Spatial modeling for air pollution monitoring network design: example of residential woodsmoke

The purpose of this paper is to demonstrate how to develop an air pollution monitoring network to characterize small-area spatial contrasts in ambient air pollution concentrations. Using residential woodburning emissions as our case study, this paper reports on the first three stages of a four-stage protocol to measure, estimate, and validate ambient residential woodsmoke emissions in Vancouver, British Columbia. The first step is to develop an initial winter nighttime woodsmoke emissions surface using inverse-distance weighting of emissions information from consumer woodburning surveys and property assessment data. Second, fireplace density and a compound topographic index based on hydrological flow regimes are used to enhance the emissions surface. Third, the spatial variation of the surface is used in a location-allocation algorithm to design a network of samplers for the woodsmoke tracer compound levoglucosan and fine particulate matter. Measurements at these network sites are then used in the fourth stage of the protocol (not presented here): a mobile sampling campaign aimed at developing a high-resolution surface of woodsmoke concentrations for exposure assignment in health effects studies. Overall the results show that relatively simple data inputs and spatial analysis can be effective in capturing the spatial variability of ambient air pollution emissions and concentrations.     

Spatial and temporal features of density-dependent contaminant transport: Experimental investigation and numerical modeling

We investigate the spatial and temporal features of variable-density contaminant plumes migration in porous materials. Our analysis is supported by novel experimental results concerning concentration profiles inside a vertical column setup that has been conceived at CEA to this aim. The experimental method relies on X-ray spectrometry, which allows determining solute profiles as a function of time at several positions along the column. The salient outcomes of the measurements are elucidated, with focus on miscible fluids in homogeneous saturated media. The role of the injected solution molarity is evidenced. As molarity increases, the solutes plume transport progressively deviates from the usual Fickian behavior, and pollutants distribution becomes skewed in the direction dictated by gravity. By resorting to a finite elements approach, we numerically solve the nonlinear equations that rule the pollutants migration: a good agreement is found between the simulated profiles and the experimental data. At high molarity, a strong dependence on initial conditions is found. Finally, we qualitatively explore the (unstable) interfacial dynamics between the dense contaminant plume and the lighter resident fluid that saturates the column, and detail its evolution for finite-duration contaminant injections.     

Experimental analysis and modeling of a stormwater perlite filter

This paper presents the study of a mixed porous media composed of expanded perlite and a nonwoven needle-punched geotextile used to reduce the suspended solids load and concentration in urban runoff. Laboratory procedures were designed to quantify the suspended solids removal efficiency and variation in time of filtration rate. Different grain-size distributions of expanded perlite, diverse suspended solids concentrations, and different hydraulic and geometric conditions were tested to determine the most effective filter media. A dimensionless parameter, termed Global Performance Index (GPI), was developed to reach this objective. Measured data were also used to build a dimensional and a regression model to represent the performance of the filter media mathematically. The theory, derivation, and performance of both models are presented and compared with an existent empirical model. The dimensional model better reproduces the observations, becoming a useful tool for the design, operation, and evaluation of commercial porous media filters.     

Spatial analysis of extreme precipitation in Sweden 1961-2000

Extreme daily precipitation in Sweden for the years 1961-2000 is analyzed with respect to spatial scale, regional variations and associated weather types. Correlograms based on a lag distance of 30 km estimated the spatial scale of variation of the annual mean precipitation, the 99th percentile of daily precipitation and the average of annual maximum daily precipitation to 100 km, 60-100 km and 40-70 km, respectively. Regions of correlation with respect to precipitation at 82 stations during days of extreme events are identified through Maximum-Likelihood Factor Analysis. Eleven factors are found to provide the optimum factor solution. Weather types for the days of extreme events are determined by an objective classification scheme, based on daily sea level pressure, which is modified by subjective inclusion of fronts. In total, 63% of the extreme events occurred during cyclonic weather types, 32% during frontal, 3% during directional and 2% during anticyclonic types. The frequency of the weather types during extreme events varied between the regions however.     

