Absorption of Gaseous Air Pollutants By a Standardized Plant Canopy

Concentration profiles for hydrogen fluoride(HF), sulfur dioxide(SO₂), ozone (O₃), nitrogen dioxide(NO₂), and nitric oxide(NO) generated in a standardized alfalfa canopy are presented. Wind, light, temperature, and carbon dioxide(CO₂) profiles, canopy pollutant uptake rates, and canopy structural data are also given. Canopy pollutant concentration profile characteristics were studied to evaluate the relative potentials for major air pollutants to penetrate into canopies. The study was conducted in an environmental growth chamber equipped to control automatically environmental conditions and monitor continuously gas exchange rates. HF, SO₂, and NO₂ profiles suggested that these gases were removed efficiently by the upper portion of the canopy as well as by the immediate subsurface vegetation. The steady state HF profile showed the greatest displacement within the canopy. The NO profile was displaced the least. The uptake rate of NO by plants was apparently too slow in comparison with gas transport and mixing within the canopy to affect the internal profile substantially. O₃ appeared to be readily deposited on the surface tissues, but the deeper tissues in the canopy had less effect on the concentration profile. Data are also presented to show the relationship between NO₂ concentration within the canopy and changes in the air concentration above the vegetation. The results indicated that gas transport between the atmosphere and canopy interior was rapid. The data presented should be of current interest to agriculturists, researchers, administrators, and environmental planners concerned with effects of air pollutants on plants and on the fate of pollutants in the microenvironment.     

Artificial intelligence modeling to evaluate field performance of photocatalytic asphalt pavement for ambient air purification

In recent years, the application of titanium dioxide (TiO₂) as a photocatalyst in asphalt pavement has received considerable attention for purifying ambient air from traffic-emitted pollutants via photocatalytic processes. In order to control the increasing deterioration of ambient air quality, urgent and proper risk assessment tools are deemed necessary. However, in practice, monitoring all process parameters for various operating conditions is difficult due to the complex and non-linear nature of air pollution-based problems. Therefore, the development of models to predict air pollutant concentrations is very useful because it can provide early warnings to the population and also reduce the number of measuring sites. This study used artificial neural network (ANN) and neuro-fuzzy (NF) models to predict NO_x concentration in the air as a function of traffic count (T_r) and climatic conditions including humidity (H), temperature (T), solar radiation (S), and wind speed (W) before and after the application of TiO₂ on the pavement surface. These models are useful for modeling because of their ability to be trained using historical data and because of their capability for modeling highly non-linear relationships. To build these models, data were collected from a field study where an aqueous nano TiO₂ solution was sprayed on a 0.2-mile of asphalt pavement in Baton Rouge, LA. Results of this study showed that the NF model provided a better fitting to NO_x measurements than the ANN model in the training, validation, and test steps. Results of a parametric study indicated that traffic level, relative humidity, and solar radiation had the most influence on photocatalytic efficiency.     

Analysis of an anomalous case of high air pollution concentration in Turin after a foehn event

A case of unusually high concentrations of some urban air pollutants (CO, NO, SO₂) in Turin (Northwestern Italy) is presented. This episode occurred during the late afternoon of 7 November 1995. This day was characterised by a strong northern foehn event in the morning, which followed the passage of a cold front. The analysis has been carried out by means of data derived from the urban and suburban air quality monitoring networks, of meteorological data (wind velocity, temperature and relative humidity) from the same network and from other networks in the region, and of the output of the numerical model LAMBO (operatively used by the Regional Meteorological Service of Emilia Romagna). The analysis of meteorological data appears to be in good correlation with the distribution of the air pollutant concentrations; in particular, the high concentrations observed in the late afternoon are due to a strong thin inversion layer near the ground, developing immediately after the sudden end of the foehn episode.     

