The distribution of organochlorine pesticides (OCPs) in surface sediments of Bohai Sea Bay,China

The residues of organochlorine pesticides (OCPs) in 19 surface sediments of Bohai Sea Bay were determined in this study. Total OCP concentration in surface sediment ranged from 9.01 to 18.04 ng/g dry weight, with a mean concentration of 12.50 ng/g. These findings are in the mid-range of pesticide concentrations compared to those reported in other regions worldwide. DDTs and HCHs were the predominant species. The α-HCH/β-HCH ratios and the predominant γ-HCH indicate that the technical HCH contamination was due mainly to historical usage, although there appeared to be a fresh input of lindane. The results from \(\left( {\mbox{DDD}\,\mbox{+}\,\mbox{DDE}} \right)\mbox{/}\sum {\mbox{DDTs}} \) and DDD/DDE calculations suggest that the usage of DDT in agricultural activities was not terminated, and the historical/fresh inputs of DDT in these areas could be more easily degraded into DDD under an anoxic condition. PCA implies that the recent usage of DDT could serve as important fresh input sources for OCPs.     

Seasonal variations and source profile of <Emphasis Type="Italic">n</Emphasis>-alkanes in particulate matter (PM<Subscript>10</Subscript>) at a heavy traffic site,Delhi

Delhi is one of the most polluted cities in the world. The generation of aerosols in the lower atmosphere of the city is mainly due to a large amount of natural dust advection and sizable anthropogenic activities. The compositions of organic compounds in aerosols are highly variable in this region and need to be investigated thoroughly. Twenty-four-hour sampling to assess concentrations of n-alkanes (ng/m³) in PM₁₀ was carried out during January 2015 to June 2015 at Indira Gandhi Delhi Technical University for Women (IGDTUW) Campus, Delhi, India. The total average concentration of n-alkanes, 243.7 ± 5.5 ng/m³, along with the diagnostic tools has been calculated. The values of CPI₁, CPI₂, and CPI₃ for the whole range of n-alkanes series, petrogenic n-alkanes, and biogenic n-alkanes were 1.00, 1.02, and 1.04, respectively, and C _max were at C₂₅ and C₂₇. Diagnostic indices and curves indicated that the dominant inputs of n-alkanes are from petrogenic emissions, with lower contribution from biogenic emissions. Significant seasonal variations were observed in average concentrations of n-alkanes, which is comparatively higher in winter (187.4 ± 4.3 ng/m³) than during the summer season (56.3 ± 1.1 ng/m³).     

Pollution characteristics and ecological risk assessment of heavy metals in three land-use types on the southern Loess Plateau,China

The accumulation of heavy metals in agricultural soils has been the subject of great concern because these metals have the potential to be transferred to soil solutions and subsequently accumulate in the food chain. To study the persistence of trace metals in crop and orchard soils, representative surface soil samples were collected from terrace farmland that had been cultivated for various numbers of years (3, 8, 12, 15, and >20 years), terrace orchard land that had been cultivated for various numbers of years (4, 7, 10, 12, 15, 18, 25, and >30 years), and slope farmland with various gradients (3°, 5°, 8°, 12°, 15°, and 25°) and analyzed for heavy metals (As, Cr, Cu, Hg, Ni, and Zn). These samples were collected from Nihegou catchment of Chunhua county in the southern Loess Plateau of China. The six heavy metals demonstrated different trends with time or gradient in the three land-use types. The Cu and Zn contents of the soil were higher than the referee background values of the loessal soil, and the contents of Cr and Ni, and especially those of As and Hg, were lower. Cu was the only heavy metal that just met the Grade III Environmental Quality Standard for Soils of China, while the others reached grade I. Cu and Hg were considered contaminant factors and Hg was a moderate potential ecological risk factor in the catchment. Of the sites investigated, 89.5% fell into the category with a low degree of contamination (C _d ) and rest were moderate, while all three land-use types had low potential ecological risk (RI). Changes of C _d and RI were consistent with the cultivated time in the terrace farmland and terrace orchard land. Values of RI increased while C _d decreased with the increasing of slope gradient in the slope farmland. Evaluating the ecological risk posed by heavy metals using more soil samples in a larger study area is necessary on the Loess Plateau of China.     

