GIS based hotspot analysis and health risk assessment of groundwater arsenic from an unconfined deep aquifer of Lahore, Pakistan.

Use of groundwater for drinking purpose poses serious hazards of arsenic contamination particularly in plains of western Himalayan region. Therefore, current study was designed to investigate the level of Arsenic (As) in the water obtained from tubewells in a metropolitan city of Lahore, Pakistan and assess the human health risk. So, a total of 73 tubewells were sampled randomly in the manner that the whole study region was covered without any clustering. The water samples were analyzed for As using atomic absorption spectrophotometer. These samples were also tested for total dissolved solids, chlorides, pH, alkalinity, turbidity, hardness and calcium. GIS based hotspots analysis technique was used to investigate the spatial distribution patterns. Our results revealed that only one sample out of total 73 had arsenic level below the WHO guideline of 10 µg/L. The spatial distribution map of arsenic revealed that the higher concentrations of arsenic are present in the north-western region of Lahore. The cluster and outlier analysis map using Anselin Local Moran's I statistic indicated the presence of an arsenic cluster in the west of River Ravi. Furthermore, the optimized hotspot analysis based on Getis-Ord Gi* statistics confirmed the statistical significance (P < 0.05) and (P < 0.01) of these samples from the vicinity of River Ravi. Regression analysis showed that variables such as turbidity, alkalinity, hardness, chlorides, calcium and total dissolved solids were significantly (all P < 0.05) associated with level of Arsenic in tubewells. Whereas, PH and electrical conductivity and other variables like town, year of installation, depth and diameter of the wells were not significantly associated with Arsenic concentrations in tubewells. Principal component analysis (PCA) exhibited that the random distribution of tubewell samples showed no distinct clustering with towns studied. Health risk assessment based on hazard and Cancer risk index revealed serious risk of developing carcinogenic and non-carcinogenic diseases particularly in children. The health risk due to prevalence of high As concentration in tubewells' water need to be mitigated immediately to avoid worst consequences in future.

Health risk assessment and geospatial analysis of arsenic contamination in shallow aquifer along Ravi River, Lahore, Pakistan.

The exposure variation of arsenic from different ground and surface water sources has remained unpredictable which may cause severe human health problems. The current study is, therefore, designed to analyze the spatial variability of arsenic contamination in shallow aquifer and assess the potential human health risks. For this purpose, a total of 55 groundwater, 10 drain water, 4 river water, and 6 sediment samples were collected along zero to 5 km stretch of the River Ravi, Lahore. All water samples were tested for As, pH, and total dissolved solids (TDS), whereas sediments were only tested for As. Health risk models were used to predict cancer and non-cancer risk in adults and children. Among water samples, highest median (minimum-maximum) concentrations (µg/L) of As were recorded 53.32 (1.98-1555) in groundwater, followed by 53.04 (1.58-351.5) in drain water, and 4.80 (2.13-8.67) in river water, respectively, whereas As concentration (mg/kg) in river sediments was 6.03 (5.56-13.92). Variation of As in groundwater was non-significant (P > 0.05) among every 1-km stretch from the Ravi River. However, maximum median concentrations (µg/L) of 60.18 and 60.08 were recorded between 2-3 and 0-1 km from River Ravi, respectively, reflecting possible mixing of river water with shallow aquifers. A very high cancer and non-cancer risk (HI > 1.0 × 10-4) through groundwater As exposure was predicted for both children and adults. The current study concluded that prevalence of As above WHO prescribed limits in shallow aquifer along the urban stretch of the River Ravi is posing serious health risk to the exposed population.

A multi-tissue biomonitoring investigation of toxic trace elements and their trophic transfer potential in a semi aquatic bird species, the Cattle Egret (Bubulcus ibis).