Vegetation: A Sink for Atmospheric Pollutants

The possibility of vegetation being an important sink for gaseous air pollutants was investigated. Plant pollutant uptake measurements were made utilizing a typical vegetation canopy and chambers that were designed specifically for gaseous exchange studies. The data indicate that an alfalfa canopy removed gases from the atmosphere in the following order: hydrogen fluoride (HF) > sulfur dioxide (SO₂) > chlorine (Cl₂) > nitrogen dioxide (NO₂) > ozone (O₃) > peroxyacetyl nitrate (PAN) > nitric oxide (NO) > carbon monoxide (CO). The absorption rate of NO was low, and no absorption of CO could be detected with the methods used. In the typical ambient concentration range uptake increased linearly with increasing concentration except for O₃ and Cl₂ which caused partial stomatal closure at the higher concentrations. Wind velocity above the plants, height of the canopy, and light intensity were shown to affect the pollutant removal rate. A relationship between the absorption rate and solubility of the pollutant in water was also shown. It was concluded that vegetation may be an important sink for many gaseous air pollutants.     

Impacts of some meteorological parameters on SO2 and TSP concentrations in Erzurum, Turkey

The air pollution is the one of the most important environmental problems in Erzurum, situated in the eastern of Turkey, during winter periods. The unfavorable climate as well as the city’s topography, and inappropriate urbanization cause serious air pollution problems. The air pollutant concentrations in a city have a close relationship with its meteorological parameters. In the present study, the relationship between daily average total suspended particulate (TSP) and sulphur dioxide (SO₂) concentrations with meteorological factors, such as wind speed, temperature, relative humidity, pressure and precipitation, in 1995–2002 winter seasons was statistically analyzed using the stepwise multiple linear regression analysis. According to the results obtained through analysis, higher TSP and SO₂ concentrations are strongly related to colder temperatures, lower wind speed, higher pressure system and weakly lower precipitation and higher relative humidity. The statistical models of SO₂ and TSP including meteorological parameters gave R² of 0.74 and 0.88, respectively. Furthermore, the correlation between the previous day’s SO₂, TSP concentrations and actual concentrations of these pollutants on that day was investigated and found as 0.84 and 0.53, respectively. In order to develop this model, previous day’s SO₂ and TSP concentrations were added to the equations. The new model for SO₂ enhanced considerably (R² = 0.92), but for TSP new model was not enhanced (R² = 0.89).     

Predicting hourly air pollutant levels using artificial neural networks coupled with uncertainty analysis by Monte Carlo simulations

Recent progress in developing artificial neural network (ANN) metamodels has paved the way for reliable use of these models in the prediction of air pollutant concentrations in urban atmosphere. However, improvement of prediction performance, proper selection of input parameters and model architecture, and quantification of model uncertainties remain key challenges to their practical use. This study has three main objectives: to select an ensemble of input parameters for ANN metamodels consisting of meteorological variables that are predictable by conventional weather forecast models and variables that properly describe the complex nature of pollutant source conditions in a major city, to optimize the ANN models to achieve the most accurate hourly prediction for a case study (city of Tehran), and to examine a methodology to analyze uncertainties based on ANN and Monte Carlo simulations (MCS). In the current study, the ANNs were constructed to predict criteria pollutants of nitrogen oxides (NO_x), nitrogen dioxide (NO₂), nitrogen monoxide (NO), ozone (O₃), carbon monoxide (CO), and particulate matter with aerodynamic diameter of less than 10 μm (PM₁₀) in Tehran based on the data collected at a monitoring station in the densely populated central area of the city. The best combination of input variables was comprehensively investigated taking into account the predictability of meteorological input variables and the study of model performance, correlation coefficients, and spectral analysis. Among numerous meteorological variables, wind speed, air temperature, relative humidity and wind direction were chosen as input variables for the ANN models. The complex nature of pollutant source conditions was reflected through the use of hour of the day and month of the year as input variables and the development of different models for each day of the week. After that, ANN models were constructed and validated, and a methodology of computing prediction intervals (PI) and probability of exceeding air quality thresholds was developed by combining ANNs and MCSs based on Latin Hypercube Sampling (LHS). The results showed that proper ANN models can be used as reliable metamodels for the prediction of hourly air pollutants in urban environments. High correlations were obtained with R ² of more than 0.82 between modeled and observed hourly pollutant levels for CO, NO_x, NO₂, NO, and PM₁₀. However, predicted O₃ levels were less accurate. The combined use of ANNs and MCSs seems very promising in analyzing air pollution prediction uncertainties. Replacing deterministic predictions with probabilistic PIs can enhance the reliability of ANN models and provide a means of quantifying prediction uncertainties.     

