Sorption coefficients were evaluated for pyroxasulfone, s-metolachlor, and dimethenamid-p across 25 soil types with different chemical and physical properties to better understand how soil properties influence the binding of pyroxasulfone in different soils. Sorption coefficients were determined using a batch equilibrium method to evaluate relative differences in binding among the three herbicides. Based on water solubility values, we would have expected the relative order of binding to be dimethenamid-p (1450 mg L⁻¹ at 20°C), s-metolachlor (530 mg L⁻¹ at 20°C), and pyroxasulfone (3.49 mg L⁻¹ at 20°C) in order of increasing binding. However, when sorption coefficients were calculated, we observed the order of pyroxasulfone = dimethenamid-p < s-metolachlor in the order of increasing binding. The average K_d(sorption coefficient) values were 1.7, 2.3, and 4.0 L kg⁻¹ for pyroxasulfone, dimethenamid-p, and s-metolachlor, respectively. Although dimethenamid-p has water solubility values that are over 400 times greater than pyroxasulfone, there was no statistical difference in binding between pyroxasulfone and dimethenamid-p. s-Metolachlor binding was statistically greater than both pyroxasulfone and dimethenamid-p. Across all soil chemical and physical properties, sorption coefficients for all three herbicides were highly and statistically correlated to soil organic matter. Sand and silt were also statistically correlated to binding, although these correlations could be explained by the high correlation of organic matter to these properties. Evaluation of sorption coefficients indicates that pyroxasulfone is most prevalent in the soil solution where herbicides are available for plant uptake. Reduced soil binding and greater activity at the target site could contribute to comparable weed control efficacies of pyroxasulfone even when applied at lower use rates compared to either s-metolachlor or dimethenamid-p.

This work studied the effects, under greenhouse conditions, of six heavy metals (Cd, Co, Cr, Cu, Ni, and Pb) on three leguminous crops representing food, feed, and forage crops commonly grown in Egypt. Metal concentrations ranged from 0 to as high as 4.8 mmol kg⁻¹ soil. Results showed that all three plant parameters measured (dry matter yield, nodulation, and N uptake) decreased significantly with increasing heavy-metal concentrations. Plots of the natural log of each parameter against metal concentration were linear within the ranges studies. From the slopes of these regression lines, the concentration of each heavy metal required to achieve 50% reduction (R₅₀) of each parameter was calculated. In general, the lowest metal concentrations for R₅₀ were for Cd²⁺ and Pb²⁺ and the highest were for Cr³⁺ and Cu²⁺. Heavy-metal additions to soils should be closely monitored because they can negatively affect nodulation and N nutrition of leguminous crops.

This article is discussing the impacts of land cover change from paddy field to barren land in small scale area (1,516.5 km²), on the surrounding local climate components in central Java, Indonesia. Data of several climate components from 2000-2010 were collected from weather stations that located separately. The land covers were dominated with cropland and little forest on eastern site, and settlements (urban) on western site. This study confirmed that the decrease in 13.1% of paddy field and the increase in 12.4% of barren land had significantly resulted in low daily actual vapor pressure (ea) during dry months with low rainfalls. The eastern areas that were originally occupied by croplands and trees, responded to the decrease of paddy fields by the increasing of air temperatures. The air temperatures and their variations at urban areas located in the western part were not distinctly affected by the land cover change.

This research combines a hydrological and pedological approach to better understand the spatial distribution of contaminated soils along the Massawippi River (southern Québec, Canada). This river crosses through former mines, which were some of the largest copper mining areas in North America from 1865 to 1939. To determine the spatial distribution and concentration of the metal elements, soil samples were taken in each flood recurrence zone appearing on official flood zone maps. The maximum values obtained for Cu and Pb are 380 and 200 mg kg⁻¹, respectively, for the soils in the frequent flood zones (FFzs), while the values for soils in the moderate flood zones (MFzs) range from 700 to 540 (Cu) and 580 to 460 mg kg⁻¹ (Pb). Contamination extends through several kilometers of the former mining sites (Eustis and Capleton), and concentration of metals in alluvial soils is slightly higher near the mine sites.

This study investigates the effect of volatile organic compound (VOC) feed fluctuations on trickle bed air biofilters (TBABs) and the ability of a two-bed adsorption/desorption unit in dampening fluctuations. A mixture of n-hexane, benzene, and methanol with concentration ratios of 1:3:6.6 was fed to two parallel TBABs. To simulate feed fluctuations, four different square waves were applied. The total VOC loading rates (LRs) varied from 28.4 to 107.3 g/m³ h. The average concentration of VOCs applied to both TBABs was within allowable limits as determined in an earlier study. One TBAB was preceded by a two-bed cyclic adsorption/desorption unit (integrated unit), while the other TBAB (control unit) was directly subjected to the high and low peaks. n-Hexane elimination in the integrated unit was steady, and stable performance was obtained (75%-89%) based on the LRs, whereas the control unit showed erratic performance. The other two VOCs were mostly removed.

