Cancer and Non-Cancer Health Risk from Eating Cassava Grown in Some Mining Communities in Ghana

Food crops such as cassava, cocoyam and other tuber crops grown in mining communities uptake toxic or hazardous chemicals such as arsenic, and cadmium, from the soil. Cassava is a stable food for Ghanaians. This study evaluated human health risk from eating cassava grown in some mining communities in Ghana such as Bogoso, Prestea, Tarkwa and Tamso, which are important mining towns in the Western Region of Ghana. The study evaluated cancer and non-cancer health effects from eating cassava grown in the study areas in accordance with US Environmental Protection Agency’s Risk Assessment guidelines. The results of the study revealed the following: cancer health risk for Tamso, 0.098 (RME – Reasonable Maximum Exposure) and 0.082 (CTE – Central Tendency Exposure). This means that approximately 10 and 8 out of 100 resident adults are likely to suffer from cancer related cases by RME and CTE parameters respectively. For Prestea, we have 0.010 and 0.12, which also means that approximately 1 out of 100 and 10 resident adults out of 100 are also likely to suffer from cancer related diseases by RME and CTE parameters. The results of the study obtained were found to be above the acceptable cancer risk range of 1× 10⁻⁶ to 1× 10⁻⁴, i.e., 1 case of cancer out of 1 million or 100,000 people respectively.     

Anaerobic tapered fluidized bed reactor for starch wastewater treatment and modeling using multilayer perceptron neural network

Anaerobic treatability of synthetic sago wastewater was investigated in a laboratory anaerobic tapered fluidized bed reactor(ATFBR) with a mesoporous granular activated carbon(GAC)as a support material.The experimental protocol was defined to examine the effect of the maximum organic loading rate(OLR),hydraulic retention time(HRT),the efficiency of the reactor and to report on its steady- state performance.The reactor was subjected to a steady-state operation over a range of OLR up to 85.44 kg COD/(m~3.d).The COD removal efficiency was found to be 92% in the reactor while the biogas produced in the digester reached 25.38 m~3/(m~3·d) of the reactor. With the increase of OLR from 83.7 kg COD/(m~3.d),the COD removal efficiency decreased.Also an artificial neural network(ANN) model using multilayer perceptron(MLP)has been developed for a system of two input variable and five output dependent variables. For the training of the input-output data,the experimental values obtained have been used.The output parameters predicted have been found to be much closer to the corresponding experimental ones and the model was validated for 30% of the untrained data.The mean square error(MSE)was found to be only 0.0146.     

Impacts of Changes in Precipitation Amount and Distribution on Water Resources Studied Using a Model Rainwater Harvesting System

Water supply reliability is expected to be affected by both precipitation amount and distribution changes under recent and future climate change. We compare historical (1951‐2010) changes in annual‐mean and annual‐maximum daily precipitation in the global set of station observations from Global Historical Climatology Network and climate models from the Inter‐Sectoral Impact Model Intercomparison Project (ISI‐MIP), and develop the study to 2011‐2099 for model projections under high radiative forcing scenario (RCP8.5). We develop a simple rainwater harvesting system (RWHS) model and drive it with observational and modeled precipitation. We study the changes in mean and maximum precipitation along with changes in the reliability of the model RWHS as tools to assess the impact of changes in precipitation amount and distribution on reliability of precipitation‐fed water supplies. Results show faster increase in observed maximum precipitation (10.14% per K global warming) than mean precipitation (7.64% per K), and increased reliability of the model RWHS driven by observed precipitation by an average of 0.2% per decade. The ISI‐MIP models show even faster increase in maximum precipitation compared to mean precipitation. However, they imply decreases in mean reliability, for an average 0.15% per decade. Compared to observations, climate models underestimate the increasing trends in mean and maximum precipitation and show the opposite direction of change in reliability of a model water supply system.     

TRMM 3B42卫星降水数据在赣江流域径流模拟中的应用

以赣江流域为研究区,基于观测降水和TRMM准实时数据(3B42RTV6、3B42RTV7)和分析数据(3B42V6、3B42V7),驱动VIC水文模型,开展卫星降水产品在赣江流域的水文模拟,评估TRMM降水产品在水文模拟中的应用能力。结果表明:(1)在赣江流域,3B42V7估算的降水与实测降水的对比结果最好,3B42RTV6的估算精度最低,3B42RTV7较3B42RTV6在赣江流域的降水估算精度提升非常明显;(2)在径流模拟方面,3B42V6和3B42V7在日尺度上尽管对洪峰的模拟有所偏差,但模拟结果仍能反映径流变化特征,在月尺度上模拟结果精度较高,纳什系数均在0.9以上,并且二者在4、5月的径流模拟结果较好,7、8月的模拟结果较差,而3B42RTV6对径流的模拟能力较差,日径流量和月径流量均呈现明显低估,3B42RTV7对径流的模拟结果比3B42RTV6有明显改善,可以满足实时水文预报的需求。     

近50年鄱阳湖五大流域降水变化特征研究

基于鄱阳湖流域在江西省内部分对应的79县市气象站1960～2006年逐日降水观测资料,采用线性回归的方法分别研究五大流域的年降水量、降水日数、暴雨日数等3要素的变化趋势,并用Mann法进行了变化趋势的显著性检验,用距平与均方差之比达到15和20作为气候异常检验指标,对各流域的各时间序列进行了异常检验,采用了Mann Kendall法对各时间序列进行突变检测。结果表明：（1）各流域的年降水量变化趋势基本一致,年降水量与年暴雨日数密切相关;饶河流域强降水事件较多,降水强度大,赣江中游流域降水时间分布相对较均匀,强降水事件较少;（2）各流域年降水量、暴雨日数总体呈波动上升趋势,20世纪90年代以来暴雨日数异常偏多的概率最大;（3）年降水日数以20世纪80年代中期为界,之前呈波动上升趋势,之后呈波动下降趋势,2002年至今各流域降雨日数明显偏少;（4）各流域的年降水量、降水日数、暴雨日数均未出现趋势性的突变;（5）近50年来鄱阳湖流域降水时间分布不均的情况加剧,旱涝灾害风险增加。     

MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.     

