Assessment of deep aquifer groundwater quality in a geographically unique climatic region of Southern Western Ghats,India using water quality indices

Water quality index (WQI) models are generally used in hydrochemical studies to simplify complex data into single values to reflect the overall quality. In this study, deep groundwater quality in the Chittur and Palakkad Taluks of the Bharathapuzha river basin of Kerala, India, was assessed by employing the WQI method developed by the Canadian Council of Ministers of the Environment (CCME). The assessment of overall water quality is indispensable due to the specific characteristics of the study area, such as geography, climate, over-drafting, and prevalent agricultural practices. Forty representative samples were collected from the study area for monsoon (MON) and pre-monsoon (PRM) seasons. The results showed a general increase of contents from MON to PRM. The major cations were spread in the order Ca²⁺>Na+>Mg²⁺>K⁺ and the anions HCO₃⁻>Cl⁻>CO₃²⁻ based on their relative abundance. Among various parameters analysed, alkalinity and bicarbonate levels during MON were comparatively high, which is indicative of carbonate weathering, and 90% of the samples failed to meet the World Health Organization (WHO, 2017)/Bureau of Indian Standards (BIS, 2012) drinking water guidelines. The CCME WQI analysis revealed that nearly 50% of the samples during each season represented good and excellent categories. The samples in the poor category comprised 10% in MON and 15% in PRM. The overall WQI exhibited 15% of poor category samples as well. The spatial depiction of CCME WQI classes helped to expose zones of degraded quality in the centre to eastward parts. The spatial and temporal variations of CCME WQI classes and different physicochemical attributes indicated the influence of common factors attributing to the deep groundwater quality. The study also revealed inland salinity at Kolluparamba and Peruvamba stations, where agricultural activities were rampant with poor surface water irrigation.     

Five-wheel framework for system-based monitoring of heavy metal pollution in rivers

Sectorial approach for monitoring heavy metal pollution in rivers has failed to report realistic pollution status and associated ecological and human health risks. The increasing spread of heavy metals from different sources and emerging risks to human and environmental health call for reexamining heavy metal pollution monitoring frameworks. Also, the sources, spread, and load of heavy metals in the environment have changed significantly over time, requiring consequent modification in the monitoring frameworks. Therefore, studies on heavy metal monitoring in rivers conducted in the last decade were evaluated for experimental designs, research frameworks, and data presentations. Most studies (∼99%) (i) lacked inclusiveness of all environmental compartments; (ii) focused on “one pollutant – one/two compartment” or sometimes “one pollutant – one compartment – one effect” approach; and (iii) remained “data-rich but information poor.” An ecological approach with integrative system thinking is proposed to develop a holistic approach for monitoring river pollution. It is visualized that heavy metal monitoring, risk analyses, and water management must incorporate tracking pollutants in different environmental compartments of a river (water, sediment, and floodplain/bank soil) and consider correlating it with riverbank land use. The systems-based pollution monitoring and assessment studies will reveal the critical factors that drive heavy metals pollutant movement in ecosystems and associated potential risks to the environment, wildlife, and humans. Also, water quality and pollution indexing tools would help better communicate complex pollution data and associated risks among all stakeholders. Therefore, integrating systems approaches in scientific- and policy-based tools would help sustainably manage the health of rivers, wildlife, and humans.     

天水市紫外吸收性气溶胶时空动态的遥感监测

采用OMI传感器的气溶胶产品,分析了2006—2015年中国西部城市天水市对流层紫外吸收性气溶胶的时空分布特征。结果表明:空间上,十年间天水市的吸收性气溶胶表现出从中部向周围依次减弱的南北向带状分布规律;季节变化呈现出秋冬季高于春夏季的规律;时间上,吸收性气溶胶指数(AI)从2006年的0.075增至2015年的0.506,年均值为0.28,年均增长率为57.5%;十年间出现2次阶段性增长和2次阶段性减小;AI年际变化与天水市地方总产值相关性为0.902,第一产业对其影响最大,第三产业影响最小。     

沼泽湿地水生无脊椎动物完整性指数构建与健康评价

依据2017年5、7、9月对三江平原19处沼泽湿地(参照湿地6处,受损湿地13处)的水生无脊椎动物采样结果,应用生物完整性理论和方法,构建水生无脊椎动物完整性指数,评价三江平原沼泽湿地健康状况。通过对27个候选指标的分布范围、判别能力和相关性分析,筛选出总分类单元数、扁卷螺科百分比、龙虱科百分比、刮食者百分比4个指标构成水生无脊椎动物完整性指数核心指标。采用比值法计算各指标参数值,将各参数值加和得到水生无脊椎动物完整性指数值。根据参照湿地水生无脊椎动物完整性指数值的25%分位数值确定评价标准,对小于25%分位数的值进行三等分,确定三江平原沼泽湿地健康评价标准:≥2.58,无干扰;1.72～2.58,轻度干扰;0.86～1.72,中度干扰;0～0.86,重度干扰。结果表明:所调查的三江平原沼泽湿地有78.95%受到不同程度的干扰(其中47.37%受到了中重度干扰),21.05%属于无干扰。     

快速溶剂萃取-分子筛脱水净化-气质联用法测土壤有机氯农药

用丙酮和正己烷(体积比为1∶1)作溶剂,在100℃和1 500 psi的压力下,用快速溶剂萃取仪从土壤中萃取出有机氯农药,用分子筛进行脱水和净化,GC-MS进行分析,对土壤中有机氯农药进行测定。方法的检出限为0.000 4~0.000 7 mg/kg,曲线的相关系数在0.998以上。对进口标准土进行测定,回收率为77.1%~105.2%,相对误差为-22.9%~5.2%,测定结果在证书允许误差范围内。用硅藻土制成高、中、低3个浓度级别的加标回收和精密度实验,加标回收率为84.3%~101.5%,相对标准偏差为0.6%~11.4%,表明方法准确可靠,方法用于实际土壤测定时发现土壤有不同程度的有机氯农药污染。     

