964 resultados para Air quality monitoring stations


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Three-dimensional computational simulations are performed to examine indoor environment and micro-environment around human bodies in an office in terms of thermal environment and air quality. In this study, personal displacement ventilation (PDV), including two cases with all seats taken and two middle seats taken, is compared with overall displacement ventilation (ODV) of all seats taken under the condition that supply temperature is 24℃ and air change rate is 60 l/s per workstation. When using PDV, temperature stratification, the characteristic of displacement ventilation, is obviously observed at the position of occupant’s head and clearer in the case with all seats taken. Verticalertical ertical temperature temperature temperature temperature temperature differences below height of the head areare under under under 2℃ in two cases in two cases in two cases in two cases in two cases in two cases in two cases in two cases with all seats taken,and the temperature with PDV is higher than that with ODV. Verticalertical ertical temperature temperature temperature temperature temperature temperature difference is under 3 under 3under 3 under 3℃ in the case in the case in the case in the case in the case in the case in the case with two middle seats taken. CO2 concentration is lower th is lower th is lower this lower this lower than 2 g/man 2 g/m an 2 g/man 2 g/man 2 g/man 2 g/m 3 in the breath zone. in the breath zone. in the breath zone. in the breath zone. in the breath zone. in the breath zone. in the breath zone. in the breath zone. in the breath zone. The results indicate that PDV can be used in the room with big change of occupants’ number to satisfy the need of thermal comfort and air quality. When not all seats are taken, designers should increase supply air requirement or reduce its temperature for thermal comfort. INDEX TERMS

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In order to evaluate the future potential benefits of emission regulation on regional air quality, while taking into account the effects of climate change, off-line air quality projection simulations are driven using weather forcing taken from regional climate models. These regional models are themselves driven by simulations carried out using global climate models (GCM) and economical scenarios. Uncertainties and biases in climate models introduce an additional “climate modeling” source of uncertainty that is to be added to all other types of uncertainties in air quality modeling for policy evaluation. In this article we evaluate the changes in air quality-related weather variables induced by replacing reanalyses-forced by GCM-forced regional climate simulations. As an example we use GCM simulations carried out in the framework of the ERA-interim programme and of the CMIP5 project using the Institut Pierre-Simon Laplace climate model (IPSLcm), driving regional simulations performed in the framework of the EURO-CORDEX programme. In summer, we found compensating deficiencies acting on photochemistry: an overestimation by GCM-driven weather due to a positive bias in short-wave radiation, a negative bias in wind speed, too many stagnant episodes, and a negative temperature bias. In winter, air quality is mostly driven by dispersion, and we could not identify significant differences in either wind or planetary boundary layer height statistics between GCM-driven and reanalyses-driven regional simulations. However, precipitation appears largely overestimated in GCM-driven simulations, which could significantly affect the simulation of aerosol concentrations. The identification of these biases will help interpreting results of future air quality simulations using these data. Despite these, we conclude that the identified differences should not lead to major difficulties in using GCM-driven regional climate simulations for air quality projections.

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The EU FP7 Project MEGAPOLI: "Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation" (http://megapoli.info) brings together leading European research groups, state-of-the-art scientific tools and key players from non-European countries to investigate the interactions among megacities, air quality and climate. MEGAPOLI bridges the spatial and temporal scales that connect local emissions, air quality and weather with global atmospheric chemistry and climate. The suggested concept of multi-scale integrated modelling of megacity impact on air quality and climate and vice versa is discussed in the paper. It requires considering different spatial and temporal dimensions: time scales from seconds and hours (to understand the interaction mechanisms) up to years and decades (to consider the climate effects); spatial resolutions: with model down- and up-scaling from street- to global-scale; and two-way interactions between meteorological and chemical processes.

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The ClearfLo project provides integrated measurements of the meteorology, composition and particulate loading of London's urban atmosphere to improve predictive capability for air quality. Air quality and heat are strong health drivers and their accurate assessment and forecast are important in densely populated urban areas. However, the sources and processes leading to high concentrations of main pollutants such as ozone, nitrogen dioxide, and fine and coarse particulate matter in complex urban areas are not fully understood, limiting our ability to forecast air quality accurately. This paper introduces the ClearfLo project's interdisciplinary approach to investigate the processes leading to poor air quality and elevated temperatures. Within ClearfLo (www.clearflo.ac.uk), a large multi-institutional project funded by the UK Natural Environment Research Council (NERC), integrated measurements of meteorology, gaseous and particulate composition/loading within London's atmosphere were undertaken to understand the processes underlying poor air quality. Long-term measurement infrastructure installed at multiple levels (street and elevated), and at urban background, kerbside and rural locations were complemented with high-resolution numerical atmospheric simulations . Combining these (measurement/modeling) enhances understanding of seasonal variations in meteorology and composition together with the controlling processes. Two intensive observation periods (winter 2012 and summer Olympics 2012) focus upon the vertical structure and evolution of the urban boundary layer, chemical controls on nitrogen dioxide and ozone production, in particular the role of volatile organic compounds, and processes controlling the evolution, size, distribution and composition of particulate matter. The paper shows that mixing heights are deeper over London than in the rural surroundings and the seasonality of the urban boundary layer evolution controls when concentrations peak. The composition also reflects the seasonality of sources such as domestic burning and biogenic emissions.

