Pesticides in shallow groundwater of Bahawalnagar, Muzafargarh, D.G. Khan and Rajan Pur districts of Punjab, Pakistan

In Pakistan there is little data on environmental contamination of rural water sources by pesticides. This study evaluated pesticide contamination of groundwater in four intensive cotton growing districts. Water samples were collected from 37 rural open wells in the areas of Bahwalnagar, Muzafargarh, D.G. Khan and Rajan Pur districts of Punjab and analysed for eight pesticides which are mostly used. Information on types of pesticide used and distance to nearest pesticide mixing area and application areas was obtained for each site. From the eight pesticides analysed, six pesticides were detected in the water samples. Only cypermethrin and cabosulfan were not detected. The percentage of detection of bifenthrin, lambda-cyhalothrin, carbofuran, endosulfan, methyl parathion and monocrotophos was, respectively 13.5%, 5.4%, 59.4%, 8%, 5.4% and 35.1% in July; 16.2%, 13.55%, 43.2%, 8%, N.D. (not detected) and 24.3% in October. Maximum contamination levels (MCLs) established by the U.S. Environmental Protection Agency for drinking water were not exceeded. The study has shown the need for monitoring pesticide contamination in rural water resources, and the development of drinking water quality standards for specific pesticides in Pakistan. The conclusions and recommendations will be disseminated to senior decision makers in central and local governments, extension agents and farmers.     

Habitat preference and population estimates of Indian pangolin (Manis crassicaudata) in district Chakwal of Potohar Plateau,Pakistan

Indian pangolin (Manis crassicaudata) is a fossorial, “Near threatened” mammalian species occurring in Pakistan and facing a risk of endangerment in its wild habitat. Being nocturnal, ecological data of the species is lacking in the country and in south Asia as well. The current study investigated some ecological parameters of the species like, distribution, habitat analysis, population and food habits in district Chakwal of Potohar Plateau. Illegal trapping and killing by professional nomads for its scales is the main threat to the species in the study area.     

Heavy metals concentration in edible fishes from coastal region of Kalpakkam, southeastern part of India

Concentrations of Cu, Mn, Zn, Fe, Cr, and Pb were estimated using ICP-MS in nine commercially important and locally consumed fish species (Sarda orientalis, Scomberomorus commerson, Rastrelliger kanagurta, Sardinella longiceps, Paraplagusia bilineata, Cynoglossus lida, Cynoglossus macrostomus, Lepturacanthus savala, and Siganus javus) collected from coastal waters of Kalpakkam, eastern part of India. Their concentration (μg g(-1)) in the examined fish species ranged as follows: Cu (0.8-6.5), Zn (14.3-27.9), Mn (0.5-8.8), Fe (17.6-117.0), Cr (0.24-1.78), and Pb (0.18-2.29). Concentrations of most of the metals in the fish species studied were found to be safe for human consumption barring Mn.     

Solid waste bin detection and classification using Dynamic Time Warping and MLP classifier

The increasing requirement for Solid Waste Management (SWM) has become a significant challenge for municipal authorities. A number of integrated systems and methods have introduced to overcome this challenge. Many researchers have aimed to develop an ideal SWM system, including approaches involving software-based routing, Geographic Information Systems (GIS), Radio-frequency Identification (RFID), or sensor intelligent bins. Image processing solutions for the Solid Waste (SW) collection have also been developed; however, during capturing the bin image, it is challenging to position the camera for getting a bin area centralized image. As yet, there is no ideal system which can correctly estimate the amount of SW. This paper briefly discusses an efficient image processing solution to overcome these problems. Dynamic Time Warping (DTW) was used for detecting and cropping the bin area and Gabor wavelet (GW) was introduced for feature extraction of the waste bin image. Image features were used to train the classifier. A Multi-Layer Perceptron (MLP) classifier was used to classify the waste bin level and estimate the amount of waste inside the bin. The area under the Receiver Operating Characteristic (ROC) curves was used to statistically evaluate classifier performance. The results of this developed system are comparable to previous image processing based system. The system demonstration using DTW with GW for feature extraction and an MLP classifier led to promising results with respect to the accuracy of waste level estimation (98.50%). The application can be used to optimize the routing of waste collection based on the estimated bin level.     

Taurine mitigates nitrite-induced methemoglobin formation and oxidative damage in human erythrocytes

Environmental Science and Pollution Research - Nitrite is present as a noxious contaminant in drinking water and causes oxidative damage in various tissues of humans and animals. It is a well-known...     

不同降水下覆盖与缓释肥减量对油菜土壤微生物群落结构的影响

为探讨沟垄集雨、秸秆覆盖和减量缓释肥集成技术对油菜土壤微生物群落结构的影响,在大田定位试验条件下,设置3种栽培方式（秸秆覆盖、沟垄集雨、传统平作）和4种施肥水平（习惯施肥、缓释肥减量20%、缓释肥减量40%、不施肥）,比较分析2016~2017年（多雨年份）和2017~2018年（季节性干旱年份）这2种不同降水年型下油菜土壤微生物群落结构对集成技术的响应.结果表明,不同降雨条件下,秸秆覆盖+缓释肥减量20%（J80）与沟垄覆盖+缓释肥减量20%（M80）较习惯栽培（PC）更利于土壤微生物生长.在多雨年型和季节性干旱年型下,J80与M80能平均分别提高微生物量碳9.94%和10.32%;提高土壤微生物量氮2.38%和1.19%.多雨年型下,土壤微生物磷酸脂肪酸（PLFA）总量较干旱年型降低30.75%,覆盖能有效提高土壤PLFA质量摩尔浓度.多雨年型下土壤细菌、真菌PLFA质量摩尔浓度较干旱年型平均减少33.67%和53.21%;而放线菌PLFA增加13.04%.微生物群落对异常降水具有敏感响应.多雨气候会造成细菌/真菌升高;干旱气候则会增加直链饱和脂肪酸/直链单不饱和脂肪酸及直链单不饱和脂肪酸/环丙烷脂肪酸.通过秸秆覆盖与缓释肥的集成技术,能稳定异常降水下的土壤微环境,缓解水分和养分胁迫,为油菜稳产和可持续发展提供有效途径.     

Investigation of oxidative stress enzymes and histological alterations in tilapia exposed to chlorpyrifos

Environmental Science and Pollution Research - Chlorpyrifos (ChF) is an organophosphate pesticide that is widely used in agricultural fields and indoor for controlling pests. Aquatic ecosystems are...     

Influence of coal ash on the concrete properties and its performance under sulphate and chloride conditions

Environmental Science and Pollution Research - This study investigated the influence of coal bottom ash (CBA) on the concrete properties and evaluate the effects of combined exposure of sulphate...