Multiple regression analysis in modeling of columnar ozone in Peninsular Malaysia

This study aimed to predict monthly columnar ozone (O₃) in Peninsular Malaysia by using data on the concentration of environmental pollutants. Data (2003–2008) on five atmospheric pollutant gases (CO₂, O₃, CH₄, NO₂, and H₂O vapor) retrieved from the satellite Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) were employed to develop a model that predicts columnar ozone through multiple linear regression. In the entire period, the pollutants were highly correlated (R?=?0.811 for the southwest monsoon, R?=?0.803 for the northeast monsoon) with predicted columnar ozone. The results of the validation of columnar ozone with column ozone from SCIAMACHY showed a high correlation coefficient (R?=?0.752–0.802), indicating the model’s accuracy and efficiency. Statistical analysis was utilized to determine the effects of each atmospheric pollutant on columnar ozone. A model that can retrieve columnar ozone in Peninsular Malaysia was developed to provide air quality information. These results are encouraging and accurate and can be used in early warning of the population to comply with air quality standards.     

Current factor analysis receptor models are ill-posed

Current factor models lack sufficient physical constraints to guarantee a unique, physically valid solution; in this sense they are ill-posed. Any realistic factor model must obey certain natural physical constraints, for example, the predicted source contributions and elemental compositions must be non-negative. Five such constraints are given in the paper. As shown by a simple example with only two sources and three elements, these natural constraints are insufficient to define a unique factor model. The same is shown to be true for a more complex example with seven sources and 10 elements. Since the examples use simulated data without observational or other errors, they prove that current factor models are, in general, biased in the statistical sense. The examples also show that the bias, or systematic error, can be very large. Thus, while factor analysis continues to be a valuable screening tool for unexpected sources, in the hands of the inexperienced it could lead to serious errors in source apportionment and derived source compositions.     

Spatial and temporal analysis of the COVID-19 incidence pattern in Iran

Environmental Science and Pollution Research - In the present paper, province-level variations of novel coronavirus (COVID-19) disease incidence across Iran were investigated. To this end, a...     

Spatial analysis of volatile organic compounds in South Philadelphia using passive samplers

Select volatile organic compounds (VOCs) were measured in the vicinity of a petroleum refinery and related operations in South Philadelphia, Pennsylvania, USA, using passive air sampling and laboratory analysis methods. Two-week, time-integrated samplers were deployed at 17 sites, which were aggregated into five site groups of varying distances from the refinery. Benzene, toluene, ethylbenzene, and xylene isomers (BTEX) and styrene concentrations were higher near the refinery’s fenceline than for groups at the refinery’s south edge, mid-distance, and farther removed locations. The near fenceline group was significantly higher than the refinery’s north edge group for benzene and toluene but not for ethylbenzene or xylene isomers; styrene was lower at the near fenceline group versus the north edge group. For BTEX and styrene, the magnitude of estimated differences generally increased when proceeding through groups ever farther away from the petroleum refining. Perchloroethylene results were not suggestive of an influence from refining. These results suggest that emissions from the refinery complex contribute to higher concentrations of BTEX species and styrene in the vicinity of the plant, with this influence declining as distance from the petroleum refining increases.

Implications: Passive sampling methodology for VOCs as discussed here is employed in recently enacted U.S. Environmental Protection Agency Methods 325A/B for determination of benzene concentrations at refinery fenceline locations. Spatial gradients of VOC concentration near the refinery fenceline were discerned in an area containing traffic and other VOC-related sources. Though limited, these findings can be useful in application of the method at such facilities to ascertain source influence.     

Spatial and temporal analysis of pesticides concentrations in surface water: pesticides atlas

Dutch water boards have a well-established program for monitoring pesticide contamination of surface waters. These monitoring data have been processed into a graphic format accessible online and designed to provide insight into pesticide presence in Dutch surface waters and trends over time: the Pesticides Atlas (http://www.pesticidesatlas.nl). With this tool one can easily get maps of where a pesticide is being measured and where it might possibly constitute an environmental problem over the years. Presently, results of the periods 1997/1998 until 2005/2006 are available at the level of individual active ingredients. At a national level, the percentage of pesticides concentrations that exceed the maximum tolerable risk has declined 30% to 38% over the years 2003/2004 compared with 1997/1998. This means that surface water quality in the Netherlands has improved with respect to pesticides, however there are still many locations at which the measured concentrations exceed the environmental quality standards. The results on linking land use to pesticides concentrations were shown to assist in optimization of monitoring programs. By developing the present Internet tool, many new opportunities for environmental risk assessment and risk management were identified, e.g. optimization of monitoring strategies and communication to policymakers.     