In this study, a sequencing batch reactor was set up and operated for over three months to cultivate polyphosphate-accumulating organisms polyphosphate-accumulating organisms (PAOs) in the enriched activated sludge. Batch studies were then carried out to study the effect of different carbon sources on phosphorus removal as well as polyhydroxybutyrate (PHB) production. The carbon sources investigated were acetate, glucose, wastewater, and beef extract. It was found that enhanced biological phosphorus removal could not be achieved using glucose as substrate. This suggested that glucose was not a good candidate for biological phosphorus removal. In terms of PHB production, using acetate and glucose as substrate resulted in PHB production of 42% and 40%, respectively, of the dry cell weight (DCW). Lower PHB production was obtained from using municipal wastewater and beef extract as a carbon source. This resulted in ∼15% and 13% of DCW. It was concluded that municipal wastewater activated sludge can be an economic alternative for PHB production if municipal wastewater is mixed with certain kinds of carbon-enriched industrial wastewater.

Airborne particulates play a significant role in the atmospheric radiative balance and impact human health. To characterize this impact, global-scale observations and data products are needed. Satellite products allow for this global coverage but require in situ validations. This study used a remote-controlled aerial vehicle to look at the horizontal, vertical, and temporal variability of airborne particulates within the first 150 m of the atmosphere. Four flights were conducted on December 4, 2014, between 12:00 pm and 5:00 pm local time. The first three flights flew a pattern of increasing altitude up to 140 m. The fourth flight was conducted at a near-constant altitude of 60 m. The mean PM_2.5 concentration for the three flights with varying altitude was 36.3 µg/m³, with the highest concentration occurring below 10 m altitude. The overall vertical variation was very small with a standard deviation of only 3.6 µg/m³. PM_2.5 concentration also did not change much throughout the day with mean concentrations for the altitude-varying flights of 35.1, 37.2, and 36.8 µg/m³. The fourth flight, flown at a near-constant altitude, had a lower concentration of 23.5 µg/m³.

Despite reducing the consumption of the pesticide (2,4-dichlorophenoxy)acetic acid (2,4-D), it can still be occasionally found in natural waters. The most effective method for its removal is adsorption on a solid surface using carbonaceous sorbents; however, these sorbents are considered highly priced. Therefore, diverse waste products have been increasingly used in recent years. In this study, the sorption possibility of 2,4-D from aqueous solutions with low concentration (1 µg L⁻¹) of carbon- and silicon-containing sorbents of different nature was investigated. It was observed that precipitated silica from rice husk could be used for sorption posttreatment of 2,4-D. There was almost a complete removal of the pesticide with the carbon sorbent by “Sibunit”. Mesoporous sorbents derived from rice husk and straw showed a sorption efficiency of 23%-35%, indicating their use for treatment of natural waters.

This study focuses on the reclassification of a soil texture system following a hybrid approach in which the conventional particle-size distribution (PSD) models are coupled with a random forest (RF) algorithm for achieving more generally applicable and precise outputs. The existing parametric PSD models that could be used for this purpose have various limitations; different models frequently show unequal degrees of precision in different soils or under different environments. The authors present in this article a novel ensemble modeling approach in which the existing PSD models are used as ensemble members. An improvement in precision was proved by better statistical indicators for the results obtained, and the article documents that the ensemble model worked better than any of its constituents (different existing parametric PSD models). This study is verified by using a soil dataset from Slovakia, which was originally labeled by a national texture classification system, which was then transformed to the USDA soil classification system. However, the methodology proposed could be used more generally, and the information provided is also applicable when dealing with the soil texture classification systems used in other countries.

AERMOD and CALPUFF air dispersion models were evaluated for their performance in predicting nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) in Maptaphut industrial area in Thailand. Emission data were obtained from 292 point sources in the study domain. Modeled results were compared with those measured data from 10 receptor sites. Evaluation of model performance was carried out by using statistical analysis. Overall results revealed that AERMOD provided more accurate results than CALPUFF model for both NO₂ and SO₂ predictions. As for the highest value, results from robust highest concentration analysis indicated that AERMOD had better performance in predicting extreme high-end concentration than CALPUFF.