The constant exposure of toxic trace elements can elicit adverse health effects particularly in birds and species residing higher at the food web. The current study is designed to evaluate the tendency of toxic trace elements viz. Cd, Cr, Pb, Cu, As and Hg to bioaccumulate in liver, kidney, blood, pelvic and pectoral muscles of cattle egret (Bubulcus ibis) collected from premises of a metropolitan city, Lahore, Pakistan. Further, the Trophic Transfer Potential of these elements was also estimated using prey/food samples of cattle egret. All of the selected toxic trace elements except Hg and As were detected with varying concentrations in different tissues of cattle egret. In general, toxic trace elements followed the pattern as Cu > Pb > Cd > Cr in tissues of cattle egret. The maximum mean (Min-max) concentrations (µg/g) of Cu 0.58 (0.11-0.93) and Pb 0.46 (0.40-0.54) in blood and Cd at 0.46 (0.40-0.54) were observed in liver. Similarly, the highest mean (min-max) concentration (µg/g) of Cr 0.17 (0.09-0.25) was recorded in pectoral muscle. In general, blood and liver were found as the most contaminated tissues followed by kidney, pectoral and pelvic muscles. Differences of trace elements were found non-significant (all P > 0.05) among tissues of cattle egret reflecting their homogenous distribution in body. Principal Component Analysis (PCA) corroborated lack of strong association between any of the trace elements and tissues. All the toxic trace elements except Cr showed higher tendency of trophic transfer potential through food chain in all the tissues of Cattle Egret (TTF >1). Although the current study revealed decreasing trends of toxic trace elements, yet their still presence in the local environment and greater likelihood of trophic transfer can undoubtedly cause some severe health effects to the already declining bird populations.

Trends and projections of land use land cover and land surface temperature using an integrated weighted evidence-cellular automata (WE-CA) model.

Land use land cover (LULC) change has become a major concern for biodiversity, ecosystem alteration, and modifying the climatic pattern especially land surface temperature (LST). The present study assessed past and predicted future LULC and LST change in the Swabi District of Pakistan. LULC maps were generated from satellite data for years 1987, 2002, and 2017 using supervised classification. Mean LST and its areal change were estimated for different LULC classes from thermal bands of satellite images. LULC and LST were projected for the year 2047 using the integrated weighted evidence-cellular automata (WE-CA) model and a regression equation developed in this study, respectively. LULC change revealed an increase of > 5% in the built-up while a decrease in the agricultural area by ~ 9%. There was an increase of ~ 63% area in the LST class ≥ 27 °C which may create urban heat island (UHI). Simulation results indicated that the built-up area will further be increased by ~ 3% until 2047. Area associated with LST class > 30 °C indicated a further increase of ~ 38% till 2047 with reference to year 2017. Findings of this study suggested proper utilization of LULC in order to mitigate the creation of UHIs associated with urbanization and built-up areas.

Groundwater quality assessment and its correlation with gastroenteritis using GIS: a case study of Rawal Town, Rawalpindi, Pakistan.

Majority of the people of Pakistan get drinking water from groundwater source. Nearly 40 % of the total ailments reported in Pakistan are the result of dirty drinking water. Every summer, thousands of patients suffer from acute gastroenteritis in the Rawal Town. Therefore, a study was designed to generate a water quality index map of the Rawal Town and identify the relationship between bacteriological water quality and socio-economic indicators with gastroenteritis in the study area. Water quality and gastroenteritis patient data were collected by surveying the 262 tubewells and the major hospitals in the Rawal Town. The collected spatial data was analyzed by using ArcGIS spatial analyst (Moran's I spatial autocorrelation) and geostatistical analysis tools (inverse distance weighted, radial basis function, kriging, and cokriging). The water quality index (WQI) for the study area was computed using pH, turbidity, total dissolved solids, calcium, hardness, alkalinity, and chloride values of the 262 tubewells. The results of Moran's I spatial autocorrelation showed that the groundwater physicochemical parameters were clustered. Among IDW, radial basis function, and kriging and cokriging interpolation techniques, cokriging showed the lowest root mean square error. Cokriging was used to make the spatial distribution maps of water quality parameters. The WQI results showed that more than half of the tubewells in the Rawal Town were providing "poor" to "unfit" drinking water. The Pearson's coefficient of correlation for gastroenteritis with fecal coliform was found significant (P < 0.05) in Water and Sanitation Agency (WASA) zone 2, and with shortage of toilets, it was significant (P < 0.05) in WASA zones 1 and 3. However, it was significantly (P < 0.01) inversely related with literacy rate in WASA zones 1, 2, and 3.