Single Pollution Source Research Articles

Oxidative Stress Effects of Multiple Pollutants in an Indoor Environment on Human Bronchial Epithelial Cells

Benzene, toluene, and xylene (denoted as BTX) are normally used in coatings, sealants, curing agents and other home decoration products, which can cause harm to human health. However, traditional studies mostly focus on the toxicity evaluation of a single pollution source, and little attention has been paid to the toxicity reports of multiple pollutants in a complex system. To evaluate the impact of indoor BTX on human health at the cellular level, the oxidative stress effect of BTX on human bronchial epithelial cells was assessed, including cell cytotoxicity, intracellular ROS, cell mitochondrial membrane potential, cell apoptosis, and CYP2E1 expression. The concentrations of BTX introduced into the human bronchial epithelial cell culture medium were determined based on both the tested distribution in 143 newly decorated rooms and the limited concentrations in the indoor air quality (denoted as IAQ) standards. Our study showed that the concentration in line with the standard limit may still pose a serious risk to health. The cellular biology effect studies of BTX showed that BTX, even at concentrations lower than the national standard limit, can still induce observable oxidative stress effects which warrant attention.

Characteristics of soil pollution and element migration associated with the use of coal in Hutou Village, Yunnan Province, China

This study aimed to reveal the status and source apportionment of trace element soil pollution in a village with a relatively high incidence of lung cancer in China and determine the element migration characteristics from coal to road dust and soil. To this end, 24 soil samples, 48 road dust samples (from a previous study), and 2 coal samples were collected; major element oxides, V, Cr, Co, Ni, Cu, Zn, Zr, Cd, and rare earth elements were analyzed; minerals were identified by SEM-EDX and XRD; a geoaccumulation index (Igeo), Spearman’s correlation analysis, provenance index (PI) and positive matrix factorization (PMF) were carried out to assess the status and source apportionment of soil pollution; and mineralogical and geochemical methods were used for provenance discrimination and migration characteristics identification. The results demonstrated that (1) the Cd and Cr pollution of the soil was severe and originated mainly from indigenous zinc smelting, agricultural activities, and the use of coal. (2) The pollution migrated from Yantang coal to the road dust to the soil through mineralogical and geochemical methods. (3) A stronger fractionation of light and heavy rare earth elements was observed in the soil than in the road dust, indicating a single pollution source in the road dust and a complex source in the soil. (4) The primary reason for the lower rare earth element values in the road dust could be physical separation by the wind.

Introduction of IoT-Based Surrogate Parameters in the Ex-Post Countermeasure of Industrial Sectors in Integrated Permit Policy

New approaches and techniques are required for environmental management in workplaces that emit pollutants. The best available techniques (BATs) that are suggested by the integrated environmental permit system (IEPS) play a pivotal role in providing state-of-the-art approaches and techniques to workplaces. For the workplaces that install facilities with the BATs, it is necessary to perform real-time monitoring to determine whether pollutant emission facilities and treatment facilities are operating normally and whether such facilities can maintain the optimal condition during the emission of pollutants. The environmental management measures used before the IEPS had limitations for workplaces that are subjected to integrated environmental management because they consider the entire workplace as a single pollution source by combining all media. In addition, only the emission concentrations and amounts of pollutants were monitored because only the points at which most pollutants are discharged, i.e., stacks for air pollutant emission facilities and final effluent outlets for water pollutant emission facilities, are monitored. These monitoring approaches in a variety of facilities involve considerable costs, and most of them (95% for stacks in workplaces under IEPS, Korea) cannot perform real-time observation even though some of them are capable of it (5% for stacks managed by Tele Monitoring System, TMS). In this study, the applicability of a wireless sensor monitoring network was examined as a new approach for environmental management in workplaces. Based on the sensor monitoring network, surrogate parameters that can indirectly monitor the critical operating factors of pollutant emission and prevention facilities were developed and then measured in real time to examine the status of these facilities. Surrogate parameters can be used instead of directly measuring pollutants as the former has high efficiency, such as cost reduction, and can provide reliable data on the emission characteristics of pollutants. The wireless network is based on an Internet of Things (IoT) platform under real-time conditions in the emission and production facilities in a workplace. This study suggested that a wireless network using the IoT platform improves the BAT assessment methodology to understand the efficiency of environmental pollution reduction and the economic contribution to the workplace.

