The land carrying capacity and environmental risk assessment of livestock and poultry breeding considering crop planting

Environmental Science and Pollution Research - At present, the contradiction between survival and ecology necessitates the integration of crop planting, chemical fertilizer application, and...     

Research progress and hot spots of hydrothermal liquefaction for bio-oil production based on bibliometric analysis

Environmental Science and Pollution Research - Hydrothermal liquefaction (HTL) of biomass used HTL reaction under high temperature and pressure to produce bio-oil. This technology is considered as...     

武汉地区夏季和秋冬季大气污染的天气概念模型

利用2013～2019年武汉市生态环境局监测数据、L波段雷达探空资料、NCEP/NCAR逐日再分析资料,对夏季和秋冬季武汉地区污染日的大气污染特征、边界层结构、环流形势、物理量场进行研究,建立了武汉地区大气污染的天气概念模型.主要结论如下:(1)武汉市空气质量具有季节性变化特征,大气污染程度四季分布表现为冬＞秋＞春＞夏.夏季首要污染物是臭氧,冬季首要污染物是PM2.5.(2)比较挑选出的夏季清洁日和污染日的气象要素特征,污染日逆温的平均强度约为清洁日的一倍,逆温底高一般在600 m以下,空气质量一般为轻度-中度污染;静风频率(37.1％)明显高于清洁日的静风频率(2.9％);污染日平均风速小(0.8 m/s),边界层内相对湿度较低.同样比较秋冬季两类天气的气象要素特征,污染日逆温底高低、厚度小,不及清洁日的一半,不利于污染物的扩散,易出现重度污染天气.静风频率(20％)高于清洁日的静风频率(7.5％),风速小(1.6 m/s),污染日边界层内呈明显上千下湿的格局.(3)建立了夏季大气污染的天气概念模型,污染日副高偏弱位置偏东,长江流域易少雨干旱;地面我国东部大范围地区处于均压场中,武汉地区为偏东北异常小风,不利于大气污染物的扩散.(4)建立了秋冬季大气污染的天气概念模型,长江流域环流平直少波动,配合地面弱低压的天气形势和较强的逆温使得大气污染物聚集在近地面.蒙古冷高压强度偏弱,使得入侵我国的冷空气强度偏弱;武汉地区为偏北小风,对雾霾的移除和稀释扩散作用差.该研究结论可供大气污染预测预警研究和环境管理部门大气污染的联防联控参考.     

Magnetic graphene-based nanocomposites as highly efficient absorbents for Cr(VI) removal from wastewater

Environmental Science and Pollution Research - Due to the merits of their high adsorption and convenient separation, magnetic graphene-based composites have become a promising adsorbent in terms of...     

AI-based runoff simulation based on remote sensing observations: A case study of two river basins in the United States and Canada

Data-driven techniques are used extensively for hydrologic time-series prediction. We created various data-driven models (DDMs) based on machine learning: long short-term memory (LSTM), support vector regression (SVR), extreme learning machines, and an artificial neural network with backpropagation, to define the optimal approach to predicting streamflow time series in the Carson River (California, USA) and Montmorency (Canada) catchments. The moderate resolution imaging spectroradiometer (MODIS) snow-coverage dataset was applied to improve the streamflow estimate. In addition to the DDMs, the conceptual snowmelt runoff model was applied to simulate and forecast daily streamflow. The four main predictor variables, namely snow-coverage (S-C), precipitation (P), maximum temperature (T_max), and minimum temperature (T_min), and their corresponding values for each river basin, were obtained from National Climatic Data Center and National Snow and Ice Data Center to develop the model. The most relevant predictor variable was chosen using the support vector machine-recursive feature elimination feature selection approach. The results show that incorporating the MODIS snow-coverage dataset improves the models' prediction accuracies in the snowmelt-dominated basin. SVR and LSTM exhibited the best performances (root mean square error = 8.63 and 9.80) using monthly and daily snowmelt time series, respectively. In summary, machine learning is a reliable method to forecast runoff as it can be employed in global climate forecasts that require high-volume data processing.     

Mechanism of complexation of toxic arsenate,selenate, and molybdate with hydrotalcites

Environmental Chemistry Letters - Wastewater from the uranium mining industry contains toxic arsenate (AsO43–), selenate (SeO42–), and molybdate (MoO42–) that can be removed by...     

Characterization of the incipient smoke point for steam-/air-assisted and nonassisted flares

Flares are important safety devices for pressure relief; at the same time, flares are a significant point source for soot and highly reactive volatile organic compounds (HRVOCs). Currently, simple guidelines for flare operations to maintain high combustion efficiency (CE) remain elusive. This paper fills the gap by investigating the characteristics of the incipient smoke point (ISP), which is widely recognized as the condition for good combustion. This study characterizes the ISP in terms of 100–% combustion inefficiency (CE), percent opacity, absorbance, air assist, steam assist, air equivalence ratio, steam equivalence ratio, exit velocity, vent gas net heating value, and combustion zone net heating value. Flame lengths were calculated for buoyant and momentum-dominated plumes under calm and windy conditions at stable and neutral atmosphere. Opacity was calculated using the Beer–Lambert law based on soot concentration, flame diameter, and mass-specific extinction cross section of soot. The calculated opacity and absorbance were found to be lognormally distributed. Linear relations were established for soot yield versus absorptivity with R² > 0.99 and power-law relations for opacity versus soot emission rate with R² ≥ 0.97 for steam-assisted, air-assisted, and nonassisted flares. The characterized steam/air assists, combustion zone/vent gas heating values, exit velocity, steam, and air equivalence ratios for the incipient smoke point will serve as a useful guideline for efficient flare operations.

Implications: A Recent EPA rule requires an evaluation of visible emissions in terms of opacity in compliance with the standards. In this paper, visible emissions such as soot particles are characterized in terms of opacity at ISP. Since ISP is widely recognized as most efficient flare operation for high combustion efficiency (CE)/destruction efficiency (DE) with initial soot particles formed in the flame, this characterization provides a useful guideline for flare operators in the refinery, oil and gas, and chemical industries to sustain smokeless and high combustion efficiency flaring in compliance with recent EPA regulations, in addition to protecting the environment.     

Effects of intercropping with floricultural accumulator plants on cadmium accumulation in grapevine

Environmental Science and Pollution Research - Grapevine (Vitis vinifera L.) intercropping with floricultural cadmium (Cd) accumulator plants (Helianthus annuus L., Cosmos sulphureus Cav., Cosmos...     

Numerical model of aerobic bioreactor landfill considering aerobic-anaerobic condition and bio-stable zone development

Environmental Science and Pollution Research - Aeration by airflow technology is a reliable method to accelerate waste biodegradation and stabilization and hence shorten the aftercare period of a...     

Probabilistic health risk assessment of nitrosamines in drinking water of Shaoxing,Zhejiang, China

Environmental Science and Pollution Research - Nitrosamines (NAms) are potent genotoxic and carcinogenic but widely detected in drinking water. This study aimed to investigate the occurrence of...