Spatial and temporal analysis of pharmaceutical concentrations in the upper Tennessee River basin

The behavior of pharmaceutical compounds in aquatic ecosystems is not well defined. In order to determine spatial and temporal variations in concentrations of pharmaceuticals in the Tennessee River, water samples were collected from multiple points along the river and at the inflow of major tributaries. Sampling structure was designed to investigate trends between surface and subsurface samples, seasonal trends (winter, spring, summer, and fall), the direct influence of sewage treatment plants (upstream versus downstream), and the effect of downstream distance on pharmaceutical concentrations. All samples were quantified via solid phase extraction followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). This method yielded reproducible quantitation at low parts per trillion (ng L(-1)) levels for all 14 analytes (acetaminophen, atorvastatin, caffeine, carbamazepine, ciprofloxacin, diltiazem, fluoxetine, levofloxacin, lovastatin, norfluoxetine, ranitidine, sertraline, sulfamethoxazole, and trimethoprim). Correlation analyses (depth, distance) and repeated-measures ANOVAs (season, sewage treatment plant proximity) were used to determine statistically significant trends for frequently detected pharmaceuticals (caffeine, carbamazepine, sulfamethoxazole). Caffeine and sulfamethoxazole were found to vary by season in subsurface samples; spring exhibited the highest concentrations. Carbamazepine varied in proximity to sewage treatment plant outfall with subsurface samples yielding greater concentrations downstream than upstream. In addition, individual pharmaceuticals displayed positive correlation between surface and subsurface samples and negative correlation with downstream distance from the headwaters.     

基于量纲分析的转载点诱导气流影响因素分析与应用

为解决转载点粉尘污染问题,采用量纲分析法将影响转载点诱导风量的因素进行分类推演,建立转载系统诱导风量计算模型,并搭建转载点诱导气流实验装置,系统分析物料在转载过程中给料量、落料高差、下料管倾角和皮带运行速度等因素对产生诱导气流的影响,拟合得出转载点诱导风量计算模型的数学表达式。结果表明:转载点物料的给料量和落料高差是影响诱导风量的主要因素;对量纲分析所得模型利用实验数据进行拟合所得各参数系数的标准误差优于0.032 1,实验结果与数学模型计算结果误差小于9.48%。该计算模型可用于估算转载点诱导风量大小,为现场的粉尘治理及生产实践提供参考依据。     

Measurement, analysis, and modeling of fine particulate matter in eastern North Carolina

An analysis of fine particulate data in eastern North Carolina was conducted to investigate the impact of the hog industry and its emissions of ammonia into the atmosphere. The fine particulate data are simulated using ISORROPIA, an equilibrium thermodynamic model that simulates the gas and aerosol equilibrium of inorganic atmospheric species. The observational data analyses show that the major constituents of fine particulate matter (PM2.5) are organic carbon, elemental carbon, sulfate, nitrate, and ammonium. The observed PM2.5 concentration is positively correlated with temperature but anticorrelated with wind speed. The correlation between PM2.5 and wind direction at some locations suggests an impact of ammonia emissions from hog facilities on PM2.5 formation. The modeled results are in good agreement with observations, with slightly better agreement at urban sites than at rural sites. The predicted total inorganic particulate matter (PM) concentrations are within 5% of the observed values under conditions with median initial total PM species concentrations, median relative humidity (RH), and median temperature. Ambient conditions with high PM precursor concentrations, low temperature, and high RH appear to favor the formation of secondary PM.     

因子分析及其在河网水质综合评价中的应用研究

对因子分析方法在天然水体水质评价中的应用进行研究,证明在数据较为缺乏的情况下,使用因子分析方法可以损失较少信息,减少评价指标,针对主因子进行分析,使水质评价结果更为合理和有效。同时,利用因子的得分值还可以将不同地区进行比较分析。应用因子分析对河网地区典型河流的水质状况进行分析,发现了增长潜力较大的主要因子,并对该地区的水质状况做出了符合实际的总体评价,表明因子分析在水质评价中具有重要应用价值。     

Integrated factor analysis of water level variation in geographically isolated ponds

Environmental Science and Pollution Research - Small geographically isolated ponds provide a multitude of ecological functions and services, but water table fluctuations alter the magnitude of...     

Management-oriented sensitivity analysis for pesticide transport in watershed-scale water quality modeling using SWAT

The Soil and Water Assessment Tool (SWAT) was calibrated for hydrology conditions in an agricultural watershed of Orestimba Creek, California, and applied to simulate fate and transport of two organophosphate pesticides chlorpyrifos and diazinon. The model showed capability in evaluating pesticide fate and transport processes in agricultural fields and instream network. Management-oriented sensitivity analysis was conducted by applied stochastic SWAT simulations for pesticide distribution. Results of sensitivity analysis identified the governing processes in pesticide outputs as surface runoff, soil erosion, and sedimentation in the study area. By incorporating sensitive parameters in pesticide transport simulation, effects of structural best management practices (BMPs) in improving surface water quality were demonstrated by SWAT modeling. This study also recommends conservation practices designed to reduce field yield and in-stream transport capacity of sediment, such as filter strip, grassed waterway, crop residue management, and tailwater pond to be implemented in the Orestimba Creek watershed.     