A three-dimensional and multi-source integrated technology system for controlling rural non-point source pollution in the Three Gorges Reservoir Area, China

Techniques for controlling rural non-point source pollution (RNSP) represent cleaner production techniques that can provide an effective guarantee for regional sustainable development. The majority of studies on RNSP control technologies are mainly aimed at handling only a single pollution source. However, such studies are difficult to perform in rural areas, which have dense populations, complex terrains and extreme climates, such as the Three Gorges Reservoir Area (TGRA), China. Therefore, this paper focuses on the application of the RNSP control technologies based on the following four aspects: crop planting, livestock production, domestic inputs and water-level-fluctuating (WLF) zone. Based on the unique topography, land features and planting patterns of the TGRA, a three-dimensional (3D) and multi-source integrated technology system for controlling RNSP was established according to the principle of source reduction, runoff regulation, and nitrogen (N) and phosphorus (P) loss control. From the results of the long-term observations, the risk of RNSP has been significantly reduced in the study area. The nutrient capacity of the soil increased by 9–15%, while the chemical fertilizer application reduced by 30–50%. The loss of sediment, N and P were reduced by 60–80%, 30–70% and 50–90% in the sloping land at the backslope, respectively, by 30–60%, 70–90%, and 70–90% in the paddy field at the footslope, respectively, and by 75–90%, 30–50%, 65–95% in the WLF zone, respectively. The average removal rates of COD, NH3-N and TN in sewage in the residential area were higher than 82%, 87% and 63.3%, respectively. Overall, more than 90% of RNSP was reduced by using this 3D and multi-source technology system, and it can be widely promoted for controlling RNSP in similar ecological areas with support from local governments by implementing effective measures, such as strengthening environmental protection education and government subsidies.

Study on ventilation performance of lateral exhaust hood under the influence of two high-temperature buoyant jets

Two high-temperature buoyant jets widely exist during the pouring process of molten metal. The lateral exhaust hood is usually used to capture contaminated airflow considering production process. However, the current flow ratio design method for the lateral exhaust hood is in consideration of a single pollution source. In this study, the applicability of the current flow ratio design method for controlling two high-temperature buoyant jets is analyzed. And the performance of lateral exhaust hood influenced by these two buoyant jets is investigated through model experiment and numerical simulation. Investigated factors are distances between two high-temperature buoyant jets, initial velocity ratios, and initial temperature ratios. The results show that the maximum capture efficiency is less than 60% when the optimal exhaust flow rate for controlling the single-buoyant jet is doubled to control the two buoyant jets. Besides, with the distance ratio between the two buoyant jets increasing to 0.75, the two jets merge into one jet. Then, compared with that when the velocity ratio is 0.4, the dimensionless installation height of the lateral exhaust hood should be increased by about 0.04 when the velocity ratio is 1.0 and by about 0.12 when the velocity ratio is 1.4. Finally, with the temperature ratio increasing, the lateral exhaust hood flowrate should be increased to improve the capture efficiency instead of exhaust hood installation heights. In summary, the obtained conclusions could help develop high-efficiency ventilation systems and reduce the energy consumption of the industrial buildings.

Method of Traceability of Pollution Source by Machine Learning

In terms of traceability of pollutant sources, traditional methods are not only time-consuming and labour-intensive, but also difficult to accurately locate pollution sources. This paper applies the particle swarm optimization algorithm (PSO) and genetic algorithm (GA) to identifying a single pollution source and two pollution sources, respectively. The results show that the position of pollution sources can be located well by the method of PSO and GA.

The impacts of viaduct settings and street aspect ratios on personal intake fraction in three-dimensional urban-like geometries

High vehicular pollutants exposure to residents in near-road buildings raises special concerns in micro-scale urban science, as it causes severe health problems for those residents. This paper integrates a new parameter, i.e. personal intake fraction (IF_p), into computational fluid dynamics (CFD) simulations to investigate the flow and the resulted personal exposure of two-phase pollutants (CO and particular matters) in three-dimensional (3D) urban-like models. The impacts of street aspect ratios (building height/street width H/W = 0.5–1.5), viaduct settings, noise barriers and pollutant source locations were considered.3D downward helical flows exist in the secondary streets perpendicular to the parallel approaching wind, which produces lateral pollutant transport across the interface between the main street and secondary streets. Therefore, the overall average IF_p (<IF_p>) of CO (∼0.23–0.59 ppm) in our current 3D urban models (H/W = 1) is much smaller than that in two-dimensional (2D) street canyon (∼3.25–5.21 ppm) models. Although narrower 2D street canyons usually present greater <IF_p>, our current 3D urban models do not show this monotone decreasing trend due to the complicated flow structures. <IF_p> of fine particles are always smaller than that of CO. Furthermore, if a single pollutant source is placed on the viaduct, <IF_p> become much smaller than that in cases with a single ground-level source. If the source location changes to the upstream secondary street, <IF_p> significantly decreases due to stronger local wind. Finally, <IF_p> of leeward-side cases usually exceeds that of windward-side cases by several times, but with viaduct settings, this leeward-to-windward ratio significantly decreases.

