First attempts to obtain a reference drift curve for traditional olive grove's plantations following ISO 22866

The current standard for the field measurements of spray drift (ISO 22866) is the only official standard for drift measurements in field conditions for all type of crops, including bushes and trees. A series of field trials following all the requirements established in the standard were arranged in a traditional olive grove in Córdoba (south of Spain). The aims of the study were to evaluate the applicability of the current standard procedure to the particular conditions of traditional olive trees plantations, to evaluate the critical requirements for performing the tests and to obtain a specific drift curve for such as important and specific crop as olive trees in traditional plantations, considering the enormous area covered by this type of crop all around the world. Results showed that the field trials incur a very complex process due to the particular conditions of the crop and the very precise environmental requirements. Furthermore, the trials offered a very low level of repeatability as the drift values varied significantly from one spray application to the next, with the obtained results being closely related to the wind speed, even when considering the standard minimum value of 1 m·s^-1. The collector's placement with respect to the position of the isolated trees was determined as being critical since this substantially modifies the ground deposit in the first 5 m. Even though, a new drift curve for olive trees in traditional plantation has been defined, giving an interesting tool for regulatory aspects. Conclusions indicated that a deep review of the official standard is needed to allow its application to the most relevant orchard/fruit crops.

Cluster analysis of fine particulate matter (PM2.5) emissions and its bioreactivity in the vicinity of a petrochemical complex

This study evaluated associations between the bioreactivity of PM_2.5in vitro and emission sources in the vicinity of a petrochemical complex in Taiwan. The average PM_2.5 was 30.2 μg/m³ from 9 February to 23 March 2016, and the PM_2.5 was clustered in long-range transport (with major local source) (12.8 μg/m³), and major (17.3 μg/m³) and minor industrial emissions (4.7 μg/m³) using a k-means clustering model. A reduction in cell viability and increases in the cytotoxicity-related lactate dehydrogenase (LDH), oxidative stress-related 8-isoprostane, and inflammation-related interleukin (IL)-6 occurred due to PM_2.5 in a dose-dependent manner. The PM_2.5 from major industrial emissions was significantly correlated with increased 8-isoprostane and IL-6, but this was not observed for long-range transport or minor industrial emissions. The bulk metal concentration was 9.52 ng/m³ in PM_2.5. We further observed that As, Ba, Cd, and Se were correlated with LDH in the long-range transport group. Pb in PM_2.5 from the major industrial emissions was correlated with LDH, whereas Pb and Se were correlated with 8-isoprostane. Sr was correlated with cell viability in the minor industrial emissions group. We demonstrated a new approach to investigate particle bioreactivity, which suggested that petrochemical-emitted PM_2.5 should be a concern for surrounding residents' health.

Changes in relative fit of human heat stress indices to cardiovascular, respiratory, and renal hospitalizations across five Australian urban populations

Various human heat stress indices have been developed to relate atmospheric measures of extreme heat to human health impacts, but the usefulness of different indices across various health impacts and in different populations is poorly understood. This paper determines which heat stress indices best fit hospital admissions for sets of cardiovascular, respiratory, and renal diseases across five Australian cities. We hypothesized that the best indices would be largely dependent on location. We fit parent models to these counts in the summers (November-March) between 2001 and 2013 using negative binomial regression. We then added 15 heat stress indices to these models, ranking their goodness of fit using the Akaike information criterion. Admissions for each health outcome were nearly always higher in hot or humid conditions. Contrary to our hypothesis that location would determine the best-fitting heat stress index, we found that the best indices were related largely by health outcome of interest, rather than location as hypothesized. In particular, heatwave and temperature indices had the best fit to cardiovascular admissions, humidity indices had the best fit to respiratory admissions, and combined heat-humidity indices had the best fit to renal admissions. With a few exceptions, the results were similar across all five cities. The best-fitting heat stress indices appear to be useful across several Australian cities with differing climates, but they may have varying usefulness depending on the outcome of interest. These findings suggest that future research on heat and health impacts, and in particular hospital demand modeling, could better reflect reality if it avoided "all-cause" health outcomes and used heat stress indices appropriate to specific diseases and disease groups.

