Source apportionment of PM2.5 at two receptor sites in Brisbane, Australia

2011 ◽  
Vol 8 (6) ◽  
pp. 569 ◽  
Author(s):  
Adrian J. Friend ◽  
Godwin A. Ayoko ◽  
Eduard Stelcer ◽  
David Cohen
Keyword(s):  
Air Quality ◽  
Fine Particles ◽  
Function Analysis ◽  
Control Strategies ◽  
Motor Vehicles ◽  
The South ◽  
Receptor Sites ◽  
Reduction Strategies ◽  
Study Sites ◽  
Conditional Probability Function

Environmental contextFine particles affect air quality locally, regionally and globally. Determining the sources of fine particle is therefore critical for developing strategies to reduce their adverse effects. Advanced data analysis techniques were used to determine the sources of fine particles at two sites, providing information for future pollution reduction strategies not only at the study sites but in other areas of the world as well. AbstractIn this study, samples of particulate matter with aerodynamic diameter less than 2.5 µm (PM2.5) collected at two sites in the south-east Queensland region, a suburban (Rocklea) and a roadside site (South Brisbane), were analysed for H, Na, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Br, Pb and black carbon (BC). Samples were collected during 2007–10 at the Rocklea site and 2009–10 at the South Brisbane site. The receptor model Positive Matrix Factorisation was used to analyse the samples. The sources identified included secondary sulfate, motor vehicles, soil, sea salt and biomass burning. Conditional probability function analysis was used to determine the most likely directions of the sources. Future air quality control strategies may focus on the particular sources identified in the analysis.

scholarly journals Prediction of PM2.5 concentrations in Malaysia using machine learning techniques: a review

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 1279
Author(s):  
Naveen Palanichamy ◽  
Su-Cheng Haw ◽  
Subramanian S ◽  
Kuhaneswaran Govindasamy ◽  
Rishanti Murugan
Keyword(s):  
Machine Learning ◽  
Air Quality ◽  
Fine Particles ◽  
Smart Cities ◽  
Control Strategies ◽  
Air Pollutant ◽  
Machine Learning Techniques ◽  
Motor Vehicles ◽  
Pollutant Concentrations ◽  
Haze Pollution

Particulate matter (PM), an air pollutant that is detrimental to breathing, is either emitted or formed ambiently. The exposure of respiratory system towards PM2.5, the fine particles of 2.5 micrometres diameter, causes complication for health. Thus, developing pollution control strategies requires the prediction of PM2.5 concentrations. Advancement of technology and computer science knowledge, machine learning (ML) algorithms are used for highly accurate prediction of air pollutant concentrations. Recently, air quality in Smart Cities of Malaysia has been getting worse due to industrialization, emissions from private motor vehicles, and transboundary haze pollution. Therefore, the forecasting of PM2.5 emissions to ensure they are within the statutory limits becomes necessary. Several machine learning methods have been implemented in existing research to predict air pollution concentrations in comparison to PM2.5. However, very few studies have used ML techniques to predict air quality in Malaysia when compared with global studies. Hence, to create awareness on the ML techniques and promote further research in this area, this study reviews and highlights most of the existing ML techniques for the prediction of PM2.5.

scholarly journals Future-Year Ozone Isopleths for South Coast, San Joaquin Valley, and Maryland

Atmosphere ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 354 ◽  
Author(s):  
Susan Collet ◽  
Toru Kidokoro ◽  
Prakash Karamchandani ◽  
Tejas Shah
Keyword(s):  
Air Quality ◽  
Quality Management ◽  
Control Strategies ◽  
Ambient Air ◽  
The United States ◽  
Quality Standard ◽  
San Joaquin Valley ◽  
South Coast ◽  
Air Quality Management ◽  
The South