The impact of environmental regulation on fetal health: Evidence from the shutdown of a coal-fired power plant located upwind of New Jersey

Our study examines a case where cross-border air pollution had not been effectively dealt with by a decentralized, state level policymaking, letting a coal-fired power plant located on the border between two states pollute the downwind state for years without being controlled. We find that the shutdown of the power plant, thanks to a landmark ruling by the federal government, reduces the likelihoods of having a low birth weight baby and having a preterm birth by 15 percent and 28 percent, respectively, in areas downwind of the power plant. The ruling marks the first-ever federal level regulation under the Clean Air Act that overrides state-level regulations and is directly imposed upon a single pollution source. Our empirical setting emphasizes the importance of such regulation in curbing environmental free riding induced by jurisdictional borders, where pollution cost-shifting can be aided by natural forces such as prevailing winds.

RBF Neural Network-Based Prediction and Inverse Calculation of Air Pollutant Emission Concentration

The arrangement of the sensors in the air pollutant distribution space was designed by segmented array. A data prediction model for RBF neural network was created. Other air pollution data at the unknown positions were predicted by the data measured by the arranged sensors in order to reduce the sensor arrangement cost. According to the measured values and the predicted data, Gaussian plume diffusion model for air pollution was created, and the quadratic optimization model and inversion method for inverse calculation of single pollution source and multi pollution source were built. Single pollution source and double pollution source was inversely optimized by three different intelligent optimized algorithms in experimental simulation in order to obtain the accurate information on pollution sources. The validity of this method was verified so as to provide a reference for subsequent research.

Seasonal impact of regional outdoor biomass burning on air pollution in three Indian cities: Delhi, Bengaluru, and Pune

Air pollution in many of India's cities exceeds national and international standards, and effective pollution control strategies require knowledge of the sources that contribute to air pollution and their spatiotemporal variability. In this study, we examine the influence of a single pollution source, outdoor biomass burning, on particulate matter (PM) concentrations, surface visibility, and aerosol optical depth (AOD) from 2007 to 2013 in three of the most populous Indian cities. We define the upwind regions, or “airsheds,” for the cities by using atmospheric back trajectories from the HYSPLIT model. Using satellite fire radiative power (FRP) observations as a measure of fire activity, we target pre-monsoon and post-monsoon fires upwind of the Delhi National Capital Region and pre-monsoon fires surrounding Bengaluru and Pune. We find varying contributions of outdoor fires to different air quality metrics. For the post-monsoon burning season, we find that a subset of local meteorological variables (air temperature, humidity, sea level pressure, wind speed and direction) and FRP as the only pollution source explained 39% of variance in Delhi station PM10 anomalies, 77% in visibility, and 30% in satellite AOD; additionally, per unit increase in FRP within the daily airshed (1000 MW), PM10 increases by 16.34 μg m−3, visibility decreases by 0.155 km, and satellite AOD increases by 0.07. In contrast, for the pre-monsoon burning season, we find less significant contributions from FRP to air quality in all three cities. Further, we attribute 99% of FRP from post-monsoon outdoor fires within Delhi's average airshed to agricultural burning. Our work suggests that although outdoor fires are not the dominant air pollution source in India throughout the year, post-monsoon fires contribute substantially to regional air pollution and high levels of population exposure around Delhi. During 3-day blocks of extreme PM2.5 in the 2013 post-monsoon burning season, which coincided with statistically significant high fire activity, concentrations in Delhi averaged 304 μg m−3, or more than 1000% above the 24-h PM2.5 guideline (25 μg m−3) of the World Health Organization. These results suggest that providing viable alternatives to agricultural residue burning could help improve post-monsoon air quality for a growing population of 63 million (39% in urban areas) within Delhi's airshed.

