Detecting Trends Using Spearman's Rank Correlation Coefficient

Spearman's rank correlation coefficient is a useful tool for exploratory data analysis in environmental forensic investigations. In this application it is used to detect monotonic trends in chemical concentration with time or space.     

Evidence of aircraft activity impact on local air quality: A study in the context of uncommon airport operation

Wuhan Tianhe International Airport (WUH) was suspended to contain the spread of COVID-19, while Shanghai Hongqiao International Airport (SHA) saw a tremendous flight reduction. Closure of a major international airport is extremely rare and thus represents a unique opportunity to straightforwardly observe the impact of airport emissions on local air quality. In this study, a series of statistical tools were applied to analyze the variations in air pollutant levels in the vicinity of WUH and SHA. The results of bivariate polar plots show that airport SHA and WUH are a major source of nitrogen oxides. NO_x, NO₂ and NO diminished by 55.8%, 44.1%, 76.9%, and 40.4%, 33.3% and 59.4% during the COVID-19 lockdown compared to those in the same period of 2018 and 2019, under a reduction in aircraft activities by 58.6% and 61.4%. The concentration of NO₂, SO₂ and PM_2.5 decreased by 77.3%, 8.2%, 29.5%, right after the closure of airport WUH on 23 January 2020. The average concentrations of NO, NO₂ and NO_x scatter plots at downwind of SHA after the lockdown were 78.0%, 47.9%, 57.4% and 62.3%, 34.8%, 41.8% lower than those during the same period in 2018 and 2019. However, a significant increase in O₃ levels by 50.0% and 25.9% at WUH and SHA was observed, respectively. These results evidently show decreased nitrogen oxides concentrations in the airport vicinity due to reduced aircraft activities, while amplified O₃ pollution due to a lower titration by NO under strong reduction in NO_x emissions.     

Differences in physical properties and CO2 gasification reactivity between coal char and petroleum coke

This paper mainly investigated the physical properties and gasification reactivity of coal char and petroleum coke, separately at the high temperature pyrolysis (950–1400 °C) with slow heating rate and pyrolysis pressure of the atmospheric pressure and at the pressurized pyrolysis (the atmospheric pressure to 3 MPa) with rapid heating rate and the pyrolysis temperature of 950 °C. Some significant differences in those between coal chars and petroleum coke were found. The high temperature pyrolysis caused more easily the graphitization of petroleum coke than that of coal char, especially in the higher temperature range. The increasing pyrolysis temperature resulted in the decrease of surface areas of coal char and the increase of surface areas of petroleum coke. As the pyrolysis pressure was elevated from the atmospheric pressure to 3 MPa, surface areas of petroleum coke initially increased and then decreased, while those of coal chars presented an opposite tendency. The increasing pyrolysis temperature was adverse to the gasification activity of coal chars and was favorable for the gasification activity of petroleum coke. Also, the effects of the pyrolysis pressure on the gasification activity of coal char and petroleum coke were significantly different. The gasification activity of petroleum coke was obviously lower than that of coal chars, and even lower than that of the natural graphite.     