Estimation of underwater visibility in coastal and inland waters using remote sensing data

An optical method is developed to estimate water transparency (or underwater visibility) in terms of Secchi depth (Z _sd ), which follows the remote sensing and contrast transmittance theory. The major factors governing the variation in Z _sd , namely, turbidity and length attenuation coefficient (1/(c + K _d ), c = beam attenuation coefficient; K _d  = diffuse attenuation coefficient at 531 nm), are obtained based on band rationing techniques. It was found that the band ratio of remote sensing reflectance (expressed as (R _rs (443) + R _rs (490))/(R _rs (555) + R _rs (670)) contains essential information about the water column optical properties and thereby positively correlates to turbidity. The beam attenuation coefficient (c) at 531 nm is obtained by a linear relationship with turbidity. To derive the vertical diffuse attenuation coefficient (K _d ) at 531 nm, K _d (490) is estimated as a function of reflectance ratio (R _rs (670)/R _rs (490)), which provides the bio-optical link between chlorophyll concentration and K _d (531). The present algorithm was applied to MODIS-Aqua images, and the results were evaluated by matchup comparisons between the remotely estimated Z _sd and in situ Z _sd in coastal waters off Point Calimere and its adjoining regions on the southeast coast of India. The results showed the pattern of increasing Z _sd from shallow turbid waters to deep clear waters. The statistical evaluation of the results showed that the percent mean relative error between the MODIS-Aqua-derived Z _sd and in situ Z _sd values was within ±25%. A close agreement achieved in spatial contours of MODIS-Aqua-derived Z _sd and in situ Z _sd for the month of January 2014 and August 2013 promises the model capability to yield accurate estimates of Z _sd in coastal, estuarine, and inland waters. The spatial contours have been included to provide the best data visualization of the measured, modeled (in situ), and satellite-derived Z _sd products. The modeled and satellite-derived Z _sd values were compared with measurement data which yielded RMSE = 0.079, MRE = ?0.016, and R ²  = 0.95 for the modeled Z _sd and RMSE = 0.075, MRE = 0.020, and R ²  = 0.95 for the satellite-derived Z _sd products.     

Effects of land conversion from native shrub to pistachio orchard on soil erodibility in an arid region

Land-use change through degrading natural vegetation for agricultural production adversely affects many of soil properties particularly organic carbon content of soils. The native shrub land and grassland of Gaziantep-Adiyaman plateau that is an important pistachio growing eco-region have been cleared to convert into pistachio orchard for the last 50 to 60 years. In this study, the effects of conversion of natural vegetation into agricultural uses on soil erodibility have been investigated. Soil samples were collected from surface of agricultural fields and adjacent natural vegetation areas, and samples were analyzed for some soil erodibility indices such as dispersion ratio (DR), erosion ratio (ER), structural stability index (SSI), Henin’s instability index (I _s ), and aggregate size distribution after wet sieving (AggSD). According to the statistical evaluation, these two areas were found as different from each other in terms of erosion indices except for I _s index (P < 0.001 for DR and ER or P < 0.01 for SSI). In addition, native shrub land and converted land to agriculture were found different in terms of AggSD in all aggregate size groups. As a contrary to expectations, correlation tests showed that there were no any interaction between soil organic carbon and measured erodibility indices in two areas. In addition, significant relationships were determined between measured variables and soil textural fractions as statistical. These obtaining findings were attributed to changing of textural component distribution and initial aggregate size distribution results from land-use change in the study area. Study results were explained about hierarchical aggregate formation mechanism.     

