Local Pollution Sources Research Articles

Real-Time Synchronous 3-D Detection of Air Pollution and Wind Using a Solo Coherent Doppler Wind Lidar

The monitoring and tracking of urban air pollution is a challenging environmental issue. The approach of synchronous 3-D detection of wind and pollution using a solo coherent Doppler wind lidar (CDWL) is developed and demonstrated. The 3-D distribution of pollutant is depicted by the backscatter coefficient based on signal intensity of CDWL. Then, a high-resolution wind field is derived to track the local air pollution source with its diffusion and to analyze transboundary air pollution episodes. The approach is experimentally implemented in a chemical industry park. Smoke plumes caused by point source pollutions are captured well using plan position indicator (PPI) scanning with low elevation. A typical source of pollution is located, combining the trajectory of the smoke plume and the horizontal wind vector. In addition, transboundary air pollution caused by the transport of dust storms is detected in a vertical profile scanning pattern, which is consistent with the results of national monitoring stations and backward trajectory models. Our present work provides a significant 3-D detection approach to air pollution monitoring with its sources, paths, and heights by using a solo-CDWL system.

Application of synthetic data to establish the working framework for multivariate statistical analysis of river pollution traceability - the heavy metals in Nankan River, Taiwan.

This study applied multivariate statistical analysis (MSA) to synthetic data simulated by a river water quality model to verify whether the MSA can correctly infer the pollution scenario assigned in the river water quality model. The results showed that when assessing the number and possible locations of pollution sources based on the results of cluster analysis (CA), two instead of three pollution point source were identified when considering the hydraulic variations of surface water. When discussing the principal component analysis (PCA) result, the second principal component (PC2) and the Pearson correlation coefficients among the pollutants should also be considered, which can infer that Cu, Pb, Cr, and Ni are contributed by the same pollutant point source, and Cu is also influenced by another pollutant point source. This result also implies that the solid and liquid partition coefficients (Kd) of pollutants can affect the interpretation of the PCA results, so the Kd values should be determined before tracing the pollution sources to facilitate the evaluation of the source characteristics and potential targets. This study established a working framework for surface water pollution traceability to enhance the effectiveness of pollution traceability.

An innovative framework for real-time monitoring of pollutant point sources in river networks

Simultaneous identification of the location and release history of pollutant sources in river networks is an ill-posed and complicated problem, particularly in the case of multiple sources with time-varying release patterns. This study presents an innovative method for solving this problem using minimum observational data. To do so, a procedure is proposed in which, the number and the suspected reaches to the existence of pollutant sources are determined. This is done by defining two different types of monitoring stations with an adaptive arrangement in addition to real-time data collection and reliable flow and transport mathematical models. In the next step, the sources’ location and their release history are identified by solving the inverse source problem employing a geostatistical approach. Different scenarios are discussed for different conditions of number, release history and location of pollutant sources in the river network. Results indicated the capability of the proposed method in identifying the characteristics of the sources in complicated cases. Hence, it can be effectively used for the comprehensive monitoring of river networks for different purposes.

Online non-convex learning for river pollution source identification

In this article, novel gradient-based online learning algorithms are developed to investigate an important environmental application: real-time river pollution source identification, which aims at estimating the released mass, location, and time of a river pollution source based on downstream sensor data monitoring the pollution concentration. The pollution is assumed to be instantaneously released once. The problem can be formulated as a non-convex loss minimization problem in statistical learning, and our online algorithms have vectorized and adaptive step sizes to ensure high estimation accuracy in three dimensions which have different magnitudes. In order to keep the algorithm from sticking in the saddle points of non-convex loss, the “escaping from saddle points” module and multi-start setting are derived to further improve the estimation accuracy by searching for the global minimizer of the loss functions. This can be shown theoretically and experimentally as the O(N) local regret of the algorithms and the high probability cumulative regret bound O(N) under a particular error bound condition in loss functions. A real-life river pollution source identification example shows the superior performance of our algorithms compared with existing methods in terms of estimation accuracy. Managerial insights for the decision maker to use the algorithms are also provided.