Data fusion modeling for groundwater systems

Engineering projects involving hydrogeology are faced with uncertainties because the earth is heterogeneous, and typical data sets are fragmented and disparate. In theory, predictions provided by computer simulations using calibrated models constrained by geological boundaries provide answers to support management decisions, and geostatistical methods quantify safety margins. In practice, current methods are limited by the data types and models that can be included, computational demands, or simplifying assumptions. Data Fusion Modeling (DFM) removes many of the limitations and is capable of providing data integration and model calibration with quantified uncertainty for a variety of hydrological, geological, and geophysical data types and models. The benefits of DFM for waste management, water supply, and geotechnical applications are savings in time and cost through the ability to produce visual models that fill in missing data and predictive numerical models to aid management optimization. DFM has the ability to update field-scale models in real time using PC or workstation systems and is ideally suited for parallel processing implementation. DFM is a spatial state estimation and system identification methodology that uses three sources of information: measured data, physical laws, and statistical models for uncertainty in spatial heterogeneities. What is new in DFM is the solution of the causality problem in the data assimilation Kalman filter methods to achieve computational practicality. The Kalman filter is generalized by introducing information filter methods due to Bierman coupled with a Markov random field representation for spatial variation. A Bayesian penalty function is implemented with Gauss–Newton methods. This leads to a computational problem similar to numerical simulation of the partial differential equations (PDEs) of groundwater. In fact, extensions of PDE solver ideas to break down computations over space form the computational heart of DFM. State estimates and uncertainties can be computed for heterogeneous hydraulic conductivity fields in multiple geological layers from the usually sparse hydraulic conductivity data and the often more plentiful head data. Further, a system identification theory has been derived based on statistical likelihood principles. A maximum likelihood theory is provided to estimate statistical parameters such as Markov model parameters that determine the geostatistical variogram. Field-scale application of DFM at the DOE Savannah River Site is presented and compared with manual calibration. DFM calibration runs converge in less than 1 h on a Pentium Pro PC for a 3D model with more than 15,000 nodes. Run time is approximately linear with the number of nodes. Furthermore, conditional simulation is used to quantify the statistical variability in model predictions such as contaminant breakthrough curves.     

Description and evaluation of a model of deposition velocities for routine estimates of air pollutant dry deposition over North America.: Part I: model development

This paper describes the development of a detailed dry deposition model for routine computation of dry deposition velocities of SO₂, O₃, HNO₃ and fine particle SO₄²⁻ across much of North America. Four different dry deposition/surface exchange sub-models have been combined with the current Canadian weather forecast model (Global Environmental Multiscale model) with a 3 h time resolution and a horizontal spatial resolution of 35 km. The present model uses the US Geological Survey North American Land Cover Characteristics data to obtain fourteen different land use and five seasonal categories. The four sub-models used are a multi-layer model for gaseous species over taller canopy land-use types, a big-leaf model for gaseous species over lower canopies (including bare soil and water) and for HNO₃ under all surface types and, two different models for SO₄²⁻, one for tall canopies and the other for short canopies. All necessary parameters for each sub-model, chemical species, land-use and seasonal categories have been selected from available data libraries or from the values reported in the literature. The purpose for developing this model (referred to as the Routine Deposition Model (RDM)), when coupled with air concentration data, is to provide estimates of seasonal dry deposition, which can be combined with wet deposition to produce total deposition estimates. Model theory is discussed in this paper and model sensitivity tests and results will be presented in a companion paper.     

Regulating groundwater use: The challenges of policy implementation in Guanajuato,Central Mexico

Around the world it has proven very difficult to develop policies and interventions that ensure socio-environmentally sustainable groundwater use and exploitation. In the state of Guanajuato, Central Mexico, both the national government and the decentralized state government have pursued to regulate groundwater use through direct state control, groundwater markets, energy pricing, and user self-regulation. We present and analyze these regulatory mechanisms and their outcomes in the field. We argue that the close interdependencies of these regulatory mechanisms have pre-empted the effectiveness of these policy instruments as well as that of other measures aimed at reducing groundwater use in order to advance towards sustainable exploitation levels.     

Organic contaminants in sediments and mussels from Thermaikos gulf,Greece

Thirteen surficial sediment samples, two sediment cores and mussels (Mytilus galloprovincialis) from six locations were collected from Thermaikos gulf, Greece and analyzed for herbicides, organochlorine compounds and aliphatic hydrocarbons. Herbicide concentrations were low in surface sediments (not detected‐0.8 ng/g dry wt) and undetectable in subsurface samples. Organochlorine concentrations ranged between 0.8 and 88.2 ng/g dry wt for the polychlorinated biphenyls (PCBs) and between 1.7 and 22.8 ng/g dry wt for the SDDTs, while aliphatic hydrocarbon values varied from 28.8 to 965.4 ng/g dry wt. The highest concentrations for all the pollutants were measured in the vicinity of the city of Thessaloniki. Petroleum‐related hydrocarbons were dominant in surface sediments, while were still detected till about 1 m depth in the sediment core. Mussels presented low organochlorine concentrations (3.6–10.5 ng/g dry wt for the PCBs, 12.2–34.0 ng/g dry wt for the DDTs), but petroleum hydrocarbon concentrations were rather increased, mainly in the samples collected along the east coastline of the gulf (aliphatic hydrocarbons 52.3–224.3 μg/g dry wt).     