Many areas of the United States are working toward achieving the 2015 ozone National Ambient Air Quality Standard (NAAQS) attainment level. The objective of this study was to develop future-year (2030) volatile organic compounds and nitrogen oxides (VOC-NOx) isopleth diagrams of the 4th highest maximum daily 8-h average ozone design value concentrations at monitors of interest in the South Coast Air Basin (SoCAB) and San Joaquin Valley (SJV) in California, and in Maryland. The simulation results showed there would be attainment of the 2015 ozone NAAQS in 2030 without further controls at the selected monitors: 27% in SoCAB, 57% in SJV, and 100% in Maryland. The SoCAB ozone isopleths developed in this study were compared with those reported in the South Coast Air Quality Management District 2016 Air Quality Management Plan. There are several differences between the two modeling studies, the results are qualitatively similar for most of the monitors in the relative amounts of additional emission reductions needed to achieve the ozone NAAQS. The results of this study provide insight into designing potential control strategies for ozone attainment in future years for areas currently in non-attainment. Additional photochemical modeling using these strategies can then provide confirmation of the effectiveness of the controls.

scholarly journals Seropositivity to canine tick-borne pathogens in a population of sick dogs in Italy

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Jairo Alfonso Mendoza-Roldan ◽  
Giovanni Benelli ◽  
Marcos Antonio Bezerra-Santos ◽  
Viet-Linh Nguyen ◽  
Giuseppe Conte ◽  
...  
Keyword(s):  
Borrelia Burgdorferi ◽  
Serological Test ◽  
Control Strategies ◽  
Central Italy ◽  
Rickettsia Conorii ◽  
High Seroprevalence ◽  
The South ◽  
Serum Samples ◽  
Serological Tests ◽  
Distribution Maps

Abstract Background Canine vector-borne diseases (CVBDs) associated to ticks are among the most important health issues affecting dogs. In Italy, Ehrlichia canis, Anaplasma spp., Rickettsia conorii and Borrelia burgdorferi (s.l.) have been studied in both healthy canine populations and those clinically ill with suspected CVBDs. However, little information is currently available on the overall prevalence and distribution of these pathogens in the country. The aim of this study was to assess the prevalence and distribution of tick-borne pathogens (TBPs) in clinically suspect dogs from three Italian macro areas during a 15-year period (2006–2020). Methods A large dataset (n = 21,992) of serological test results for selected TBPs in three macro areas in Italy was analysed using a Chi-square test to evaluate the associations between the categorical factors (i.e. macro area, region, year, sex and age) and a standard logistic regression model (significance set at P = 0.05). Serological data were presented as annual and cumulative prevalence, and distribution maps of cumulative positive cases for TBPs were generated. Results Of the tested serum samples, 86.9% originated from northern (43.9%) and central (43%) Italy. The majority of the tests was requested for the diagnosis of E. canis (47%; n = 10,334), followed by Rickettsia spp. (35.1%; n = 7725), B. burgdorferi (s.l.) (11.6%; n = 2560) and Anaplasma spp. (6.2%; n = 1373). The highest serological exposure was recorded for B. burgdorferi (s.l.) (83.5%), followed by Rickettsia spp. (64.9%), Anaplasma spp. (39.8%) and E. canis (28.7%). The highest number of cumulative cases of Borrelia burgdorferi (s.l.) was recorded in samples from Tuscany, central Italy. Rickettsia spp. was more prevalent in the south and on the islands, particularly in dogs on Sicily older than 6 years, whereas Anaplasma spp. was more prevalent in the north and E. canis more prevalent in the south and on the islands. Conclusions The results of this study highlight the high seroprevalence and wide distribution of the four TBPs in dogs with clinically suspected CVBDs from the studied regions of Italy. The very high seroprevalence of B. burgdorferi (s.l.) exemplifies a limitation of this study, given the use of clinically suspect dogs and the possibility of cross-reactions when using serological tests. The present research provides updated and illustrative information on the seroprevalence and distribution of four key TBPs, and advocates for integrative control strategies for their prevention. Grapic abstract

scholarly journals Effectiveness of SOx, NOx, and Primary Particulate Matter Control Strategies in the Improvement of Ambient PM Concentration in Taiwan

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 460
Author(s):  
Jiun-Horng Tsai ◽  
Ming-Ye Lee ◽  
Hung-Lung Chiang
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Model Simulation ◽  
Control Strategies ◽  
Ambient Air ◽  
Clean Air Act ◽  
Control Measures ◽  
Control Plan ◽  
Clean Air ◽  
Pm2.5 Concentration