Accurate Identification of Pollution Sources in a Chemical Enterprise Based on a Distributed Multi-channel VOCs Online Monitoring Mass Spectrometry System

A monitoring and traceability management system for unorganized emissions of volatile organic compounds (VOCs) in industrial parks has been established. This system uses distributed multi-channel mass spectrometry to continuously monitor multiple online monitoring points within the enterprise and the factory boundary to initially identify the source of unorganized emissions of VOCs. Based on online monitoring data, the system combined a positive matrix factorization (PMF) model and conditional bivariate probability function (CBPF) methods to accurately identify pollution sources of different scales in the park. The system was successfully applied to a pharmaceutical chemical factory in Taizhou Chemical Industry Park, and VOCs online monitoring was carried out for more than three months at 10 monitoring sites in the factory area. The sources of VOCs were analyzed using the PMF model, and the geographical location information of each pollution source factor was identified by the CBPF method. During the monitoring period, the contribution of chlorobenzene emissions and the number of early warnings were much higher than those of other species. Compared with that of other species, the frequency of abnormal emissions of butene was higher, and the frequency of abnormal emissions of toluene was lower. Among the top ten species, only chlorobenzene had significant concentration changes in different monitoring sites. Ambient VOCs in the plant mainly came from six sources:butene emission, toluene emission, chlorobenzene emission, solvent use, sulfur-related processes, and industrial production. Based on the CBPF results of each pollution source factor relative to the ten monitoring stations, the local pollution source and external pollution source in the plant were distinguished, and the specific location of the local pollution source and the transmission direction of the external pollution source were identified.

TREE LITTER PRODUCTION AND DECOMPOSITION IN FOREST ECOSYSTEMS UNDER BACKGROUND CONDITIONS AND INDUSTRIAL AIR POLLUTION

The paper provides an overview of Russian and foreign articles devoted to the study of the tree litter production and decomposition in forest ecosystems subjected to natural and anthropogenic factors. The spatial variability (below crown and between crown spaces) and the seasonal features of the tree litter production, its chemical composition, and decomposition processes are poorly studied. In addition, most of the works, both in Russia and foreign countries science, highlight the influence of natural factors on the litter production and the processes of its decomposition, while the impact of local sources of industrial air pollution is rarely considered. The study of the variability of the size, fractional and chemical composition and processes of decomposition of tree litter under conditions of industrial air pollution is important for predicting the dynamics of forest ecosystems subjected to the combined action of natural and anthropogenic factors and reducing the negative impact of production processes on forests.

Microplastics in intertidal water of South Australia and the mussel Mytilus spp.; the contrasting effect of population on concentration

Microplastics, plastic particles <5 mm in size, are of global concern as human-caused pollutants in marine and fresh waters, and yet little is known of their distribution, behaviour and ecological impact in the intertidal environment of South Australia. This study confirms for the first time, the presence of microplastic in the South Australian intertidal ecosystem by quantifying the abundance of particles in intertidal water and in the keystone species, the blue mussel, Mytilus spp., an important fisheries species, at ten and six locations respectively, along the South Australian coastline. For a remote region known for its pristine environment, microplastic concentration in intertidal water was found to be low to moderate (mean = 8.21 particles l−1 ± 4.91) relative to global levels and microplastic abundance in mussels (mean = 3.58 ± 8.18 particles individual−1) was within the range also reported globally. Microplastic particles were ubiquitous across sites and bioavailable by size in water (mean = 906.36 μm) and in mussel (mean = 983.29 μm) raising concerns for the health of South Australia's unique coastal ecosystems and for the human food chain. Furthermore, a positive correlation was found between human coastal population size and microplastic concentration in intertidal water, irrespective of influences from industry - tourism, fishing and shipping ports. FTIR analysis determined plastic type to include polyamide (PA), polyethylene (PE), polypropylene (PP), acrylic resin, polyethyleneterephthalate (PET) and cellulose, suggesting synthetic and semi-synthetic particles from single-use, short-life cycle products, fabrics, ropes and cordage. Our findings shed light on the urgent need to establish the local sources of microplastic pollution in order to assist the community, industry and government to reduce the impact of microplastic on the fragile marine systems within South Australian intertidal waters and on the organisms associated with the human food chain.