A new method for wind speed forecasting based on copula theory

How to determine representative wind speed is crucial in wind resource assessment. Accurate wind resource assessments are important to wind farms development. Linear regressions are usually used to obtain the representative wind speed. However, terrain flexibility of wind farm and long distance between wind speed sites often lead to low correlation. In this study, copula method is used to determine the representative year's wind speed in wind farm by interpreting the interaction of the local wind farm and the meteorological station. The result shows that the method proposed here can not only determine the relationship between the local anemometric tower and nearby meteorological station through Kendall's tau, but also determine the joint distribution without assuming the variables to be independent. Moreover, the representative wind data can be obtained by the conditional distribution much more reasonably. We hope this study could provide scientific reference for accurate wind resource assessments.

Ecological covariates based predictive model of malaria risk in the state of Chhattisgarh, India

Malaria being an endemic disease in the state of Chhattisgarh and ecologically dependent mosquito-borne disease, the study is intended to identify the ecological covariates of malaria risk in districts of the state and to build a suitable predictive model based on those predictors which could assist developing a weather based early warning system. This secondary data based analysis used one month lagged district level malaria positive cases as response variable and ecological covariates as independent variables which were tested with fixed effect panelled negative binomial regression models. Interactions among the covariates were explored using two way factorial interaction in the model. Although malaria risk in the state possesses perennial characteristics, higher parasitic incidence was observed during the rainy and winter seasons. The univariate analysis indicated that the malaria incidence risk was statistically significant associated with rainfall, maximum humidity, minimum temperature, wind speed, and forest cover (p < 0.05). The efficient predictive model include the forest cover [IRR-1.033 (1.024-1.042)], maximum humidity [IRR-1.016 (1.013-1.018)], and two-way factorial interactions between district specific averaged monthly minimum temperature and monthly minimum temperature, monthly minimum temperature was statistically significant [IRR-1.44 (1.231-1.695)] whereas the interaction term has a protective effect [IRR-0.982 (0.974-0.990)] against malaria infections. Forest cover, maximum humidity, minimum temperature and wind speed emerged as potential covariates to be used in predictive models for modelling the malaria risk in the state which could be efficiently used for early warning systems in the state.

Assessment of the clear-sky bias issue using continuous PM10 data from two AERONET sites in Korea

A bias in clear-sky conditions that will be involved in estimating particulate matter (PM) concentration from aerosol optical depth (AOD) was examined using PM₁₀ from two Aerosol Robotic Network sites in Korea. The study periods were between 2004 and 2007 at Anmyon and between 2003 and 2011 at Gosan, when both PM₁₀ and AOD were available. Mean PM₁₀ when AOD was available (PM_AOD) was higher than that from all PM₁₀ data (PM_all) by 5.1 and 9.9μg/m³ at Anmyon and Gosan, which accounted for 11% and 26% of PM_all, respectively. Because of a difference between mean PM₁₀ under daytime clear-sky conditions (PM_clear) and PM_AOD, the variations in ΔPM₁₀, the difference of PM_all from PM_clear rather than from PM_AOD, were investigated. Although monthly variations in ΔPM₁₀ at the two sites were different, they were positively correlated to those in ΔT, similarly defined as ΔPM₁₀ except for temperature, at both sites. ΔPM₁₀ at Anmyon decreased to a negative value in January due to an influence of the Siberian continental high-pressure system while ΔPM₁₀ at Gosan was high in winter due to an effect of photochemical production at higher temperatures than at Anmyon.

Combined physical, chemical and biological factors shape Alexandrium ostenfeldii blooms in The Netherlands

Harmful algal blooms (HABs) are globally expanding, compromising water quality worldwide. HAB dynamics are determined by a complex interplay of abiotic and biotic factors, and their emergence has often been linked to eutrophication, and more recently to climate change. The dinoflagellate Alexandrium is one of the most widespread HAB genera and its success is based on key functional traits like allelopathy, mixotrophy, cyst formation and nutrient retrieval migrations. Since 2012, dense Alexandrium ostenfeldii blooms (up to 4500cellsmL^-1) have recurred annually in a creek located in the southwest of the Netherlands, an area characterized by intense agriculture and aquaculture. We investigated how physical, chemical and biological factors influenced A. ostenfeldii bloom dynamics over three consecutive years (2013-2015). Overall, we found a decrease in the magnitude of the bloom over the years that could largely be linked to changing weather conditions during summer. More specifically, low salinities due to excessive rainfall and increased wind speed corresponded to a delayed A. ostenfeldii bloom with reduced population densities in 2015. Within each year, highest population densities generally corresponded to high temperatures, low DIN:DIP ratios and low grazer densities. Together, our results demonstrate an important role of nutrient availability, absence of grazing, and particularly of the physical environment on the magnitude and duration of A. ostenfeldii blooms. Our results suggest that predicted changes in the physical environment may enhance bloom development in future coastal waters and embayments.