Dissipation pattern and risk quotients assessment of amisulbrom in Korean melon cultivated in plastic house conditions

Amisulbrom formulated as suspension concentrate was applied at the rate recommended for Korean melon to determine the dissipation pattern (at two different sites), the pre-harvest residue limit (PHRL), and risk assessments. Samples collected over 10 days were extracted using liquid-liquid extraction (LLE) and cleaned up with solid-phase extraction (SPE) Florisil cartridge. Residual concentrations were determined using liquid chromatography-ultraviolet detector (LC-UVD) and confirmed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The standard showed good instrument response linearity with a correlation coefficient (R ²) = 0.9999, and the recovery ranged from 87.5 to 93.7%. The dissipation half-life calculated from two different sites were found to be 7.0 and 8.8 days for sites 1 and 2, respectively. A PHRL graph constructed from the data indicated that if the residue levels were less than 0.55–0.59 mg/kg 3 days before harvest or less than 0.61–0.74 mg/kg 7 days before harvest, then they would be lower than the maximum residue limits (MRLs) at harvest. Risk assessments showed that the risk quotient (RQ) was 4.39–3.47% at 0 day, declined to 1.53–1.63% at 10 days. Therefore, the current data indicate that the amisulbrom can be applied safely to Korean melon; hence, it is unlikely to induce adverse health effects in consumers.     

Carbon and nitrogen mineralization in Vertisol as mediated by type and placement method of residue

Selection of appropriate residue application method is essential for better use of biomass for soil and environmental health improvement. A laboratory incubation experiment was conducted for 75 days to investigate C and N mineralization of residues of soybean (Glycine max L.), chickpea (Cicer arietinum L.), maize (Zea mays L.), and wheat (Triticum aestivum L.) placed on the soil surface and incorporated into the soil. The residue of soybean and chickpea had a greater decomposition rate than that of maize and wheat, despite of their placements. Higher rate of decomposition of the residue of soybean and chickpea was recorded when it was kept on the soil surface while soil incorporation of residue of wheat and maize resulted in faster decomposition. Therefore, these findings could be used as guidelines for management of crop residue application in farmland to improve soil and environmental quality.     

Stochastic modeling approaches based on neural network and linear–nonlinear regression techniques for the determination of single droplet collection efficiency of countercurrent spray towers

This paper presents a new mathematical model and a two-layer neural network approach to predict the single droplet collection efficiency (SDCE), η _d, of countercurrent spray towers. SDCE values were calculated using MATLAB^® algorithm for 205 different artificial scenarios given in a large range of operating conditions. Theoretical results were compared with outputs obtained from a two-layer neural network and DataFit^® scientific software. The predicted model developed from linear–nonlinear regression analysis and network outputs agreed with the theoretical data, and all predictions proved to be satisfactory with a correlation coefficient of about 0.921 and 0.99, respectively. By using the proposed model, iterations between Reynolds number (Re), drag coefficient (C _D) and terminal velocity values (v _T) were neglected for a large range of operating conditions. SDCE values were also obtained speedily and practically for five main operating inputs used in the model.     

Assessment of heavy metal pollution in vegetables and relationships with soil heavy metal distribution in Zhejiang province,China

There are increasing concerns on heavy metal contaminant in soils and vegetables. In this study, we investigated heavy metal pollution in vegetables and the corresponding soils in the main vegetable production regions of Zhejiang province, China. A total of 97 vegetable samples and 202 agricultural soil samples were analyzed for the concentrations of Cd, Pb, As, Hg, and Cr. The average levels of Cd, Pb, and Cr in vegetable samples [Chinese cabbage (Brassica campestris spp. Pekinensis), pakchoi (Brassica chinensis L.), celery (Apium graveolens), tomato (Lycopersicon esculentum), cucumber (Colletotrichum lagenarium), cowpea (Vigna unguiculata), pumpkin (Cucurbita pepo L.), and eggplant (Solanum melongena)] were 0.020, 0.048, and 0.043 mg kg^?1, respectively. The Pb and Cr concentrations in all vegetable samples were below the threshold levels of the Food Quality Standard (0.3 and 0.5 mg kg^?1, respectively), except that two eggplant samples exceeded the threshold levels for Cd concentrations (0.05 mg kg^?1). As and Hg contents in vegetables were below the detection level (0.005 and 0.002 mg kg^?1, respectively). Soil pollution conditions were assessed in accordance with the Chinese Soil Quality Criterion (GB15618-1995, Grade II); 50 and 68 soil samples from the investigated area exceeded the maximum allowable contents for Cd and Hg, respectively. Simple correlation analysis revealed that there were significantly positive correlations between the metal concentrations in vegetables and the corresponding soils, especially for the leafy and stem vegetables such as pakchoi, cabbage, and celery. Bio-concentration factor values for Cd are higher than those for Pb and Cr, which indicates that Cd is more readily absorbed by vegetables than Pb and Cr. Therefore, more attention should be paid to the possible pollution of heavy metals in vegetables, especially Cd.     