Air pollution and CO2 from daily mobility: Who emits and Why? Evidence from Paris

Urban road transport is an important source of local pollution and carbon emissions. Designing effective and fair policies tackling these externalities requires understanding who contributes to emissions today. We estimate individual transport-induced pollution footprints combining a travel demand survey from the Paris area with NOx, PM2.5 and CO2 emission factors. We find that the top 20% emitters contribute 75%–85% of emissions on a representative weekday. They combine longer distances travelled, a high car modal share and, especially for local pollutants, a higher emission intensity of car trips. Living in the suburbs, being a man and being employed are the most important characteristics associated with top emissions. Among the employed, those commuting from suburbs to suburbs, working at a factory, with atypical working hours or with a manual, shopkeeping or top executive occupation are more likely to be top emitters. Finally, policies targeting local pollution may be more regressive than those targeting CO2 emissions, due to the different correlation between income and the local pollutant vs. CO2 emission intensity of car trips.

Classification of aerosol-cloud interaction regimes over Tokyo

Previous studies on the aerosol indirect effect have demonstrated that there are three regimes (aerosol-limited, updraft-limited, and transitional regimes). However, this classification of regimes has not been widely used in field observations as it requires measurements of updraft or supersaturation near the cloud base (Smax), which are not easy to perform. In this study, we attempted to classify the regimes using the effective supersaturation (Seff) which is relatively easy to estimate by matching cloud droplet number concentration (Nc) and supersaturation spectra of cloud condensation nuclei. Parcel model simulations were performed to examine the suitability of Seff as a proxy for Smax. Further, 35 low-level cloud cases observed around 458 m over Tokyo were classified into three regimes. In the aerosol-limited regime, Nc increased more rapidly with an increment of aerosols than in the other two regimes, indicating that the regime classification using Seff was sufficiently robust. The aerosol-limited regime in Tokyo appeared frequently when northerly winds prevailed, indicating the impact of local pollution sources around Tokyo on the aerosol cloud interaction. The results imply that anthropogenic aerosol emissions affect the climate of Tokyo.

Atmospheric levels, distribution, sources, correlation with meteorological parameters and other pollutants and health risk of PAHs bound in PM2.5 and PM10 in Burgas, Bulgaria – a case study

The quality of atmospheric air of Burgas city, Bulgaria was analyzed in relation to PAHs in two particulate matter fractions – 2.5 μm and 10 μm. It was found that PAHs registered in PM10 represent entirely the ones registered in PM2.5 – an indication that the particulate PAHs in ambient air of Burgas for the sampling period are associated with the fine PM fraction. The PAH compounds with highest concentrations are mainly associated with coal combustion, diesel and gasoline vehicle and biomass burning, which is further confirmed by the calculated diagnostic ratios. The combustion-derived PAHs represent on average 86.6 ± 2.8% of total PAHs concentration. The linear regression analysis showed strong and statistically meaningful correlations between PM fractions and PAHs indicating the influence of similar local events and emission sources of pollution. PM2.5 or PM10 relationships with PAHs were significant but lower correlation coefficients were observed for low-molecular weight (LMW) PAHs in comparison to middle-molecular weight (MMW) and higher-molecular weight (HMW) PAHs, due to their lower presence in particulates and higher partition in gaseous atmospheric phase. Further significant correlations were found with wind speed, solar radiation and atmospheric pressure as well as NO2 and O3 ambient concentration. The calculated excess cancer risks are twice as much as acceptable limit.

Pilot study on the concentrations of organochlorine compounds and potentially toxic elements in pregnant women and local food items from the Finnish Lapland