Public health risks of prolonged fine particle events associated with stagnation and air quality index based on fine particle matter with a diameter <2.5 μm in the Kaoping region of Taiwan

The increasing frequency of droughts in tropical and sub-tropical areas since 1970 due to climate change requires a better understanding of the relationship between public health and long-duration fine particle events (FPE; defined as a day with an average PM_2.5 ≥ 35.5 μg/m³) associated with rainfall and wind speed. In the Kaoping region of Taiwan, 94.46 % of the daily average PM_2.5 in winter exceeds the limit established by 2005 World Health Organization (WHO) guidelines. This study investigated the differences in winter weather characteristics and health effects between non-FPE and FPE days, and the performance of air quality indexes on FPE days. Z-statistics for one-tailed tests, multiplicative decomposition models, logarithmic regression, and product-moment correlations were used for the analysis. The results indicate that mean wind speeds, rainfall hours, and air temperature were significantly decreased on FPE days. Daily mean PM_2.5 concentrations were positively correlated to the duration of FPE days. The duration of FPE days was positively related to the length of drought (r = 0.97, P < 0.05). The number of respiratory admissions was positively correlated with the FPE duration (r ² = 0.60). The age groups >15 years experienced the largest average reduction in asthma admissions on lag-days. Compared to the pollutant standard index (PSI) and revised air quality index (RAQI), the PM_2.5 index is more representative and sensitive to changes in PM_2.5 concentrations.

Meteorological and hydrological conditions driving the formation and disappearance of black blooms, an ecological disaster phenomena of eutrophication and algal blooms

Potentially toxic black blooms can disrupt drinking water treatment plants and have fatal effects on aquatic ecosystems; therefore, lake management is required to determine whether conditions are favorable for the formation and disappearance of black blooms in water supply sources. Long-term climate background, short-term thresholds of meteorological and hydrological conditions, and the duration of harmful algal blooms (HABs) were investigated as factors affecting the formation and disappearance of black blooms in hyper-eutrophic Lake Taihu. Long-term climate warming (0.31°C/decade), decreases in wind speed (0.26m/s per decade) and air pressure (0.16hPa/decade), and the increase in the meteorological index of black blooms (3.6days/decade) in Lake Taihu over the past 51years provided climate conditions conducive to the formation and occurrence of black blooms. A total of 16 black bloom events with an area larger than 0.1km(2) were observed from 2007 to 2014. Several critical thresholds for short-term meteorological and hydrological conditions were determined for the formation of black blooms, including a five-day average air temperature above 25°C, a five-day average wind speed <2.6m/s, average precipitation of five consecutive days close to 0, and continuous HAB accumulation for >5days. Heavy precipitation events, sudden cooling, and large wind disturbances were the driving factors of black blooms' disappearance. The use of a coupling model that combines the remote sensing of HABs with environmental, meteorological, and hydrological observations could permit an adequate and timely response to black blooms in drinking water sources.

The association between wind-related variables and stroke symptom onset: A case-crossover study on Jeju Island

BACKGROUND

Although several studies have investigated the effects of ambient temperature on the risk of stroke, few studies have examined the relationship between other meteorological conditions and stroke. Therefore, the aim of this study was to analyze the association between wind-related variables and stroke symptoms onset.

METHODS

Data regarding the onset of stroke symptoms occurring between January 1, 2006, and December 31, 2007 on Jeju Island were collected from the Jeju National University Hospital stroke registry. A fixed-strata case-crossover analysis based on time of onset and adjusted for ambient temperature, relative humidity, air pressure, and pollutants was used to analyze the effects of wind speed, the daily wind speed range (DWR), and the wind chill index on stroke symptom onset using varied lag terms. Models examining the modification effects by age, sex, smoking status, season, and type of stroke were also analyzed.