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This paper describes the hydrochemistry of a lowland, urbanised river-system, The Cut in England, using in situ sub-daily sampling. The Cut receives effluent discharges from four major sewage treatment works serving around 190,000 people. These discharges consist largely of treated water, originally abstracted from the River Thames and returned via the water supply network, substantially increasing the natural flow. The hourly water quality data were supplemented by weekly manual sampling with laboratory analysis to check the hourly data and measure further determinands. Mean phosphorus and nitrate concentrations were very high, breaching standards set by EU legislation. Though 56% of the catchment area is agricultural, the hydrochemical dynamics were significantly impacted by effluent discharges which accounted for approximately 50% of the annual P catchment input loads and, on average, 59% of river flow at the monitoring point. Diurnal dissolved oxygen data demonstrated high in-stream productivity. From a comparison of high frequency and conventional monitoring data, it is inferred that much of the primary production was dominated by benthic algae, largely diatoms. Despite the high productivity and nutrient concentrations, the river water did not become anoxic and major phytoplankton blooms were not observed. The strong diurnal and annual variation observed showed that assessments of water quality made under the Water Framework Directive (WFD) are sensitive to the time and season of sampling. It is recommended that specific sampling time windows be specified for each determinand, and that WFD targets should be applied in combination to help identify periods of greatest ecological risk. This article is protected by copyright. All rights reserved.

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This paper presents a summary of the work done within the European Union's Seventh Framework Programme project ECLIPSE (Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants). ECLIPSE had a unique systematic concept for designing a realistic and effective mitigation scenario for short-lived climate pollutants (SLCPs; methane, aerosols and ozone, and their precursor species) and quantifying its climate and air quality impacts, and this paper presents the results in the context of this overarching strategy. The first step in ECLIPSE was to create a new emission inventory based on current legislation (CLE) for the recent past and until 2050. Substantial progress compared to previous work was made by including previously unaccounted types of sources such as flaring of gas associated with oil production, and wick lamps. These emission data were used for present-day reference simulations with four advanced Earth system models (ESMs) and six chemistry transport models (CTMs). The model simulations were compared with a variety of ground-based and satellite observational data sets from Asia, Europe and the Arctic. It was found that the models still underestimate the measured seasonality of aerosols in the Arctic but to a lesser extent than in previous studies. Problems likely related to the emissions were identified for northern Russia and India, in particular. To estimate the climate impacts of SLCPs, ECLIPSE followed two paths of research: the first path calculated radiative forcing (RF) values for a large matrix of SLCP species emissions, for different seasons and regions independently. Based on these RF calculations, the Global Temperature change Potential metric for a time horizon of 20 years (GTP20) was calculated for each SLCP emission type. This climate metric was then used in an integrated assessment model to identify all emission mitigation measures with a beneficial air quality and short-term (20-year) climate impact. These measures together defined a SLCP mitigation (MIT) scenario. Compared to CLE, the MIT scenario would reduce global methane (CH4) and black carbon (BC) emissions by about 50 and 80 %, respectively. For CH4, measures on shale gas production, waste management and coal mines were most important. For non-CH4 SLCPs, elimination of high-emitting vehicles and wick lamps, as well as reducing emissions from gas flaring, coal and biomass stoves, agricultural waste, solvents and diesel engines were most important. These measures lead to large reductions in calculated surface concentrations of ozone and particulate matter. We estimate that in the EU, the loss of statistical life expectancy due to air pollution was 7.5 months in 2010, which will be reduced to 5.2 months by 2030 in the CLE scenario. The MIT scenario would reduce this value by another 0.9 to 4.3 months. Substantially larger reductions due to the mitigation are found for China (1.8 months) and India (11–12 months). The climate metrics cannot fully quantify the climate response. Therefore, a second research path was taken. Transient climate ensemble simulations with the four ESMs were run for the CLE and MIT scenarios, to determine the climate impacts of the mitigation. In these simulations, the CLE scenario resulted in a surface temperature increase of 0.70 ± 0.14 K between the years 2006 and 2050. For the decade 2041–2050, the warming was reduced by 0.22 ± 0.07 K in the MIT scenario, and this result was in almost exact agreement with the response calculated based on the emission metrics (reduced warming of 0.22 ± 0.09 K). The metrics calculations suggest that non-CH4 SLCPs contribute ~ 22 % to this response and CH4 78 %. This could not be fully confirmed by the transient simulations, which attributed about 90 % of the temperature response to CH4 reductions. Attribution of the observed temperature response to non-CH4 SLCP emission reductions and BC specifically is hampered in the transient simulations by small forcing and co-emitted species of the emission basket chosen. Nevertheless, an important conclusion is that our mitigation basket as a whole would lead to clear benefits for both air quality and climate. The climate response from BC reductions in our study is smaller than reported previously, possibly because our study is one of the first to use fully coupled climate models, where unforced variability and sea ice responses cause relatively strong temperature fluctuations that may counteract (and, thus, mask) the impacts of small emission reductions. The temperature responses to the mitigation were generally stronger over the continents than over the oceans, and with a warming reduction of 0.44 K (0.39–0.49) K the largest over the Arctic. Our calculations suggest particularly beneficial climate responses in southern Europe, where surface warming was reduced by about 0.3 K and precipitation rates were increased by about 15 (6–21) mm yr−1 (more than 4 % of total precipitation) from spring to autumn. Thus, the mitigation could help to alleviate expected future drought and water shortages in the Mediterranean area. We also report other important results of the ECLIPSE project.

