Phytoremediation is an emerging green technology that uses plants and their associated microbes to remediate different environments contaminated with various pollutants. Phytoremediation, as an effective soil remediation technology, has gained popularity in the past ten years both in developed and developing countries. The main goal of the current article is to improve the understanding of phytoremediation of organic pollutants with emphasis on hydrocarbons. To design phytoremediation systems and also enhancement of their efficiency, either in laboratory or in field experiments, there is a serious need for better knowledge of phytoremediation mechanisms and also of factors affecting phytoremediation. In addition to phytoremediation applications, advantages, and limitations, its mechanisms and related new developments have been discussed in this article.

The present research article highlights the metal (Cd, Cu, Pb, Zn and Fe)distribution pattern in the RSPM generated in different hot spot sites located at Kochi, theQueen of Arabian Sea. These sampling sites are categorized under three different zonesas estuarine, riverine, and coastal. Two sampling phases are selected in order to check theconsistency in pollution trend after a two year gap and are described in Phase I and PhaseII, respectively. Metals are noticed to be intensely concentrated in the post monsoonmonths in both phases. Among the metals, Fe is revealed as the prominent metal at theestuarine sites. Estuarine and riverine zone expresses the overall enrichment pattern withslight difference at coastal regime in phase I. In phase II, insignificant metal load withirregular pattern is observed. Source apportionment study reveals that major sources ofmetals are from automobile exhausts and the estuarine zone is entangled with 45.9%.

Readymade garment industries are the prominent economic sector for Bangladesh as well as scoping the huge working area for workers. But health condition of workers, drinking water quality, and proper maintenance of the environmental parameters are not well monitored. This study aims to assess the physio-chemical and bacteriological quality of drinking water provided for the garment workers in Dhaka. Ten garment industries were pre-selected for the water quality analysis and three drinking water samples from each industry were taken for further analysis. Physio-chemical parameters viz pH, TDS were measured by probe method and Total harness and Chloride of the water samples were measured by titrimetric method, respectively. Biological parameters viz Total coliforms, Fecal coliforms, Total aerobic bacteria count, Fecal streptococci, Pseudomonas spp., and Vibrio Cholerae were determined through standard procedure. Results show that pH (6.7±0.05 to 7.4±0.20), TDS (126.2±8.42 to 217.9±3.60 mg/L), Total Hardness (92±7.07 to 275±21.22 mg/L), and Chloride (8.5±0.95 to 46.5±3.27 mg/L) are within the acceptable limit. Bacteriological results show that Total coliform (1.05×103±0.071×103 to 2.16×103±0.084×103 CFU/100 ml), Fecal coliforms (145±2.828 to 249±21.213 CFU/100 ml), and Total aerobic bacteria count (2152.5±399.51 to 5540.5±185.97 CFU/100 ml) are higher than the standard limits. Pseudomonas spp. was also present in all drinking water samples but Fecal streptococci and Vibrio Cholerae were absent in all water samples. Bacteriological analysis shows that sources of drinking water are contaminated and proper maintenance and screening facilities should be improved.

The contamination of riverbed sediments by heavy metals has assumedserious problems due to their toxicity and accumulative behavior. The present studyinvestigated the concentrations of heavy metals from the bottom sediments of ShitalakhyaRiver to understand the level of contamination and their distribution. The averageconcentrations of heavy metals Al, K, Ca, Mg, Fe, As, Cu, Co, Cr, and Zn are 30432.41,10929.21, 391139.13, 23148.14, 38697.37, 14.02, 143.69, 13.37, 74.82, and 200.59mg/kg respectively in river sediments, and their abundance decreased in the followingorder: Ca (79.05%)>Fe (7.82%)>Al (6.15%)>Mg (4.68%)>K (2.21%)>Zn (0.04%)>Cu(0.03%)>Cr (0.015%)>As (0.0028%)>Co (0.0027%). In most cases, the meanconcentrations of the heavy metals exceed the permissible limit. Significantly higherconcentrations of Ca, Mg, Zn, and Cu were found in sediment samples. The heavy metalscontaminations in the sediments were also evaluated by applying index of geoaccumulation(Igeo), contamination factor (Cf), degree of contamination (Cd), and pollutionload index (PLI) etc. These indices indicated that most of the samples were moderate tostrongly pollute by heavy metals and the spatial distribution showed that the northern andsouthern parts of the study area are more contaminant than middle portion.

The staff working at beauty centers are exposed to various chemicalproducts used daily in their working environment. Both hair dressers and nail techniciansare exposed to chemicals that are known to have an influence on the respiratory system.In order to evaluate such influence, this cross-sectional observational study wasconducted on a randomly selected 14 beauty centers in Dammam City, Saudi Arabia. Atthe investigated salons, both of respiratory symptoms and the quality of air wereevaluated and data were analyzed statistically. 40.5% out of the 79 subjects included inthe study were hairdressers, 17.7% were nail technicians and (41.8%) were working inboth of the previously mentioned areas as part of their everyday practice. The staffcomplained of respiratory symptoms which include dyspnea, cough, phlegm, wheeze, andshortness of breath. Both hairdressers and nail technicians developed respiratorysymptoms while working in the salons. Indoor Air pollution was assessed and many datawere out of the normal standard ranges which include: relative humidity (RH), volatileorganic compounds (VOC), carbon dioxide (CO2), and ammonia (NH3). We conclude thatgood ventilation is required to reduce the influence of such substances on the respiratorysymptoms of the staff working at salons.