In the Arctic, main sources of persistent organic pollutants and potentially toxic elements are industry and agriculture in the lower latitudes. However, there are also local sources of pollution. Our study was focused on possible pollution in the Finnish Lapland, transferred from the Pechenganikel industrial complex located in the borders of Russia, Finland and Norway.Local food items and blood samples of pregnant women from the Inari municipality were collected and organochlorine compounds (OCs) and metal(oid)s analyzed. Most of the examined food samples showed detectable levels of these compounds. The mean concentrations of DDTs and polychlorobiphenyls (PCBs) were higher in fish (0.18–0.32 ng/g and 0.34–0.64 ng/g, respectively), than in the other food groups (0.027–0.047 ng/g and 0.11–0.20 ng/g, respectively).PCBs were found at the highest concentrations in blood samples of the pregnant women, and congeners 153 and 118 were dominant. The mean concentration of PCB153, 0.29 μg/kg serum lipid, was lower than those described in many other studies. Concerning DDTs, the 4,4′-DDT/4,4′-DDE ratio, 0.092, in the blood samples was lower than that observed in the food items, 0.25–0.71, reflecting old uses of the DDT pesticide. None of the observed levels of selected potentially toxic elements in blood samples and in food items exceeded the known safe limits.Higher concentrations of PCB52 and γ-HCH were observed in the serum of pregnant women who consumed greater amounts of meat, and berries and mushrooms, respectively. The OC concentrations from the pregnant women currently studied were lower than those observed fourteen years ago with pregnant women from the same municipality. Compounds whose occurrence is likely related to a long-distance transport showed clear decreases, e.g., 63% for PCBs, and for those from pesticides, decreases were 93% and 97% for 4,4′-DDE and β-HCH, respectively. No obvious influence from the Pechenganikel complex is observed from the results.

Mapping the emission of air pollution sources based on land-use classification: A case study of Shengzhou, China

At-source pollutant control is an effective way to systematically address the environmental problems associated with air pollution. The spatial scale of China’s environmental management is often at the province or city level, which makes precise governance difficult. Taking Shengzhou, China, as an example, this study defines the control unit (CU) as the spatial location of a anthropogenic pollution source based on land-use classification. For each CU, the pollution behaviours of sulphur dioxide (SO2), nitrogen oxides (NOx), particulate matter with a diameter of < 2.5 µm (PM2.5) and ammonia (NH3) are identified, and the emission factor methods and the entropy weight method are then used to calculate a single and comprehensive pollution emissions figure. The results show that the CUs in Shengzhou can be divided into 14 types. Combining these types with the characteristics of air pollutant emissions, seven main pollution behaviours are identified. The comprehensive characteristic value (CCV) of air-mixed pollutants is between 0.0 and 2.11, and all CUs can be classified into five levels on the basis of their CCV as follows: ≥ 1.0, 0.5–1.0, 0.2–0.5, 0.0–0.2 and 0.0. The CUs with CCV ≥ 1.0 are transportation land, high-polluting industrial production site, livestock farm, landfill and sewage treatment plant. The CU reclassification and pollution calculation method proposed in this study follows the three main land-use functions of production, living and ecology and serve as a reference for research in other regions of China and in other countries. Moreover, the spatial units in this study are controlled to the smallest administrative scale in China, which can provide the spatial precision required for the implementation of differentiated environmental policies.

Combination of UNMIX, PMF model and Pb-Zn-Cu isotopic compositions for quantitative source apportionment of heavy metals in suburban agricultural soils

Quantitative identification of heavy metals (HM) sources in soils is key to prevention and control of heavy metal pollution. In this study, UNMIX, PMF (Positive matrix factorization) model and Pb-Zn-Cu isotopic compositions were combined to quantitatively identify heavy metal sources in a suburban agricultural area of Kaifeng, China. Using multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) and ICP-MS, we measured Pb, Zn and Cu stable isotopic compositions, HM concentrations and HM chemical fractions in studied soils, as well as potential sources around the highly polluted site, including total suspended particle, compound fertilizer, irrigated river water and sediments. The results showed that total contents and chemical fractions of heavy metals, as well as Pb-Zn-Cu isotopic compositions presented great variation in different sites, which implied that heavy metal accumulation was obviously affected by local anthropogenic pollution source. UNMIX and PMF presented good agreement on source apportionment that industrial and agricultural activities (61.74% and 60.75% for UNMIX and PMF, respectively) were the major contributors to heavy metal accumulation in the study area. Especially, sewage irrigation and atmosphere deposition accounted for a large proportion (28.14% and 41.03% for UNMIX and PMF, respectively). Moreover, isotopic compositions of Pb, Zn and Cu in highly polluted soils and environment media gave further confirmation that sewage irrigation and atmosphere deposition were primary anthropogenic source. Therefore, combination of UNMIX, PMF model and Pb-Zn-Cu isotopic compositions showed good coordination in quantitative and specific source identification of heavy metals in agricultural soils.