Inverse identification of multiple temporal sources releasing the same tracer gaseous pollutant

When an accidental release of indoor airborne pollutants occurs, it is critical to promptly identify the pollutant sources. Current inverse models concentrate on the identification of a single pollutant source or multiple pollutant sources in a simplified puff or constant release scenarios. This investigation proposes an inverse model to precisely determine the locations and temporal release rate profiles of multiple sources releasing the same tracer gaseous pollutant. The model first constitutes a number of candidate group sources by assuming known release positions. Then Tikhonov-based matrix inversion is implemented to solve for the release rate profiles of each candidate group of sources. The concentrations provided by the sensors in the same number of the isolated sources are the known inputs for the matrix inversion. As for the multiple candidate group sources, the occurrence probability of each group is determined by the Bayesian model after matching the concentration with one additional sensor. The above strategy was applied to identify the same pollutant accidentally released by two passengers in a three-dimensional aircraft cabin. The pollutant was from the exhalation points and discharged in an intermittent sinusoidal wave and a square wave of ten seconds, respectively. The results show that the proposed method can correctly determine the locations of multiple temporally released sources. The relative errors between the inversely identified release rates and the CFD-simulated actual rates are generally less than 15%.

Pollutant source identification model for water pollution incidents in small straight rivers based on genetic algorithm

Identification of pollutant sources for river pollution incidents is an important and difficult task in the emergency rescue, and an intelligent optimization method can effectively compensate for the weakness of traditional methods. An intelligent model for pollutant source identification has been established using the basic genetic algorithm (BGA) as an optimization search tool and applying an analytic solution formula of one-dimensional unsteady water quality equation to construct the objective function. Experimental tests show that the identification model is effective and efficient: the model can accurately figure out the pollutant amounts or positions no matter single pollution source or multiple sources. Especially when the population size of BGA is set as 10, the computing results are sound agree with analytic results for a single source amount and position identification, the relative errors are no more than 5 %. For cases of multi-point sources and multi-variable, there are some errors in computing results for the reasons that there exist many possible combinations of the pollution sources. But, with the help of previous experience to narrow the search scope, the relative errors of the identification results are less than 5 %, which proves the established source identification model can be used to direct emergency responses.

Inverse identification of the release location, temporal rates, and sensor alarming time of an airborne pollutant source.

With an accidental release of an airborne pollutant, it is always critical to know where, when, and how the pollutant has been released. Then, emergency measures can be scientifically advised to prevent any possible harm. This investigation proposes an inverse model to identify the release location, the temporal rate profile, and the sensor alarming time from the start of a pollutant release. The first step is to implement the inverse operation to the cause-effect matrix to obtain the release rate profiles for discrete candidate scenarios with concentration information provided by one sensor. The second step is to interpret the occurrence probability of each solution in the first step with the Bayesian model by matching the concentration at the other sensor. The proposed model was applied to identify a single pollutant source in a two-dimensional enclosure using measurement data and in a three-dimensional aircraft cabin with simulated data. The results show that the model is able to correctly determine the pollutant source location, the temporal rate profile, and the sensor alarming time. The known conditions for input into the inverse model include a steady flow field and the valid temporal concentrations at two different locations. The proposed inverse model can tell where, when, and how a gaseous pollutant has been accidently released based on the monitoring concentrations measured by two sensors. This methodology can be useful for providing emergency protection to indoor occupants.

Magnetic properties of urban soils from typical oasis cities and their environmental implications

This study is a systematic analysis on the environmental magnetic properties, soil texture and distribution of heavy metals content in topsoil sampled from typical oasis cities in desert like Wuhai, Shizuishan and Yinchuan. The results indicated that the topsoil in Wuhai and Shizuishan is typical sandy soil, while that in Yinchuan is sandy loam. Magnetic properties of topsoil samples are all predominated by ferrimagnetic magnetic mineral (magnetite) of coarse pseudo single domain (PSD)-multi domain (MD) particles with magnetic susceptibility of 152 X 10(-8), 104X10(-8), and 117x10(-8)m(3).kg(-1) respectively for the three cities. The magnetic mineral content and magnetic particles size in topsoil samples of Wuhai are significantly higher than that of Shizuishan and Yinchuan. Pollution Load Index (PLI) of heavy metals (Cr, Cu, Pb, Zn, Fe) showed that there is slight pollution in the three cities. Dotted distribution of high values of magnetic susceptibility and Pollution Load Index is shown in nonindustrial area, whilst planar distribution with high value is shown in industrial area. The correlation coefficient between magnetic parameters and heavy metals of topsoil in Wuhai is significantly higher than that in Shizuishan and Yinchuan, which suggests that magnetic parameters are more advantageous for evaluation on pollution degree in regions with single pollution source. There is an increase by the same degree in magnetic susceptibility in parallel with the increase of Pollution Load Index, despite of the significant difference of magnetic properties among three cities. Therefore, magnetic susceptibility can be used as the unified and effective substitute indicator to evaluate the pollution degree of heavy metals in topsoil of Ningxia plain.