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European air quality legislation has reduced emissions of air pollutants across Europe since the 1970s, affecting air quality, human health and regional climate. We used a coupled composition-climate model to simulate the impacts of European air quality legislation and technology measures implemented between 1970 and 2010. We contrast simulations using two emission scenarios; one with actual emissions in 2010 and the other with emissions that would have occurred in 2010 in the absence of technological improvements and end-of-pipe treatment measures in the energy, industrial and road transport sectors. European emissions of sulphur dioxide, black carbon (BC) and organic carbon in 2010 are 53%, 59% and 32% lower respectively compared to emissions that would have occurred in 2010 in the absence of legislative and technology measures. These emission reductions decreased simulated European annual mean concentrations of fine particulate matter(PM2.5) by 35%, sulphate by 44%, BC by 56% and particulate organic matter by 23%. The reduction in PM2.5 concentrations is calculated to have prevented 80 000 (37 000–116 000, at 95% confidence intervals) premature deaths annually across the European Union, resulting in a perceived financial benefit to society of US$232 billion annually (1.4% of 2010 EU GDP). The reduction in aerosol concentrations due to legislative and technology measures caused a positive change in the aerosol radiative effect at the top of atmosphere, reduced atmospheric absorption and also increased the amount of solar radiation incident at the surface over Europe. We used an energy budget approximation to estimate that these changes in the radiative balance have increased European annual mean surface temperatures and precipitation by 0.45 ± 0.11 °C and by 13 ± 0.8 mm yr−1 respectively. Our results show that the implementation of European legislation and technological improvements to reduce the emission of air pollutants has improved air quality and human health over Europe, as well as having an unintended impact on the regional radiative balance and climate.

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When no prior knowledge is available, clustering is a useful technique for categorizing data into meaningful groups or clusters. In this paper, a modified fuzzy min-max (MFMM) clustering neural network is proposed. Its efficacy for tackling power quality monitoring tasks is demonstrated. A literature review on various clustering techniques is first presented. To evaluate the proposed MFMM model, a performance comparison study using benchmark data sets pertaining to clustering problems is conducted. The results obtained are comparable with those reported in the literature. Then, a real-world case study on power quality monitoring tasks is performed. The results are compared with those from the fuzzy c-means and k-means clustering methods. The experimental outcome positively indicates the potential of MFMM in undertaking data clustering tasks and its applicability to the power systems domain.

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The bulk of existing work on the statistical forecasting of air quality is based on either neural networks or linear regressions, which are both subject to important drawbacks. In particular, while neural networks are complicated and prone to in-sample overfitting, linear regressions are highly dependent on the specification of the regression function. The present paper shows how combining linear regression forecasts can be used to circumvent all of these problems. The usefulness of the proposed combination approach is verified using both Monte Carlo simulation and an extensive application to air quality in Bogota, one of the largest and most polluted cities in Latin America. © 2014 Elsevier Ltd.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)