Modelling vegetation greenness responses to climate variability in a Mediterranean terrestrial ecosystem

Accurate knowledge of the quality and environmental impact of the highway runoff in Pear River Delta, South China is required to assess this important non-point pollution source. This paper presents the quality characterization and environmental impact assessment of rainfall runoff from highways in urban and rural area of Guangzhou, the largest city of Pear River Delta over 1 year’s investigation. Multiple regression and Pearson correlation analysis were used to determine influence of the rainfall characteristics on water quality and correlations among the constituents in highway runoff. The results and analysis indicates that the runoff water is nearly neutral with low biodegradability. Oil and grease (O&G), suspended solids (SS) and heavy metals are the dominant pollutants in contrast to the low level of nutrient constituents in runoff. Quality of highway runoff at rural site is better than that of at urban site for most constituents. Depth and antecedent dry period are the main rainfall factors influencing quality of highway runoff. The correlation patterns among constituents in highway runoff at urban site are consistent with their dominant phases in water. Strong correlations (r ≥ 0.80) are found among chemical oxygen demand (COD), total phosphorus, Cu and Zn as well as conductivity, nitrate nitrogen and total nitrogen. O&G, COD, SS and Pb in highway runoff at urban site substantially exceed their concentrations in receiving water of Pear River. The soil directly discharged by highway runoff at rural site has contaminated seriously by heavy metals in surface layer accompanying with pH conversion from original acidic to alkaline at present.     

Does Including Soil Moisture Observations Improve Operational Streamflow Forecasts in Snow‐Dominated Watersheds?

Changing climate and growing water demand are increasing the need for robust streamflow forecasts. Historically, operational streamflow forecasts made by the Natural Resources Conservation Service have relied on precipitation and snow water equivalent observations from Snow Telemetry (SNOTEL) sites. We investigate whether also including SNOTEL soil moisture observations improve April‐July streamflow volume forecast accuracy at 0, 1, 2, and 3‐month lead times at 12 watersheds in Utah and California. We found statistically significant improvement in 0 and 3‐month lead time accuracy in 8 of 12 watersheds and 10 of 12 watersheds for 1 and 2‐month lead times. Surprisingly, these improvements were insensitive to soil moisture metrics derived from soil physical properties. Forecasts were made with volumetric water content (VWC) averaged from October 1 to the forecast date. By including VWC at the 0‐month lead time the forecasts explained 7.3% more variability and increased the streamflow volume accuracy by 8.4% on average compared to standard forecasts that already explained an average 77% of the variability. At 1 to 3‐month lead times, the inclusion of soil moisture explained 12.3‐26.3% more variability than the standard forecast on average. Our findings indicate including soil moisture observations increased statistical streamflow forecast accuracy and thus, could potentially improve water supply reliability in regions affected by changing snowpacks.     

西安市2013年PM_(2.5)浓度变化分析研究

全面分析2013年西安市13个国控环境空气质量自动监测子站PM2.5监测数据。结果表明:2013年西安市环境空气中PM2.5年均值为105μg/m3,超过《环境空气质量标准》(GB 3095—2012)二级要求(35μg/m3)200.0%,污染较严重;西安市各子站PM2.5月均值总体呈两边高、中间低的"V"型趋势,全市及各子站PM2.5月均值分别为44~206、32~275μg/m3;采暖期(上半年采暖期为1—3月,下半年采暖期为11—12月)、非采暖期(4—10月)PM2.5平均值分别为156、70μg/m3;上、下半年采暖期PM2.5平均值分别为178、124μg/m3;西安市气象风力以微风为主,雨天集中在5—9月,期间PM2.5月均值小于80μg/m3。     

Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model1

Moore, R.D. (Dan), J.W. Trubilowicz, and J.M. Buttle, 2011. Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model. Journal of the American Water Resources Association (JAWRA) 48(1): 32‐42. DOI: 10.1111/j.1752‐1688.2011.00595.x Abstract: Prediction of streamflow in ungauged basins is a global challenge, but is particularly an issue in physiographically complex regions like British Columbia (BC), Canada. The objective of this study was to assess the accuracy of a simple water balance model that can be run using existing spatial datasets. The model was developed by modifying an existing monthly water balance model to account for interception loss from forest canopy, glacier melt, and evaporation from lakes. The model was run using monthly climate normals from the ClimateBC application, which have a horizontal resolution of 400 m. Each ClimateBC grid cell was classified as forest, open land, glacier or water surface based on provincial scale digital maps of biogeoclimatic zones, glaciers, and water. The output was monthly mean runoff from each grid cell. These values were integrated within the catchment boundaries for streams gauged by the Water Survey of Canada. Annual runoff was predicted with modest accuracy: after updating the predicted runoff by interpolating errors from neighboring gauged streams, the mean absolute error was 25.4% of the gauged value, and 52% of the streams had errors less than 20%. However, the model appears to be quite robust in distinguishing between pluvial, hybrid, and melt‐dominated hydroclimatic regimes, and therefore has promise as a tool for catchment classification.