Spatial analysis of the risk of multiple cancers in relation to a petrochemical plant

In Environmental Epidemiology studies, the effects of the presence of a source of pollution on the population health can be evaluated by models that consider the distance from the source as a possible risk factor. We introduce a hierarchical Bayesian model in order to investigate the association between the risk of multiple pathologies and the presence of a single pollution source. Our approach provides the possibility to incorporate spatial effects and other confounding factors within a logistic regression model. Spatial effects are decomposed into the sum of a disease‐specific parametric component accounting for the distance from the point source and a common semi‐parametric component that can be interpreted as a residual spatial variation. The model is applied to data from a spatial case–control study to evaluate the association of the incidence of different cancers with the residential location in the neighborhood of a petrochemical plant in the Brindisi area (Italy). Copyright © 2011 John Wiley &amp; Sons, Ltd.

Scale and shape issues in focused cluster power for count data

BackgroundInterest in the development of statistical methods for disease cluster detection has experienced rapid growth in recent years. Evaluations of statistical power provide important information for the selection of an appropriate statistical method in environmentally-related disease cluster investigations. Published power evaluations have not yet addressed the use of models for focused cluster detection and have not fully investigated the issues of disease cluster scale and shape. As meteorological and other factors can impact the dispersion of environmental toxicants, it follows that environmental exposures and associated diseases can be dispersed in a variety of spatial patterns. This study simulates disease clusters in a variety of shapes and scales around a centrally located single pollution source. We evaluate the power of a range of focused cluster tests and generalized linear models to detect these various cluster shapes and scales for count data.ResultsIn general, the power of hypothesis tests and models to detect focused clusters improved when the test or model included parameters specific to the shape of cluster being examined (i.e. inclusion of a function for direction improved power of models to detect clustering with an angular effect). However, power to detect clusters where the risk peaked and then declined was limited.ConclusionFindings from this investigation show sizeable changes in power according to the scale and shape of the cluster and the test or model applied. These findings demonstrate the importance of selecting a test or model with functions appropriate to detect the spatial pattern of the disease cluster.

Measurements of stable carbon and oxygen isotopic compositions of CO in automobile exhausts and ambient air from semi-urban Mainz, Germany.

Stable isotopic measurements of atmospheric CO (13CO, C18O) were carried out at three season in a middle size city, Mainz in Germany. CO stable isotopic compositions of car exhaust fueled by gasoline, diesel and natural gas were also measured and showed different isotopic compositions (δ18O vs. V-SMOW = 22.3 ± 0.3‰, 10.9 ± 0.8‰, 20.1 ± 1.0‰ and δ13C vs. V-PDB = -29.9 ± 0.3‰, -22.2 ± 1.1‰, -51.3 ± 1.5‰, respectively). The 18O/16O ratios of atmospheric CO in Mainz show a clear linear correlation with the reciprocal concentration of CO. This reveals the contribution of CO emitted from a single pollution source (δ18O = 20.7 ± 0.5‰ V-SMOW), whose isotopic composition is close to that of CO from a gasoline engine combustion. From this value and car exhaust measurements, about 14 ± 7% of CO in Mainz air is estimated to originate from diesel fuel engine combustion. The oxygen isotopic composition can be used as a good indicator of contamination from car exhausts. On the other hand, the 13C/12C ratios of CO do not show a clear relationship with the reciprocal concentration of CO.

Management model of a groundwater system with a transient pollutant source

A management model is presented for determining the maximum concentration of a transient pollutant source such that space‐dependent groundwater quality requirements are met. The method is illustrated using a one‐dimensional groundwater system with a single pollutant source at an adjacent stream. The chloride concentration of the source is to be managed to meet variable groundwater quality constraints. Management of the pollutant source is demonstrated for a single‐period as well as for repeated‐period pollutant discharges. The Crank‐Nicolson numerical approximation of the convective‐dispersive equation is used in the management model. The pollutant source concentration is treated as a parameter in the resulting system of linear equations. Taking advantage of the block structure of the matrix, the concentrations throughout the system are defined and manipulated as functions of this parameter for each time step. The parameter is maximized by comparison of groundwater quality limits with the groundwater solute concentrations at the corresponding nodes. The minimum value of the parameter over the entire time frame is the maximum concentration allowable in the source water over the management period or periods.