工业园区碳排放核算与因素分解实证分析

工业园区贡献了全国过半的工业产值和近31%的碳排放量,是我国应对气候变化实现双碳目标的重要战场,然而当前尚未形成针对工业园区碳排放核算的规范体系。本研究在温室气体清单编制现有方法基础上,构建针对工业园区的碳排放核算体系,并利用此核算体系对重庆市某工业园区2016—2020年碳排放量进行了核算实证研究,且通过LMDI分解模型分析该园区碳排放变动的影响因素。结果表明,该园区在“十三五”期间碳排放呈逐年增长趋势,化石燃料燃烧是园区内最主要的碳排放源,占比达83.5%,化工行业碳排放在该园区所有行业中占比最大 (68.9%) ,园区碳排放的主要驱动因素是能源强度,效应贡献率为64.7%。据此,本研究提出了针对该园区的降碳路径,并通过实证分析后探讨了工业园区碳排放核算方法体系的规范化问题,以期为我国工业园区的碳减排工作提供参考。     

A sensitivity analysis of adsorption and degradation parameters in the modeling of pesticide transport in soils

The increasing use of deterministic models in predicting the movement of pesticides in soils, has focused attention on the evaluation of major parameters which represent attenuation factors of organics in the subsurface. These parameters are the degradation rate constant and the adsorption constant for the pesticide. In view of the large in situ variability of these parameters and of the difficulty in obtaining accurate field data, there is a high degree of uncertainty associated with the results obtained from deterministic models. A sensitivity analysis is performed here to quantify the impact of such variation in each of these input parameters on the output results of an unsaturated zone transport model (PRZM). Results show that variations in these parameters about their respective mean values greatly affect the predicted concentration distributions, obtained after three years, of the pesticide aldicarb in all the soil profile. A 15–22% variation in the degradation constant, or a 24% variation in the adsorption constant, lead to a 100% uncertainty in the various simulation results defined as the cumulative quantity of aldicarb or the dissolved aldicarb concentration leached below the root zone (or the unsaturated zone) of the soil. Such a deterministic model presents a high degree of sensitivity to these input parameters. Accurate field data are then needed to obtain reliable model results in predicting pesticide movement inthe unsaturated zone.     

A sensibility analysis of model selection in modeling the reactive transport of cesium in crushed granite

We performed a sensibility analysis of model selection in modeling the reactive transport of cesium in crushed granite through model calibration and validation. Based on some solid phase analysis data and kinetic batch experimental results, we hypothesized three two-site sorption models in the LEHGC reactive transport model to fit the breakthrough curves (BTCs) from the corresponding column experiments. The analysis of breakthrough curves shows that both the empirical two-site kinetic linear sorption model and the semi-mechanistic/semi-empirical two-site kinetic surface complexation model, regardless of their complexity, can match our experimental data fairly well under given test conditions. A numerical experiment to further compare the two models shows that they behave differently when the pore velocity is not of the same order of magnitude as our test velocities. This result indicates that further investigations to help determine a better model are needed. We suggest that a multistage column experiment, which tests over the whole range of practical flow velocities, should be conducted to help alleviate inadequate hypothesized models.     

Sensitivity analysis of mass balance receptor modeling: Methyl chloride as an indicator of wood smoke

The Singular Value Decomposition (SVD) approach to stability analysis of the Chemical Mass Balance (CMB) receptor model is extended to incorporate uncertainties in both source and ambient compositions. SVD is applied to determine the improved precision with which the impact of residential wood smoke can be estimated by including methyl chloride in a CMB analysis. Wood smoke impacts in Hillsboro and Medford, Oregon, are examined. The results indicate that including methyl chloride will dramatically improve the precision of estimating wood smoke impacts for Medford, while estimates for Hillsboro are changed to a much lesser extent. This result is reasonable since the Medford airshed includes many industrial sources of particulate matter with chemical compositions similar to residential wood smoke, while Hillsboro is predominantly a residential community. The precision improvements estimated by SVD are verified by CMB analysis of a series of ambient samples collected in Hillsboro. Finally, the applicability of SVD as a receptor model study design tool is discussed.