Coupled electrochemical methods for nitrogen and phosphorus recovery from wastewater: a review

Environmental Chemistry Letters - Declining mineral resources, high fertilizer production cost and widespread eutrophication are calling for the recovery of nitrogen and phosphorus from wastewaters...     

Temporal trends in agricultural water use and the relationships to hydroclimatic factors in the High Plains aquifer region

The High Plains aquifer (HPA) is the primary water source for agricultural irrigation in the US Great Plains. The water levels in many locations of the aquifer have declined steadily over the past several decades because the rate of water withdrawals exceeds recharge, which has been a serious concern to the water resources management in the region. We evaluated temporal trends and variations in agricultural water use and hydroclimatic variables including precipitation, air temperature, reference evapotranspiration, runoff, groundwater level, and terrestrial water storage across the HPA region for different periods from 1985 to 2020 at the grid, county, or region scale. The results showed that water withdrawals decreased from 21.3 km³/year in 1985 to 18.2 km³/year in 2015, while irrigated croplands increased from 71,928 km² in 1985 to 78,464 km² in 2015 in the entire HPA. The hydroclimatic time-series showed wetting trends in most of the northern HPA, but drying and warming trends in the southern region from 1985 to 2020. The groundwater level time-series indicated flat trends in the north, but significant declining in the central and southern HPA. Trends in irrigation water withdrawals and irrigation area across the HPA were controlled by the advancement of irrigation systems and technologies and the management of sustainable water use, but also were affected by dynamical changes in the hydroclimatic conditions.     

A new approach to spatial source apportionment of haze pollution in large scale and its application in China

Long-lasting expansion of haze pollution in China has already presented a stern challenge to regional joint prevention and control. There is an urgent need to enlarge and reconstruct the coverage of joint prevention and control of air pollution in key area. Air quality models can identify and quantify the regional contribution of haze pollution and its key components with the help of numerical simulation, but it is difficult to be applied to larger spatial scale due to the complexity of model parameters. The time series analysis can recognize the existence of spatial interaction of haze pollution between cities, but it has not yet been used to further identify the spatial sources of haze pollution in large scale. Using econometric framework of time series analysis, this paper developed a new approach to perform spatial source apportionment. We applied this approach to calculate the contribution from spatial sources of haze pollution in China, using the monitoring data of particulate matter (PM_2.5) across 161 Chinese cities. This approach overcame the limitation of numerical simulation that the model complexity increases at excess with the expansion of sample range, and could effectively deal with severe large-scale haze episodes.     

Health risk assessment of heavy metals in Cyprinus carpio (Cyprinidae) from the upper Mekong River

The purposes of this research are to quantify the concentration of heavy metals (Zn, Cu, As, Pb, Cd, and Hg) in the water and fish tissues of common carp (Cyprinus carpio) in the upper Mekong River and to thereby elucidate the potential dietary health risks from fish consumption of local residents. Surface water and fish tissues (gill, muscle, liver, and intestine) from four representative sample areas (influence by a cascade of four dams) along the river were analyzed for heavy metal concentrations. Results revealed that the levels of heavy metals in fish were tissue-dependent. The highest Cu and As levels were found in the liver; the highest Zn and Pb levels occurred in the intestine, and the highest Hg level was found in the muscle. The total target hazard quotient (THQ) value for residents is > 1 for long-term fish consumption, and local residents are, therefore, exposed to a significant health risk. Results from the current study provide an overall understanding of the spatial and tissue distribution of heavy metals in water and fish body along the upper Mekong River under the influence of cascade dams and highlight the potential health risk of As for the local residents of long-term fish consumption.

     

Characteristics analysis of near-field and far-field aerodynamic noise around high-speed railway bridge

Environmental Science and Pollution Research - The aerodynamic noise around the high-speed railway bridge is studied by the train-bridge-flow field numerical model and theory analysis. With the...     

有机肥处理对旱地红壤细菌群落及玉米生产力的影响

为探明旱地红壤细菌群落特征及玉米生产力对不同有机肥处理的响应，基于自2002年设置在中国科学院鹰潭红壤生态实验站的有机培肥长期定位试验，采用Illumina高通量测序，研究不同有机肥（不施肥，M0；低量有机肥，M1；高量有机肥，M2；高量有机肥加石灰，M3）处理下土壤细菌群落多样性和结构以及玉米生产力的变化.结果发现，与M0相比，土壤pH、有机质（SOM）、全氮（TN）、全磷（TP）含量和玉米生产力在不同有机肥（M1、M2和M3）处理下均显著增加，其中M3处理的提升效果最佳.施用有机肥显著提高了土壤细菌群落的Shannon、Evenness、Chao1与ACE指数，重塑了细菌群落结构.基于随机森林模型分析，土壤性质中的pH和TP显著影响土壤细菌多样性，而pH、SOM、TP和TN对土壤细菌群落结构影响显著.相关性分析和结构方程模型分析表明，土壤TP和SOM可以通过改变土壤细菌多样性和群落组成间接影响玉米生产力.研究结果从指导我国南方红壤区农田合理施肥的角度，为农田土壤质量提高及耕地产能提升提供科学依据.     

固相萃取-气相色谱法测定水中硝基氯苯类化合物

建立固相萃取-气相色谱法测定水中15种硝基氯苯类化合物的方法。选用HLB柱为固相萃取柱,选用环己烷∶丙酮(3∶1,V∶V)混合溶剂作洗脱剂,得到方法检出限为0.011～0.040μg/L。空白水样加标回收率为73.6%～119%,相对标准偏差为6.1%～13.9%,精密度和准确度良好。对成分不复杂的实际水样进行测定,加标回收率为64.1%～118%,相对标准偏差为5.8%～15.6%,该方法能够基本满足成分不复杂的环境水体中痕量硝基氯苯类化合物的测定。     

Factors associated with driving under the influence of alcohol

Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.

Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).

Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.

Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy.     

Occurrence,sorption, and transformation of free and conjugated natural steroid estrogens in the environment

Environmental Science and Pollution Research - Natural steroid estrogens (NSEs), including free estrogens (FEs) and conjugated estrogens (CEs), are of emerging concern globally among public and...     

基于有序Logit与Probit模型的交通事故严重性影响因素分析

为准确分析影响交通事故严重性的各项因素,引入有序选择模型中的Ordinal Logit模型和Ordinal Probit模型,研究驾驶员、车辆、环境、管理因素与事故严重程度之间的耦合关系,利用计量经济学理论和统计学方法对模型进行显著性检验。并选择美国北卡罗来纳州2010年至2014年385个翻车事故样本进行严重性影响因素分析,所得回归模型参数估计均符合Wald检验(p≤0.0001)和似然比检验(p≤0.0001),模型的拟合度也都符合Pearson检验(p=0.7976)、偏差检验(p=0.6006)和信息准则检验,模型预测精度指标值均大于0.7。所得两个模型中变量"安全带"(p≤0.001)、"路面状况"(p=0.0071)、"道路线形"(p=0.0077)、"路面类型"(p=0.0251)都对翻车事故的严重性具有显著影响,表明有序Logit模型和有序Probit模型均适用于分析和揭示影响交通事故严重性的各个因素。