RESULTS

A total of 409 stroke events (381 ischemic and 28 hemorrhagic) were registered between 2006 and 2007. The odds ratios (ORs) for wind speed, DWR, and wind chill among the total sample at lag 0-8 were 1.18 (95% confidence interval (CI): 1.06-1.31), 1.08 (95% CI: 1.02-1.14), and 1.22 (95% CI: 1.07-1.39) respectively. The ORs for wind speed, DWR, and wind chill for ischemic stroke patients were slightly greater than for patients in the total sample (OR=1.20, 95% CI: 1.08-1.34; OR=1.09, 95% CI: 1.03-1.15; and OR=1.22, 95% CI: 1.07-1.39, respectively). Statistically significant season-specific effects were found for spring and winter, and various delayed effects were observed. In addition, age, sex, and smoking status modified the effect size of wind speed, DWR, and wind chill.

CONCLUSIONS

Our analyses showed that the risk of stroke symptoms onset was associated with wind speed, DWR, and wind chill on Jeju Island.

Estimation of daily PM2.5 concentration and its relationship with meteorological conditions in Beijing

When investigating the impact of air pollution on health, particulate matter less than 2.5 μm in aerodynamic diameter (PM_2.5) is considered more harmful than particulates of other sizes. Therefore, studies of PM_2.5 have attracted more attention. Beijing, the capital of China, is notorious for its serious air pollution problem, an issue which has been of great concern to the residents, government, and related institutes for decades. However, in China, significantly less time has been devoted to observing PM_2.5 than for PM₁₀. Especially before 2013, the density of the PM_2.5 ground observation network was relatively low, and the distribution of observation stations was uneven. One solution is to estimate PM_2.5 concentrations from the existing data on PM₁₀. In the present study, by analyzing the relationship between the concentrations of PM_2.5 and PM₁₀, and the meteorological conditions for each season in Beijing from 2008 to 2014, a U-shaped relationship was found between the daily maximum wind speed and the daily PM concentration, including both PM_2.5 and PM₁₀. That is, the relationship between wind speed and PM concentration is not a simple positive or negative correlation in these wind directions; their relationship has a complex effect, with higher PM at low and high wind than for moderate winds. Additionally, in contrast to previous studies, we found that the PM_2.5/PM₁₀ ratio is proportional to the mean relative humidity (MRH). According to this relationship, for each season we established a multiple nonlinear regression (MNLR) model to estimate the PM_2.5 concentrations of the missing periods.

Evaluating the efficiency of an asbestos stabilizer on ceiling tiles and the characteristics of the released asbestos fibers

The efficiency of asbestos stabilizers and their adaptability were evaluated by investigating the characteristics of asbestos fibers released from ceiling tiles. The impact of such variables as the wind speed or vibration conditions was also studied along with the asbestos stabilizers. The concentrations of the asbestos fibers released from damaged ceiling tiles treated with stabilizers decreased by 69.5-84.4% compared with those of untreated tiles for all variables, with a statistically significant difference (p<0.001). The effects of the environmental factors on the asbestos concentrations were analyzed through a multiple regression analysis. It was determined that the surface status of the ceiling tiles and stabilizers were the main factors affecting the concentration, and the reliability of these factors was estimated as 58.3%. The lengths of the chrysotile fibers released from the damaged ceiling tiles were in the range of 0.991-79.1 μm for the untreated tiles and 3.74-35.6 μm for the tiles treated with inorganic stabilizers. It was confirmed that inorganic stabilizers are more efficient for damaged ceiling tiles. The results of this study also show that the asbestos concentrations are greatly reduced after treating damaged ceiling tiles with a stabilizer.

Do Weather Phenomena Have Any Influence on the Occurrence of Spontaneous Pneumothorax?

INTRODUCTION

The objective of this study was to assess the impact of weather phenomena on the occurrence of spontaneous pneumothorax (SP) in the Plzeň region (Czech Republic).

METHODS

A retrospective analysis of 450 cases of SP in 394 patients between 1991 and 2013. We observed changes in average daily values of atmospheric pressure, air temperature and daily maximum wind gust for each day of that period and their effect on the development of SP.

RESULTS

The risk of developing SP is 1.41 times higher (P=.0017) with air pressure changes of more than±6.1hPa. When the absolute value of the air temperature changes by more than±0.9°C, the risk of developing SP is 1.55 times higher (P=.0002). When the wind speed difference over the 5 days prior to onset of SP is less than 13m/sec, then the risk of SP is 2.16 times higher (P=.0004). If the pressure difference is greater than±6.1hPa and the temperature difference is greater than±0.9°C or the wind speed difference during the 5 days prior to onset of SP is less than 10.7m/s, the risk of SP is 2.04 times higher (P≤.0001).