GC × GC--A New Analytical Tool For Environmental Forensics

Comprehensive two-dimensional gas chromatography, GC 2 GC, is a new analytical tool with a tremendous capability to separate and identify organic compounds in complex environmental samples. GC 2 GC uses two different chromatography columns coupled serially by a modulator to produce a volatility by polarity separation and distribute compound peaks across a two-dimensional retention time plane. The two-dimensional separation produces an order of magnitude more resolved peaks than traditional GC methods. The grouping or ordering of the peaks in the GC 2 GC chromatogram facilitates the identification of unknown compounds and the comparison of complex environmental samples. When a mass spectrometer detector is used, each resolved GC 2 GC peak yields a single-component, interference-free mass spectrum that leads to accurate matching with mass spectral libraries. GC 2 GC examination of marine sediment extracts identified a wide variety of chemical contaminants including polychlorinated biphenyls, p -nonylphenol isomers, polycyclic aromatic hydrocarbons, benzotriazoles, and the alkane, cycloalkane, alkylbenzene, alkylnaphthalene, and biomarker fractions of petroleum. The two-dimensional GC 2 GC chromatogram image permits rapid screening of the sediment extracts for these and other unknown contaminants.     

淮南—蚌埠段淮河流域沉积物中PAHs的分布及来源辨析

采用GC-MS对淮南至蚌埠段淮河流域水源地、支流及排污口采集沉积物中18种多环芳烃(PAHs)进行定量分析.结果表明,研究区水源地及其支流沉积物中PAHs含量范围为308.12～1090.37ng/g;排污口沉积物PAHs范围为1308.36～8793.16ng/g.沉积物PAHs组成以3～4环PAHs为主,5～6环PAHs相对较少.相对于TOC,BC与沉积物总PAHs的含量相关性更好.PAHs组成特征、主成分分析及多特征比值揭示淮南至蚌埠段淮河流域沉积物PAHs主要来源于化石燃料的不完全燃烧,还有少量石油类产品的输入.生态风险评价结果显示,研究区沉积物中多数PAHs化合物已超出ER-L值和ISQV-L值,而姚家湾排污口沉积物PAHs部分化合物已超出ER-H值和ISQV-H值,表明沉积物中的PAHs对研究区环境已造成了极大的生态风险.     

几种植物根亚细胞中菲的分配

以菲为多环芳烃(PAHs)代表物,采用温室水培试验方法,研究了黑麦草、苏丹草、墨西哥玉米、高羊茅、三叶草等5种植物根亚细胞中菲的分配作用.结果表明,经144h培养,随着培养液中菲平衡浓度由0.056mg·L-1增至0.39mg·L-1,黑麦草根、细胞壁、细胞器中菲的含量分别从26.85、20.01和36.19mg·kg-1增大到56.91、49.54和59.77mg·kg-1,富集系数则分别由357.14、479.49和649.25L·kg-1降低到145.92、127.04和153.26L·kg-1.黑麦草根及亚细胞组分中菲的含量大小为细胞器根细胞壁,其中细胞器中菲含量要比细胞壁高21%～163%.水中菲的起始浓度均为1mg·L-1时,144h后,供试5种植物根细胞器中菲的含量(48.64～145.2mg·kg-1)均大于细胞壁(15.86～74.49mg·L-1).5种植物根亚细胞中菲分配的比例大小顺序为细胞器细胞壁可溶部分;其中,根内46%～53%和31%～40%的菲分别分布在细胞器和细胞壁中.