The Community Multiscale Air Quality (CMAQ) measurement was employed for evaluating the effectiveness of fine particulate matter control strategies in Taiwan. There are three scenarios as follows: (I) the 2014 baseline year emission, (II) 2020 emissions reduced via the Clean Air Act (CAA), and (III) other emissions reduced stringently via the Clean Air Act. Based on the Taiwan Emission Data System (TEDs) 8.1, established in 2014, the emission of particulate matter 2.5 (PM2.5) was 73.5 thousand tons y−1, that of SOx was 121.3 thousand tons y−1, and that of NOx was 404.4 thousand tons y−1 in Taiwan. The CMAQ model simulation indicated that the PM2.5 concentration was 21.9 μg m−3. This could be underestimated by 24% in comparison with data from the ambient air quality monitoring stations of the Taiwan Environmental Protection Administration (TEPA). The results of the simulation of the PM2.5 concentration showed high PM2.5 concentrations in central and southwestern Taiwan, especially in Taichung and Kaohsiung. Compared to scenario I, the average annual concentrations of PM2.5 for scenario II and scenario III showed reductions of 20.1% and 28.8%, respectively. From the results derived from the simulation, it can be seen that control of NOx emissions may improve daily airborne PM2.5 concentrations in Taiwan significantly and control of directly emitted PM2.5 emissions may improve airborne PM2.5 concentrations each month. Nevertheless, the results reveal that the preliminary control plan could not achievethe air quality standard. Therefore, the efficacy and effectiveness of the control measures must be considered to better reduce emissions in the future.

To what extent does the environmental magnetism technique acts as a way of assessing the uptake of atmospheric particles by plants?

2021 ◽  
Author(s):  
Sarah Letaïef ◽  
Pierre Camps ◽  
Thierry Poidras ◽  
Patrick Nicol ◽  
Delphine Bosch ◽  
...  
Keyword(s):  
Air Quality ◽  
Endemic Species ◽  
Fine Particles ◽  
Magnetic Measurements ◽  
Deposition Velocity ◽  
Environmental Magnetism ◽  
Air Pollutant ◽  
Atmospheric Pollutants ◽  
Area Index ◽  
The Impact

<p>Numerous studies have already shown the possibility of tracing the sources, the<br>compositions, and the concentration of atmospheric pollutants deposited on plant<br>leaves. In environmental geochemistry, inter-element and isotope ratios from<br>chemical element assays have been used for these purposes. Alternatively,<br>environmental magnetism represents a quick and inexpensive asset that is<br>increasingly used as a relative indicator for concentrations of air pollutant on bio<br>accumulator surfaces such as plants. However, a fundamental issue is still pending:<br>Do plants in urban areas represent a sink for fine particles that is sufficiently effective<br>to improve air quality? This is a very topical issue because some studies have shown<br>that the foliage can trap fine particles by different dry deposition processes, while<br>other studies based on CFD models indicate that plant hedges in cities can hinder<br>the atmospheric dispersion of pollutants and therefore increase pollution at the level of<br>emission sources such as traffic. To date, no consensus was made because several<br>factors not necessary well known must be taken into account, such as, PM<br>concentration and size, prevailing wind, surface structures, epicuticular wax, to<br>mention just a few examples. A first step toward the understanding of the impact of<br>urban greens on air quality is the precise determination of the deposition velocity (Vd)<br>parameter. This latter is specific for each species and it is most of the time<br>underestimated in modeling-based studies by taking standard values.<br>In that perspective, we built a wind tunnel (6 m long, 86 cm wide and 86 cm high) to<br>perform analogical experiments on different endemic species. All parameters are<br>controlled, i.e, the wind speed, the nature and the injection time of pollutants (Gasoline<br>or Diesel exhausts, brakes or tires dust, etc…). We can provide the PM concentrations<br>upwind and downwind of natural reconstituted hedges by two dustmeters (LOACs -<br>MétéoModem). Beforehand, parameters such as the hedge resistance (%) or the leaf<br>area index (LAI) have been estimated for each studied specie to allow comparability<br>between plants removal potential. The interest would ultimately combine PM<br>concentration measured by size bins from the LOACs with magnetic measurements<br>(ARM, IRM100mT, IRM300mT and SIRM) of plant leaves. The idea is to check whether it<br>would be possible to precisely determine in situ the dust removal rate by urban greens<br>with environmental magnetism measurements. Up to now, we have carried out on<br>different endemic species such as Elaeagnus x ebbingei leaves and Mediterranean<br>pine needles, the results of which will be presented.</p>

scholarly journals Does afforestation deteriorate haze pollution in Beijing–Tianjin–Hebei (BTH), China?