Evaluation of Selected Algorithms for Air Pollution Source Localisation Using Drones

Polluted air causes enormous damage to human health. There is a high demand to find a solution for locating the places of illegal waste incineration due to the persistent smog problem. The use of multi-rotor drones for that purpose has now become one of the important research topics. The aim of the work was to check the possibility of using simple algorithms to search for the source of pollution. The algorithms that require low computing power, which may be part of the robot’s measurement and the control system’s internal software, were considered. The focus was on building a system based on a single robot that independently searches an area of a certain size. The simulation of the accuracy and scalability of the three different search algorithms was analysed for areas up to 200 m × 200 m. Two multi-rotor robots were prepared for the fieldwork. The validation of the two selected algorithms was carried out in outdoor environmental conditions. The fieldwork tests were carried out in areas with a maximum size of 100 m × 100 m. The obtained results were different, in particular on the wind speed and direction and the intensity of the pollution source. The random influence of these factors can verify the operation of the proposed system in practical applications. The difference between the true and the position of the source indicated by the robot was up to 15 m. That difference depended on the mutual arrangement of the measurement points and the pollution source location.

Air Pollution within Different Urban Forms in Manchester, UK

Air pollution causes millions of mortalities and morbidities in large cities. Different mitigation strategies are being investigated to alleviate the negative impacts of different pollutants on people. Designing proper urban forms is one of the least studied strategies. In this paper, we modelled air pollution (NO2 concentration) within four hypothetical neighbourhoods with different urban forms: single, courtyard, linear east-west, and linear north-south scenarios. We used weather and air pollution data of Manchester as one of the cities with high NO2 levels in the UK. Results show that the pollution level is highly dependent on the air temperature and wind speed. Annually, air pollution is higher in cold months (45% more) compared to summer. Likewise, the results show that during a winter day, the concentration of air pollution reduces during the warm hours. Within the four modelled scenarios, the air pollution level in the centre of the linear north-south model is the lowest. The linear building blocks in this scenario reduce the concentration of the polluted air and keep a large area within the domain cleaner than the other scenarios. Understanding the location of air pollution (sources) and the direction of prevailing wind is key to design/plan for a neighbourhood with cleaner air for pedestrians.

PM Dimensional Characterization in an Urban Mediterranean Area: Case Studies on the Separation between Fine and Coarse Atmospheric Aerosol

Fine particulate matter (PM) is object of particular attention due to its health effects. It is currently regulated by adopting PM2.5 as an indicator to control anthropogenic combustion emissions. Therefore, it is crucial to collect aerosol samples representative of such sources, without including PM from natural sources. Thus, a clean separation between coarse and fine mode aerosol should be set. With this purpose, aerosol size mass distribution was taken in the aerodynamic diameter range from 0.5 to 10 µm. In comparison with a base scenario, characterized by local pollution sources, three case studies were considered, involving desert dust advection, sea salt advection and forest fire aerosol from a remote area. In the base scenario, PM2.5 represented a suitable fine-mode indicator, whereas it was considerably affected by coarse PM in case of desert dust and sea salt aerosol advection. Such interference was considerably reduced by setting the fine/coarse separation at 1.0 µm. Such separation underrepresented fine PM from forest fire long-range transport, nonetheless in the case studies considered, PM1 represented the best indicator of fine aerosol since less affected by coarse natural sources. The data presented clearly support the results from other studies associating the health effects of PM2.5 to PM1, rather than to PM1–2.5. Overall, there is a need to reconsider PM2.5 as an indicator of fine atmospheric aerosol.