Optimizing the flow adjustment of constituent concentrations via LOESS for trend analysis

Trend analysis of stream constituent concentrations requires adjustment for exogenous variables like discharge because concentrations often have variable relations with flow. To remove the influence of flow on stream water quality data, an accurate characterization of the relationship between the constituent and streamflow is needed. One popular method, locally weighted regression (LOESS), provides an effective means for flow-adjusting concentrations. The LOESS fit can be tailored to the data via the smoothing parameter (f), so that the user can avoid overfitting or oversmoothing the data. However, it is a common practice to use a single f value when flow-adjusting water quality data for trend analysis. This study provides a robust, automated method for determining the optimal f value (f_opt) for each dataset via an iterative K-fold cross-validation procedure that minimizes prediction error in LOESS. The method is developed by analyzing datasets of seven different constituents across 17 sites (119 datasets total) from a stream monitoring program in northwest Arkansas (USA). We recommend using 10 iterations of 10-fold cross-validation (10?×?10 CV) in order to select f_opt when flow-adjusting water quality data with LOESS. The use of a default f value did not produce different trend interpretations for the data used here; however, the proposed approach may be helpful in other water quality studies which employ similar statistical fitting methods. Additionally, we provide an implementation of the method in the R statistical computing environment.     

Trace elements in muscle of three fish species from Todos os Santos Bay,Bahia State,Brazil

In this study, an analysis was performed on the concentrations of the trace elements Al, As, Ba, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, V, and Zn in muscle of two carnivorous and one planktivorous fish species collected at Todos os Santos Bay (BTS). The accumulation order of the trace elements in Lutjanus analis was Al >Zn >Fe >Cr >Ba >Ni. In Cetengraulis edentulus, the order was Al >Fe >Zn >Cr >Ni >Mn >As. In the species Diapterus rhombeus, the order was Al >Fe >Zn >Cr >Ni >Mn >Cd. To determine the risk related to the consumption of fish, toxicity guidelines were used as standard references. It was observed that the species C. edentulus contained concentrations of As exceeding WHO limits, but these concentrations were acceptable according to the Agência Nacional de Vigilância Sanitária (ANVISA) guidelines. Cd levels were found only in D. rhombeus and in low concentrations according to the determinations of WHO and ANVISA. Pb levels were not detected in any of the three fish species. The analyzed elements did not differ statistically according to the species and feeding habits. The results point to possible risks of human contamination by As related to the consumption of the fish species C. edentulus from the BTS.     

Discriminant analysis for the prediction of sand mass distribution in an urban stormwater holding pond using simulated depth average flow velocity data