基于稳健统计方法对实验室比对中土壤汞的质量控制指标研究

利用稳健四分位间距法和迭代法2种稳健统计方法,通过对全国31个省、自治区、直辖市范围内共334家环境监测单位开展土壤中汞的实验室间比对,对比对测定结果和质控数据进行统计分析,系统性地研究了土壤中汞的质量控制指标。建议实际监测工作中土壤汞的实验室间相对标准偏差范围为7%～19%,相对误差控制指标为±8%,低浓度水平下可适当放宽至±10%,加标回收率控制范围为81%～109%,为日常监测开展土壤汞的质量控制工作提供了评价依据,具有广泛的应用价值和较好的指导作用。     

不同煤层煤氧化自燃性实验分析

为研究不同煤层煤自然发火特征的异同性及规律，以淮南矿区1号、3号、6号、13号煤层为研究对象，通过自然发火实验，对不同煤层煤的自然发火期周期、煤样70℃时放热强度和R70值进行分析。研究结果表明:4个不同煤层煤样自燃性由强到弱依次为:3煤>6煤>1煤>13煤；变质程度相近的4个煤层，3煤自然发火期最短，这与煤体中硫分和水分含量高有关；13煤变质程度较高，且前期放热强度、耗氧速率增长缓慢，其自燃性较弱；4个不同煤层煤的耗氧速率、CO，CO2产生率，以及C2H4/C2H6值随煤温升高具有相似的变化规律；煤中CH4气体大量解吸出现于煤温60℃之前，煤中灰分在80~120℃开始逐渐吸热融化，解析和融化均会抑制煤氧接触并且减小煤氧反应放热总量。     

基于Landsat 8遥感数据的天津市地表温度反演

以Landsat 8遥感数据为数据源,进行天津市地表温度反演研究。首先采用单通道算法反演地表温度,并利用均值标准差法进行温度分级。然后建立不同温度等级面积比例的估算模型。再通过随机样点,从不同温度等级和土地覆盖类型2个角度,分别建立并比较不同类样点的地表温度与各指数的拟合模型。结果表明:次高温区域面积比例与人口密度、人均GDP都具有较高的决定系数;地表温度与NDVI、BAEM的二元线性回归决定系数高于地表温度与单一指数的决定系数;将样点分类后,低温点与MNDBI的决定系数高于其他温度等级样点,水域和植被样点与各种指数的决定系数高于其他地物类型样点。     

A climate-change vulnerability and adaptation assessment for Brazil's protected areas

Brazil hosts the largest expanse of tropical ecosystems within protected areas (PAs), which shelter biodiversity and support traditional human populations. We assessed the vulnerability to climate change of 993 terrestrial and coastal-marine Brazilian PAs by combining indicators of climatic-change hazard with indicators of PA resilience (size, native vegetation cover, and probability of climate-driven vegetation transition). This combination of indicators allows the identification of broad climate-change adaptation pathways. Seventeen PAs (20,611 km²) were highly vulnerable and located mainly in the Atlantic Forest (7 PAs), Cerrado (6), and the Amazon (4). Two hundred fifty-eight PAs (756,569 km²), located primarily in Amazonia, had a medium vulnerability. In the Amazon and western Cerrado, the projected severe climatic change and probability of climate-driven vegetation transition drove vulnerability up, despite the generally good conservation status of PAs. Over 80% of PAs of high or moderate vulnerability are managed by indigenous populations. Hence, besides the potential risks to biodiversity, the traditional knowledge and livelihoods of the people inhabiting these PAs may be threatened. In at least 870 PAs, primarily in the Atlantic Forest and Amazon, adaptation could happen with little or no intervention due to low climate-change hazard, high resilience status, or both. At least 20 PAs in the Atlantic Forest, Cerrado, and Amazonia should be targeted for stronger interventions (e.g., improvement of ecological connectivity), given their low resilience status. Despite being a first attempt to link vulnerability and adaptation in Brazilian PAs, we suggest that some of the PAs identified as highly or moderately vulnerable should be prioritized for testing potential adaptation strategies in the near future.     

Risk assessment and risk reduction of an acrylonitrile production plant

Reducing accident occurrence in petrochemical plants is crucial, thus appropriately allocating management resources to safety investment is a vital issue for corporate management as international competition intensifies. Understanding the priority of safety investment in a rational way helps achieve this objective.In this study, we targeted an acrylonitrile plant. First, Dow Chemical's Fire and Explosion Index (F&EI) identified the reaction process as having the greatest physical risk. We evaluated the severity of accidents in the reaction process using the Process Safety Metrics advocated by the Center for Chemical Process Safety (CCPS); however, this index does not express damages a company actually experience. To solve this problem, we proposed a new metric that adds indirect cost to CCPS metrics. We adopted fault tree analysis (FTA) as a risk assessment method. In identifying top events and basic events, we attempted to improve the completeness of risk identification by considering accidents from the past, actual plant operation and equipment characteristics, natural disasters, and cyber-attacks and terrorist attacks. Consequently, we identified the top events with high priority in handling because of serious accidents as fire/explosion outside the reactor, fire/explosion inside the reactor, and reactor destruction. The new CCPS evaluation index proposed in this study found that fire and explosion outside the reactor has the highest severity. We considered the creation of the fault tree (FT) diagram of the top event, estimating the occurrence probability, and identifying the risk reduction part and capital investment aimed at risk reduction. As an economically feasible selection method for risk reduction investment, using the difference in loss amounts before and after safety investments indicated investment priority.