation in meteorological factors (i.e. temperature, humidity and wind speed) and airborne pollen concentration, diversity (number of families and Shannon and Simpson diversity indices) and evenness (Pielou index) in an Apennine high-altitude site (Gran Sasso Massif, 2117 m elevation). In contrast to patterns observed at low altitudes, the temperature had a negative correlation with pollen abundance and diversity, whereas humidity had a positive correlation. The unexpected negative correlations with temperature can be explained with the particular position of our sampling site. Wind speed was positively correlated with pollen diversity and abundance in the short term, which can be explained by the fact that higher wind speed promotes both primary emission of pollen from the anthers and subsequent re-suspension. Evenness and wind speed were negatively correlated in the short term because of the different response of different species to meteorological conditions. In the longer term, the average concentrations of the various taxa tend to reach similar values, leading to increased values of diversity. Our finding of a decrease in pollen emission with increasing temperature has important implications for the study of the impacts of global change on high-altitude plant communities. We also detected a high abundance of Cupressaceae/Taxaceae pollen, a reflection of the expansion of thermophilic species, such as Juniperus, due to climate change.

A modeling study on the effect of urban land surface forcing to regional meteorology and air quality over South China

The change of land-use from natural to artificial surface induced by urban expansion can deeply impact the city environment. In this paper, the model WRF/Chem is applied to explore the effect of this change on regional meteorology and air quality over South China, where people have witnessed a rapid rate of urbanization. Two sets of urban maps are adopted to stand for the pre-urbanization and the present urban land-use distributions. Month-long simulations are conducted for January and July, 2014. The results show that urban expansion can obviously change the weather conditions around the big cities of South China. Especially in the Pearl River Delta region (PRD), the urban land-use change can increase the sensible heat flux by 40 W/m2 in January and 80 W/m2 in July, while decrease the latent heat flux about −50 W/m2 in January and −120 W/m2 in July. In the consequent, 2-m air temperature (T2) increases as much as 1 °C and 2 °C (respective to January and July), planetary boundary layer height (PBLH) rises up by 100–150 m and 300 m, 10-m wind speed (WS10) decreases by −1.2 m/s and −0.3 m/s, and 2-m specific humidity is reduced by −0.8 g/kg and −1.5 g/kg. Also, the precipitation in July can be increased as much as 120 mm, with more heavy rains and rainstorms. These variations of meteorological factors can significantly impact the spatial and vertical distribution of air pollutants as well. In PRD, the enhanced updraft can reduce the surface concentrations of PM10 by −40 μg/m3 (30%) in January and −80 μg/m3 (50%) in July, but produce a correlating increase in the concentrations at higher atmospheric layers. However, according to the increase in T2 and the decrease in surface NO, the surface concentrations of O3 in PRD can increase by 2–6 ppb in January and 8–12 ppb in July. Meanwhile, there is a significant increase in the O3 concentrations at upper layers above PRD, which should be attributed to the increase in air temperature and the enhanced upward transport of O3 and its precursors. As for some relative small cities, such as Haikou, there is very little variation in surface PM10 and O3 in both months, implying less urbanization in these areas. Moreover, the depletion of O3 by NO may be the main cause of the reduction of O3 at upper layers in these small cities.

Trace lithium is inversely associated with male suicide after adjustment of climatic factors

BackgroundPreviously, we showed the inverse association between lithium in drinking water and male suicide in Kyushu Island. The narrow variation in meteorological factors of Kyushu Island and a considerable amount of evidence regarding the role of the factors on suicide provoked the necessities of adjusting the association by the wide variation in sunshine, temperature, rain fall, and snow fall. MethodsTo keep the wide variation in meteorological factors, we combined the data of Kyushu (the southernmost city is Itoman, 26°) and Hokkaido (the northernmost city is Wakkanai, 45°). Multiple regression analyses were used to predict suicide SMRs (total, male and female) by lithium levels in drinking water and meteorological factors. ResultsAfter adjustment of meteorological factors, lithium levels were significantly and inversely associated with male suicide SMRs, but not with total or female suicide SMRs, across the 153 cities of Hokkaido and Kyushu Islands. Moreover, annual total sunshine and annual mean temperature were significantly and inversely associated with male suicide SMRs whereas annual total rainfall was significantly and directly associated with male suicide SMRs. LimitationsThe limitations of the present study include the lack of data relevant to lithium levels in food and the proportion of the population who drank tap water and their consumption habits. ConclusionsThe present findings suggest that trace lithium is inversely associated with male but not female suicide after adjustment of meteorological factors.