The approach of this paper is to predict the sand mass distribution in an urban stormwater holding pond at the Stormwater Management And Road Tunnel (SMART) Control Centre, Malaysia, using simulated depth average floodwater velocity diverted into the holding during storm events. Discriminant analysis (DA) was applied to derive the classification function to spatially distinguish areas of relatively high and low sand mass compositions based on the simulated water velocity variations at corresponding locations of gravimetrically measured sand mass composition of surface sediment samples. Three inflow parameter values, 16, 40 and 80 m³ s^?1, representing diverted floodwater discharge for three storm event conditions were fixed as input parameters of the hydrodynamic model. The sand (grain size?>?0.063 mm) mass composition of the surface sediment measured at 29 sampling locations ranges from 3.7 to 45.5 %. The sampling locations of the surface sediment were spatially clustered into two groups based on the sand mass composition. The sand mass composition of group 1 is relatively lower (3.69 to 12.20 %) compared to group 2 (16.90 to 45.55 %). Two Fisher’s linear discriminant functions, F ₁ and F ₂, were generated to predict areas; both consist of relatively higher and lower sand mass compositions based on the relationship between the simulated flow velocity and the measured surface sand composition at corresponding sampling locations. F ₁?=??9.405?+?4232.119?×?A???1795.805?×?B?+?281.224?×?C, and F ₂?=??2.842?+?2725.137?×?A???1307.688?×?B?+?231.353?×?C. A, B and C represent the simulated flow velocity generated by inflow parameter values of 16, 40 and 80 m³ s^?1, respectively. The model correctly predicts 88.9 and 100.0 % of sampling locations consisting of relatively high and low sand mass percentages, respectively, with the cross-validated classification showing that, overall, 82.8 % are correctly classified. The model predicts that 31.4 % of the model domain areas consist of high-sand mass composition areas and the remaining 68.6 % comprise low-sand mass composition areas.     

Dynamic Modeling of Biological Treatment of Leachates from Solid Wastes

Leachates from municipal solid wastes are liquids formed by organic and inorganic components suitable for biological treatment. In biological treatment plants, prediction of the output parameter value due to dynamic variation is essential. A dynamic model based on ASM1 has been applied for prediction of effluent COD value at real scale, using three different composition leachates. Tuning between dynamic variables and predicted parameter is tested for a correct proposal of the model. Dynamic model predicts correctly fluctuations in the output COD value and tempers dynamism caused by variation of temperature and biomass concentration in the case of high organic loaded leachates. Kinetic parameters Y _H and K _s are fixed to solve the model, and dynamic variables μ _H and X_BH are changing in time. μ_H,max is obtained in simulation (0.37–1.82 day^?1) for minimum error between predicted values and experimental data. μ_H,max value is much lower compared with the value for domestic wastewater treatment due to lower biodegradability of leachate.     

Investigation of polar organic chemical integrative sampler (POCIS) flow rate dependence for munition constituents in underwater environments

Munition constituents (MC) are present in aquatic environments throughout the world. Potential for fluctuating release with low residence times may cause concentrations of MC to vary widely over time at contaminated sites. Recently, polar organic chemical integrative samplers (POCIS) have been demonstrated to be valuable tools for the environmental exposure assessment of MC in water. Flow rate is known to influence sampling by POCIS. Because POCIS sampling rates (R_s) for MC have only been determined under quasi-static conditions, the present study evaluated the uptake of 2,4,6-trinitrotoluene (TNT), RDX (hexahydro-1,3,5-trinitro-1,3,5-triazine), and 2,4- and 2,6-dinitrotoluenes (DNT), by POCIS in a controlled water flume at 7, 15, and 30 cm/s in 10-day experiments using samplers both within and without a protective cage. Sampling rate increased with flow rate for all MC investigated, but flow rate had the strongest impact on TNT and the weakest impact on RDX. For uncaged POCIS, mean R_s for 30 cm/s was significantly higher than that for 7 cm by 2.7, 1.9, 1.9, and 1.3 folds for TNT, 2,4-DNT, 2,6-DNT, and RDX, respectively. For all MC except RDX, mean R_s for caged POCIS at 7 cm/s were significantly lower than for uncaged samplers and similar to those measured at quasi-static condition, but except for 2,6-DNT, no caging effect was measured at the highest flow rate, indicating that the impact of caging on R_s is flow rate-dependent. When flow rates are known, flow rate-specific R_s should be used for generating POCIS-derived time-averaged concentrations of MC at contaminated sites.     