In the present study, air quality analyses for ozone (O3) were conducted in Shiraz, a city in the south of Iran. The measurements were taken from 2011 through 2012 in two different locations to prepare average data in the city. The average concentrations were calculated for every 24 hours, each month and each season. Results showed that the highest concentration of ozone occurs generally in the afternoon while the least concentration was found in the morning and at midnight. Monthly concentrations of ozone showed the highest value in August and June while the least value was in December. The seasonal concentrations showed the least amounts in autumn while the highest amounts were in spring. Relations between the air pollutant and some meteorological parameters were calculated statistically using the daily average data. The wind data (velocity, direction), relative humidity, temperature, sunshine periods, evaporation, dew point, and rainfall were considered as independent variables. The relationships between concentration of pollutant and meteorological parameters were expressed by multiple linear regression equations for both annual and seasonal conditions using SPSS software. Root mean square error (RMSE) test showed that among different prediction models, stepwise model is the best option.

Population’s exponential growth along with drought has increased water resources limitation, especially in arid and semi-arid area. Therefore, the use of non-conventional water is an important tool for water resource management. If unconventional water has no negative impact on soil properties and water, it can be used for irrigation coupled with desertification projects. So, this paper tries to present the effect of irrigation with municipal wastewater, salt water, brackish water, and combination of salty water and wastewater on some soil properties including nitrogen, phosphorus, and potassium in Qom plain. Soil samples were taken from agricultural land treated by wastewater, saline water, brackish water, combination of salty water, and wastewater and range land as control in five treatments from depths of 0-30 and 60-90 centimeter. The results showed that wastewater has increased the amount of N, P, and K to other treatments and control area. The concentration of potassium in surface layer of area treated by combination of salty water and wastewater with amount of 459.39 ppm has the most significant difference to control and other treatments. Also, the maximum amount of nitrogen was observed in sub layer of saline and brackish water treatment with amount of 0.08 percent.

There are many potential risks to human health from heavy metal contamination of vegetables resulting from wastewater irrigated sites. This study was carried out to assess the concentration of chromium (Cr) and the risk to human health by chromium through the intake of locally grown vegetables collected from wastewater irrigated agricultural fields. Twenty-seven samples of 9 (nine) different types of vegetables were analyzed by an Atomic Absorption Spectrometer (AAS) (Varian AAS 240 F S). The range of chromium concentration in wastewater irrigated vegetables was ND (Not detected) -4.14mg/kg. The highest mean concentration of chromium (4.14 mg/kg) was detected in radish. The mean concentration of chromium in all the vegetables was within the safe limits of WHO/FAO except radish which was much higher than the standard. Health risk index for chromium contamination in all vegetables was less than 1 for both adults and children which cause no risk to the local population. Among all vegetables tested, the highest intake value of chromium was from consumption of radish for both adults and children. The lower values of health risk index indicated chromium contamination in the wastewater irrigated vegetables that cause less negative impact on human health.

Surface ozone (Surface O3)is a secondary pollutant and there are only limited studies on ozone in South India. Studies have revealed a strong correlation between higher ozone levels and warmer days. Surface O3 along with its precursors like NO2, CO and CH4 are being measured at Kanyakumari (8.0780° N, 77.5410° E), TamilNadu, India and in this paper we present the summer time variation of ozone from 2010to 2014 . Surface O3 showed a clear diurnal variation, but an irregularity was observed during the night time for all the measuring days of Summer 2014.There was a formation of a well pronounced secondary peak in Surface O3 during 0230 hrs accompanied by relatively strong wind patterns. Since the normal diurnal variation cannot explain this phenomenon,this uncertain behavior is probably attributed tolow NOX titrations and the downward mixing of ozone in the ground layer.The daily mean of Surface O3showed an increasing trend in the study area during the summer monthsand a negative correlation was observed with its precursors. The correlation of Surface O3 with temperature and wind speed for the entire summer season was found as r= +0.68, p= 4.314E-05 and r= +0.63, p

Air pollution is a challenging issue in some of the large cities in developing countries. Air quality monitoring and interpretation of data are two important factors for air quality management in urban areas. Several methods exist to analyze air quality. Among them, we applied the dynamic neural network (TDNN) and Radial Basis Function (RBF) methods to predict the concentrations of ground-level ozone in Karaj City in Iran. Input data included humidity, hour temperature, wind speed, wind direction, PM2.5, PM10 and benzene, which were monitored in 2014. The coefficient of determination between the observed and predicted data was 0.955 and 0.999 for the TDNN and RBF, respectively. The Index of Agreement (IA) between the observed and predicted data was 0.921 for TDNN and 0.9998 for RBF. Both methods determined reliable results. However, the RBF neural network performance had better results than the TDNN neural network. The sensitivity analysis related to the TDNN neural network indicated that the PM2.5 had the greatest and benzene had the minimum effect on prediction of ground-level ozone concentration in comparison with other parameters in the study area.