CONCLUSION

Changes in atmospheric pressure, air temperature and wind speed are undoubtedly involved in the development of SP, but don't seem to be the only factors causing rupture of blebs or emphysematous bullae.

Physical controls of hypoxia in waters adjacent to the Yangtze Estuary: A numerical modeling study

A three-dimensional circulation model (the Environmental Fluid Dynamic Code) was used to examine the role that physical forcing (river discharge, wind speed and direction) plays in controlling hypoxia in waters adjacent to the Yangtze Estuary. The model assumes that the biological consumption of oxygen is constant in both time and space, which allows the role of physical forcing in modulating the oxygen dynamics to be isolated. Despite of the simplicity of this model, the simulation results showed that it can reproduce the observed variability of dissolved oxygen in waters adjacent to the Yangtze Estuary, thereby highlighting the important role of changes in physical forcing in the variation of hypoxia. The scenarios tested revealed appreciable changes in the areal extent of hypoxia as a function of wind speed and wind direction. Interestingly, well-developed hypoxia was insensitive to river discharge.

On multivariate imputation and forecasting of decadal wind speed missing data

This paper demonstrates the application of multiple imputations by chained equations and time series forecasting of wind speed data. The study was motivated by the high prevalence of missing wind speed historic data. Findings based on the fully conditional specification under multiple imputations by chained equations, provided reliable wind speed missing data imputations. Further, the forecasting model shows, the smoothing parameter, alpha (0.014) close to zero, confirming that recent past observations are more suitable for use to forecast wind speeds. The maximum decadal wind speed for Entebbe International Airport was estimated to be 17.6 metres per second at a 0.05 level of significance with a bound on the error of estimation of 10.8 metres per second. The large bound on the error of estimations confirms the dynamic tendencies of wind speed at the airport under study.

Can meteorological factors forecast asthma exacerbation in a paediatric population?

BACKGROUND

Asthma exacerbations attended in emergency departments show a marked seasonality in the paediatric age. This seasonal pattern can change from one population to another and the factors involved are poorly understood.

OBJECTIVES

To evaluate the association between meteorological factors and schooling with asthma exacerbations in children attended in the paediatric emergency department of a district hospital.

METHODS

We conducted a retrospective review of the medical records of children 5-14 years of age attended for asthma exacerbations during a 4-year period (2007-2011). Climatic data were obtained from a weather station located very close to the population studied. The number of asthma exacerbations was correlated to temperature, barometric pressure, relative humidity, rainfall, wind speed, wind distance, solar radiation, water vapour pressure and schooling, using regression analyses.

RESULTS

During the study period, 371 children were attended for asthma exacerbations; median age was eight years (IQR: 6-11), and 59% were males. Asthma exacerbations showed a bimodal pattern with peaks in spring and summer. Maximum annual peak occurred in week 39, within 15 days from school beginning after the summer holidays. A regression model with mean temperature, water vapour pressure, relative humidity, maximum wind speed and schooling could explain 98.4% (p<0.001) of monthly asthma exacerbations.

CONCLUSIONS

The combination of meteorological factors and schooling could predict asthma exacerbations in children attended in a paediatric emergency department.

Effect of wind speed and relative humidity on atmospheric dust concentrations in semi-arid climates

Atmospheric particulate have deleterious impacts on human health. Predicting dust and aerosol emission and transport would be helpful to reduce harmful impacts but, despite numerous studies, prediction of dust events and contaminant transport in dust remains challenging. In this work, we show that relative humidity and wind speed are both determinants in atmospheric dust concentration. Observations of atmospheric dust concentrations in Green Valley, AZ, USA, and Juárez, Chihuahua, México, show that PM10 concentrations are not directly correlated with wind speed or relative humidity separately. However, selecting the data for high wind speeds (>4m/s at 10 m elevation), a definite trend is observed between dust concentration and relative humidity: dust concentration increases with relative humidity, reaching a maximum around 25% and it subsequently decreases with relative humidity. Models for dust storm forecasting may be improved by utilizing atmospheric humidity and wind speed as main drivers for dust generation and transport.