Epilithic diatom assemblages and their relationships with environmental variables in the Nilüfer Stream Basin,Bursa, Turkey

Patterns of epilithic diatom species distribution in relation to environmental variables from 12 sampling sites on the main stream and some of its tributaries in the Nilüfer Stream Basin were determined using multivariate statistical techniques. The stream basin has been heavily influenced by anthropogenic effects. The upper part of the basin that is distant from pollution sources mostly has a spring water quality, while the lower part where the stream flows through the urban area and receives domestic and industrial wastewater has a quite low quality. Ordination techniques using both diatom taxa and 21 environmental variables revealed non- to slightly polluted upper basin sites and highly polluted lower basin sites along the stream. The results showed that the stream catchment is polluted gradually from upstream to downstream and that most of the downstream sites have very low water quality especially in summer months. A total of 134 epilithic diatom taxa belonging to 50 genera were recorded for 12 sample sites. Partial CCA results indicated that water temperature (T), discharge (Q), and total phosphorus (TP) were the most important variables affecting the distribution of diatom species. Unpolluted or slightly polluted upper basin sites were dominated by Achnanthidium minutissimum, Cocconeis placentula var. euglypta, Gomphonema olivaceum, and Navicula tripunctata. Highly polluted lower basin sites were characterized by high levels of organic and inorganic matters and low dissolved oxygen (DO) values. Species widespread in the highly polluted lower basin sites such as Nitzschia umbonata, Nitzschia amphibia, Nitzschia capitellata, Nitzschia palea, Nitzschia paleacea, Luticola mutica, and Stephanodiscus niagarae were mostly related to pollution indicator variables such as ammonium nitrogen (NH₄ ⁺–N), sodium (Na⁺), total phosphorus (TP), and total organic matter (TOM).     

Assessment of pesticide residues in vegetables from the Western Usambara and Uruguru Mountains in Tanzania

Assessment of levels of pesticide residues in vegetables was carried out in some villages in the Western Usambara and Uluguru Mountains of Tanzania where varieties of vegetables are grown. Tomatoes and cabbages were the most popular enterprise grown all year round and therefore were selected as the model crops for this study. Analysis of the cleaned sample extracts on a gas chromatography with electron capture detector (GC-ECD) and confirmation on the Gas chromatography–mass spectrometry (GC-MS) revealed dominance of organochlorine pesticides. Organophosphorous pesticides (parathion and marathion) were only detected in some samples, however, in most cases with higher concentrations compared to organochlorine pesticides. Levels of pesticide residues detected in vegetables were up to: parathion 5.07 μg/Kg, marathion 3.73 μg/Kg, α-endosulfan 0.32 μg/Kg, β-endosulfan 0.53 μg/Kg, dieldrin 1.36 μg/Kg, γ-HCH 0.25 μg/Kg, α-HCH 0.09 μg/Kg, and p, p′-DDT 0.64 μg/Kg. These results clearly show that vegetables are contaminated with different pesticide residues. However, the total levels of pesticide residues in both tomatoes and cabbages are lower than their respective codex alimentarius maximum residue levels (MRLs). This means that the vegetables produced in the area are suitable for human consumption.     

Physicochemical properties associated with the presence of <Emphasis Type="Italic">Burkholderia pseudomallei</Emphasis> in small ruminant farm water supplies in Peninsular Malaysia

Burkholderia pseudomallei causes melioidosis, a life-threatening infection in both humans and animals. Water is an important reservoir of the bacteria and may serve as a source of environmental contamination leading to infection. B. pseudomallei has an unusual ability to survive in water for a long period. This paper investigates physicochemical properties of water associated with the presence of B. pseudomallei in water supply in small ruminant farms in Peninsular Malaysia. Physicochemical properties of water samples taken from small ruminant farms that included temperature, pH, dissolved oxygen (DO₂), optical density (OD), and chemical oxygen demand (COD) were measured after which the samples were cultured for B. pseudomallei. Multivariable logistic regression model revealed that slightly acidic water pH and higher COD level were significantly associated with the likelihood of the B. pseudomallei presence in the water.     