2018 ◽  
Author(s):  
Xin Long ◽  
Naifang Bei ◽  
Jiarui Wu ◽  
Xia Li ◽  
Tian Feng ◽  
...  
Keyword(s):  
Forest Cover ◽  
Fine Particles ◽  
Control Strategies ◽  
Surface Wind ◽  
Forecast Model ◽  
Surface Wind Speed ◽  
Satellite Measurements ◽  
Haze Pollution ◽  
The Impact

Abstract. Although aggressive emission control strategies have been implemented recently in the Beijing–Tianjin–Hebei area (BTH), China, pervasive and persistent haze still frequently engulfs the region during wintertime. Afforestation in BTH, primarily concentrated in the Taihang and Yanshan Mountains, has constituted one of the controversial factors exacerbating the haze pollution due to its slowdown of the surface wind speed. We report here an increasing trend of forest cover in BTH during 2001–2013 based on long-term satellite measurements and the impact of the afforestation on the fine particles (PM2.5) level. Simulations using the Weather Research and Forecast model with chemistry reveal that the afforestation in BTH since 2001 generally deteriorates the haze pollution in BTH to some degree, enhancing PM2.5 concentrations by up to 6 % on average. Complete afforestation or deforestation in the Taihang and Yanshan Mountains would increase or decrease the PM2.5 level within 15 % in BTH. Our model results also suggest that implementing a large ventilation corridor system would not be effective or beneficial to mitigate the haze pollution in Beijing.

Air Quality Modeling and Decisions for Ozone Reduction Strategies

2005 ◽  
Vol 55 (10) ◽  
pp. 1558-1573 ◽  
Author(s):  
Philip M. Roth ◽  
Steven D. Reynolds ◽  
Thomas W. Tesche
Keyword(s):  
Air Quality ◽  
Air Quality Modeling ◽  
Quality Modeling ◽  
Reduction Strategies

scholarly journals Ambient Particulate Matter Air Pollution in Mpererwe District, Kampala, Uganda: A Pilot Study

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Stephan Schwander ◽  
Clement D. Okello ◽  
Juergen Freers ◽  
Judith C. Chow ◽  
John G. Watson ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Pilot Study ◽  
Fine Particles ◽  
Airborne Particulate Matter ◽  
Personal Exposure ◽  
Ambient Air ◽  
Combustion Products ◽  
Carbonaceous Aerosol ◽  
Coarse Particles

Air quality in Kampala, the capital of Uganda, has deteriorated significantly in the past two decades. We made spot measurements in Mpererwe district for airborne particulate matter PM2.5(fine particles) and coarse particles. PM was collected on Teflon-membrane filters and analyzed for mass, 51 elements, 3 anions, and 5 cations. Both fine and coarse particle concentrations were above 100 µg/m3in all the samples collected. Markers for crustal/soil (e.g., Si and Al) were the most abundant in the PM2.5fraction, followed by primary combustion products from biomass burning and incinerator emissions (e.g., K and Cl). Over 90% of the measured PM2.5mass can be explained by crustal species (41% and 59%) and carbonaceous aerosol (33%–55%). Crustal elements dominated the coarse particles collected from Kampala. The results of this pilot study are indicative of unhealthy air and suggest that exposure to ambient air in Kampala may increase the burden of environmentally induced cardiovascular, metabolic, and respiratory diseases including infections. Greater awareness and more extensive research are required to confirm our findings, to identify personal exposure and pollution sources, and to develop air quality management plans and policies to protect public health.

Sources of fine particles in the South Coast area, California

2010 ◽  
Vol 44 (26) ◽  
pp. 3095-3100 ◽  
Author(s):  
Eugene Kim ◽  
Katarzyna Turkiewicz ◽  
Sylvia A. Zulawnick ◽  
Karen L. Magliano
Keyword(s):  
Fine Particles ◽  
South Coast ◽  
The South
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