RESUMO
In urban areas, a major source of harmful particulate matter is generated by vehicles. In particular, bus stops, where people often stay for public transportation, generate high concentrations of particulate matter compared to the general atmosphere. In this study, a non-powered type brush filter that generates electrostatic force without using a separate power source was developed to manage the concentration of particulate matter exposed at bus stops, and the removal performance of particulate matter was evaluated. The dust collection performance of the non-motorized brush filter varied by material, with particle removal efficiencies of 82.1 ± 3.4, 76.1 ± 4.7, and 73.7 ± 4.5% for horse hair, nylon, and stainless steel, respectively. In conditions without the fan running to see the effect of airflow, the particle removal efficiency was relatively low at 58.2 ± 8.4, 53.6 ± 9.2, and 58.0 ± 7.3%. Then, to check the dust collection performance according to the density, the number of brushes was increased to densify the density, and the horse hair, nylon, and stainless steel brush filters showed a maximum dust collection performance of 89.6 ± 2.2, 88.3 ± 3.2, and 82.1 ± 3.8%, respectively. To determine the replacement cycle of the non-powered brush filter, the particulate removal performance was initially 88.0 ± 3.2% when five horse hair brushes were used. Over time, particulate matter tended to gradually decrease, but after a period of time, particulate matter tended to increase again. The purpose of this study is to evaluate the particulate matter removal performance using a brush filter that generates electrostatic force without a separate power source. This study's brush filter is expected to solve the maintenance problems caused by the purchase and frequent replacement of expensive HEPA filters that occur with existing abatement devices, and the ozone problems caused by abatement devices that use high voltages.
RESUMO
Lead (Pb) is a heavy metal that negatively affects human health. Many studies have shown the relationship between lead exposure and various human activities, of which automobile service stations with gasoline emissions are considered the main cause. However, a limited number of studies have specifically considered lead exposure from automobile stations in Vietnam, as well as its impact on human activities and the surrounding natural resources. The objective of this study was to assess the possible risks of lead exposure to the surrounding agricultural and non-agricultural farms of a bus station located in the center of Dalat city, Lamdong province, Vietnam. To address this objective, 45 samples were collected from the soil, irrigated water resources, and vegetable crops of areas both close to and far away from the bus station. These samples were tested using the atomic absorption spectrometry technique. Our findings demonstrated higher lead concentration levels from all three types of samples collected from areas near the bus station. Of which, soil and water samples showed higher than normal exposure values of lead, but these were still under the allowed limits established by the Vietnam standard. Different from the soil and water, vegetable samples surrounding the bus station presented greater lead contamination than the permitted limit. High risk quotient (RQ) indexes were detected to point out that accumulative consumption of leaded vegetables over time could cause lead poisoning and harm human health. This study not only provides significant inferential evidence of the risk of lead exposure to agricultural activities and human health in Vietnam, but also delivers a real-life example for a real-world context.
RESUMO
This review clarifies particulate matter (PM) pollution, including its levels, the factors affecting its distribution, and its health effects on passengers waiting at bus stations. The usual factors affecting the characteristics and composition of PM include industrial emissions and meteorological factors (temperature, humidity, wind speed, rain volume) as well as bus-station-related factors such as fuel combustion in vehicles, wear of vehicle components, cigarette smoking, and vehicle flow. Several studies have proven that bus stops can accumulate high PM levels, thereby elevating passengers' exposure to PM while waiting at bus stations, and leading to dire health outcomes such as cardiovascular disease (CVD), respiratory effects, and diabetes. In order to accurately predict PM pollution, an artificial neural network (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) have been developed. ANN is a data modeling method of proven effectiveness in solving complex problems in the fields of alignment, prediction, and classification, while the ANFIS model has several advantages including non-requirement of a mathematical model, simulation of human thinking, and simple interpretation of results compared with other predictive methods.
Assuntos
Poluentes Atmosféricos/análise , Modelos Teóricos , Veículos Automotores , Redes Neurais de Computação , Material Particulado/análise , Monitoramento Ambiental/métodos , Humanos , Poluição por Fumaça de Tabaco/análise , Emissões de Veículos/análise , Tempo (Meteorologia)RESUMO
Airborne dust, which contains high levels of toxic metals, is recognized as one of the most harmful environment component. The purpose of this study was to evaluate heavy metals pollution in dustfall from bus stations in Beijing, and to perform a risk assessment analysis for adult passengers. The concentrations of Cd, Co, Cr, Cu, Mo, Ni, Pb, V and Zn were determined by inductively coupled plasma mass spectroscopy (ICP-MS). The spatial distribution, pollution level and potential health risk of heavy metals were analyzed by Geographic Information System (GIS) mapping technology, geo-accumulation index and health risk assessment model, respectively. The results indicate that dust samples have elevated metal concentrations, especially for Cd, Cu, Pb and Zn. The nine metals can be divided into two categories in terms of spatial distribution and pollution level. Cd, Cr, Cu, Mo, Pb and Zn reach contaminated level and have similar spatial patterns with hotspots distributed within the Fifth Ring Road. While the hot spot areas of Co and V are always out of the Fifth Ring Road. Health risk assessment shows that both carcinogenic and non-carcinogenic risks of selected metals were within the safe range.