A synoptic survey of select wastewater-tracer compounds and the pesticide imidacloprid in Florida’s ambient freshwaters

Current wastewater treatment technologies do not remove many unregulated hydrophilic compounds, and there is growing interest that low levels of these compounds, referred to as emerging contaminants, may impact human health and the environment. A probabilistic-designed monitoring network was employed to infer the extent of Florida’s ambient freshwaters containing the wastewater (Includes reuse water, septic systems leachate, and wastewater treatment effluent.) indicators sucralose, acetaminophen, carbamazepine, and primidone and those containing the widely used pesticide imidacloprid. Extent estimates with 95% confidence bounds are provided for canals, rivers, streams, small and large lakes, and unconfined aquifers containing ultra-trace concentrations of these compounds as based on analyses of 2015 sample surveys utilizing 528 sites. Sucralose is estimated to occur in greater than 50% of the canal, river, stream, and large lake resource extents. The pharmaceuticals acetaminophen, carbamazepine, and primidone are most prevalent in rivers, with approximately 30% of river kilometers estimated to contain at least one of these compounds. Imidacloprid is estimated to occur in 50% or greater of the canal and river resource extents, and it is the only compound found to exceed published toxicity or environmental effects standards. Geospatial analyses show sucralose detection frequencies within Florida’s drainage basins to be significantly related to the percentage of urban land use (R²?=?0.36, p?<?0.001), and imidacloprid detection frequencies to be significantly related to the percentage of urban and agricultural land use (R²?=?0.47, p?<?0.001). The extent of the presence of these compounds highlights the need for additional emerging contaminant studies especially those examining effects on aquatic biota.     

Characterisation of the airborne pollen spectrum in Guadalajara (central Spain) and estimation of the potential allergy risk

Aerobiological research into airborne pollen diversity and seasonal variations in pollen counts has become increasingly important over recent decades due to the growing incidence of asthma, rhinitis and other pollen-related allergic conditions. Airborne pollen in Guadalajara (Castilla-La Mancha, Spain) was studied over a 6-year period (2008–2013) using a Hirst-type volumetric spore trap. The highest pollen concentrations were recorded from February to June, coinciding with the pollen season of the pollen types that most contribute to the local airborne pollen spectrum: Cupressaceae (32.2 %), Quercus (15.1 %), Platanus (13.2 %), Olea (8.3 %), Populus (7.8 %) and Poaceae (7.2 %). These are therefore critical months for allergy sufferers. The pollen calendar was typically Mediterranean and comprised 25 pollen types. Between January and March, Cupressaceae pollen concentrations exceeded allergy risk thresholds on 38 days. Other woody species such as Olea and Platanus have a shorter pollen season, and airborne concentrations exceeded allergy risk thresholds on around 13 days in each case. Poaceae pollen concentrations attained allergy risk levels on 26 days between May and July. Other highly allergenic pollen types included Urticaceae and Chenopodiaceae-Amaranthaceae, though these are less abundant than other pollen types in Guadalajara and did not exceed risk thresholds on more than 3 and 5 days, respectively.     

Assessing spatio-temporal trend of vector breeding and dengue fever incidence in association with meteorological conditions

Th aim of this study is to investigate spatio-temporal trends of dengue vector breeding and epidemic (disease incidence) influenced by climatic factors. The spatio-temporal (low-, medium-, and high-intensity periods) evaluation of entomological and epidemiological investigations along with climatic factors like rainfall (RF), temperature (T_max), relative humidity (RH), and larval indexing was conducted to develop correlations in the area of Lahore, Pakistan. The vector abundance and disease transmission trend was geo-tagged for spatial insight. The sufficient rainfall events and optimum temperature and relative humidity supported dengue vector breeding with high larval indices for water-related containers (27–37%). Among temporal analysis, the high-intensity period exponentially projected disease incidence followed by post-rainfall impacts. The high larval incidence that was observed in early high-intensity periods effected the dengue incidence. The disease incidence had a strong association with RF (r = 0.940, α = 0.01). The vector larva occurrence (r = 0.017, α = 0.05) influenced the disease incidence. Similarly, RH (r = 0.674, α = 0.05) and average T_max (r = 0.307, α = 0.05) also induced impact on the disease incidence. In this study, the vulnerability to dengue fever highly correlates with meteorological factors during high-intensity period. It provides area-specific understanding of vector behavior, key containers, and seasonal patterns of dengue vector breeding and disease transmission which is essential for preparing an effective prevention plan against the vector.