Analysis of Air Pollution around a CHP Plant: Real Measurements vs. Computer Simulations

This study examines the concentrations of air pollution in the vicinity of a combined heat and power plant (CHP) and a communication route, using computer modeling of pollutant dispersion and spatial analysis based on real measurements in the city of Łódź, Poland, Europe. The research takes into account the concentrations of particulate matter (PM10, PM2.5, PM1.0) and gaseous pollutants (SO2 and VOC) in winter and summer. The spatial distribution of pollutants is discussed, including the presence of areas with increased accumulations of pollutants. Because atmospheric air has no natural boundaries, when analyzing any location, not only local sources of pollution, but also background pollution, should be analyzed. A clear difference was observed between the concentrations of pollutants in the summer and winter seasons, with significantly higher concentrations in the winter (heating) period. The impacts of road transport, individual heating systems, and combined heat and power plants were also assessed. Computer calculations confirmed that road transport accounted for the largest share of both PM and SO2 emissions. The CHP plant was responsible for the smallest percentage of dust emissions and was the next largest producer of SO2 emissions. The share of the total emissions from the individual sources were compared with the results of detailed field tests. The numerical analysis of selected pollution sources in combination with the field analysis shows that the identified pollution sources included in the analysis represent only a part of the total observed pollutant concentrations (suggesting that other background sources account for the rest).

Network-Based Topological Exploration of the Impact of Pollution Sources on Surface Water Bodies

We developed a digital water management toolkit to evaluate the importance of the connections between water bodies and the impacts caused by pollution sources. By representing water bodies in a topological network, the relationship between point loads and basic water quality parameters is examined as a labelled network. The labels are defined based on the classification of the water bodies and pollution sources. The analysis of the topology of the network can provide information on how the possible paths of the surface water network influence the water quality. The extracted information can be used to develop a monitoring- and evidence-based decision support system. The methodological development is presented through the analysis of the physical-chemical parameters of all surface water bodies in Hungary, using the emissions of industrial plants and wastewater treatment plants. Changes in water quality are comprehensively assessed based on the water quality data recorded over the past 10 years. The results illustrate that the developed method can identify critical surface water bodies where the impact of local pollution sources is more significant. One hundred six critical water bodies have been identified, where special attention should be given to water quality improvement.

Organic carbon in atmospheric precipitation in the urbanized territory of the South of Western Siberia, Russia

Abstract This paper presents the results of studying the contents of total (TOC) and dissolved (DOC) organic carbon in atmospheric precipitation and their deposition fluxes on the territory of the city of Barnaul. Samples of atmospheric precipitation (rain and snow) were collected from May 2016 to December 2020 in the city center, additionally at the end of winter 2018–2019 samples of snow cover were taken in the territory of the city and its environs. The studies showed a significant content of organic carbon (OC) in atmospheric precipitation: the weighted average concentrations for the study period were 7.2 ± 0.6 and 4.2 ± 0.4 mg/L for TOC and DOC, respectively. The annual flux of OC deposition with atmospheric precipitation on the territory of Barnaul over the past three years has varied within 2.4–3.9 t/km2 for TOC and 1.4–2.1 t/km2 for DOC. To visualize the spatial distribution of organic matter over the territory of Barnaul, simple kriging was used, implemented in the Geostatistical Analyst module (ArcGIS® Desktop). The flow of organic carbon input into the snow cover during the winter period was used as data for the geostatistical model. According to the model, the deposition of OC from the atmosphere occurs unevenly throughout the urban area and depends on the location and intensity of pollution sources.

Assessment of pollutant elements content in ambient air dust of Khuzestan province

This study aimed to investigate the distribution of natural and anthropogenic pollutants and the enrichment of elements in air dust of Khuzestan province following the dust events. Dust samples were collected from nine regions including, Abadan, Ahvaz, Hoveyzeh, Susangerd, Shush, Omidieh, Ramhormoz, and Mahshahr. The INAA technique measured the concentration of elements. Using the results of PMF modeling and investigation of obtained factors for samples, a suitable reference element with the most negligible influence from pollutant sources was selected and used for EF calculations. The results showed very large enrichments with EF> 20 for elements such as Zn, Se, Br in Susangerd, Ahvaz, and Abadan. The concentrations of Fe, Al, and Mg in some areas of the province were much higher than LC50. The enrichment factors and the correlations between the elements in the samples of various regions showed their dependence on local pollutant sources.