Air ventilation impacts of the “wall effect” resulting from the alignment of high-rise buildings

The objective of this study is to investigate the air ventilation impacts of the so called “wall effect” caused by the alignment of high-rise buildings in complex building clusters. The research method employs the numerical algorithm of computational fluid dynamics (CFD – FLUENT) to simulate the steady-state wind field in a typical Hong Kong urban setting and investigate pollutant dispersion inside the street canyon utilizing a pollutant transport model. The model settings of validation study were accomplished by comparing the simulation wind field around a single building block to wind tunnel data. The results revealed that our model simulation is fairly close to the wind tunnel measurements. In this paper, a typical dense building distribution in Hong Kong with 2 incident wind directions (0° and 22.5°) is studied. Two performance indicators are used to quantify the air ventilation impacts, namely the velocity ratio (VR) and the retention time (T_r) of pollutants at the street level. The results indicated that the velocity ratio at 2 m above ground was reduced 40% and retention time of pollutants increased 80% inside the street canyon when high-rise buildings with 4 times height of the street canyon were aligned as a “wall” upstream. While this reduction of air ventilation was anticipated, the magnitude is significant and this result clearly has important implications for building and urban planning.     

Variation of surface ozone in Campo Grande,Brazil: meteorological effect analysis and prediction

The effect of meteorological variables on surface ozone (O₃) concentrations was analysed based on temporal variation of linear correlation and artificial neural network (ANN) models defined by genetic algorithms (GAs). ANN models were also used to predict the daily average concentration of this air pollutant in Campo Grande, Brazil. Three methodologies were applied using GAs, two of them considering threshold models. In these models, the variables selected to define different regimes were daily average O₃ concentration, relative humidity and solar radiation. The threshold model that considers two O₃ regimes was the one that correctly describes the effect of important meteorological variables in O₃ behaviour, presenting also a good predictive performance. Solar radiation, relative humidity and rainfall were considered significant for both O₃ regimes; however, wind speed (dispersion effect) was only significant for high concentrations. According to this model, high O₃ concentrations corresponded to high solar radiation, low relative humidity and wind speed. This model showed to be a powerful tool to interpret the O₃ behaviour, being useful to define policy strategies for human health protection regarding air pollution.     

PAH air pollution at a Portuguese urban area: carcinogenic risks and sources identification

This study aimed to characterize air pollution and the associated carcinogenic risks of polycyclic aromatic hydrocarbon (PAHs) at an urban site, to identify possible emission sources of PAHs using several statistical methodologies, and to analyze the influence of other air pollutants and meteorological variables on PAH concentrations.The air quality and meteorological data were collected in Oporto, the second largest city of Portugal. Eighteen PAHs (the 16 PAHs considered by United States Environment Protection Agency (USEPA) as priority pollutants, dibenzo[a,l]pyrene, and benzo[j]fluoranthene) were collected daily for 24 h in air (gas phase and in particles) during 40 consecutive days in November and December 2008 by constant low-flow samplers and using polytetrafluoroethylene (PTFE) membrane filters for particulate (PM₁₀ and PM_2.5 bound) PAHs and pre-cleaned polyurethane foam plugs for gaseous compounds. The other monitored air pollutants were SO₂, PM₁₀, NO₂, CO, and O₃; the meteorological variables were temperature, relative humidity, wind speed, total precipitation, and solar radiation. Benzo[a]pyrene reached a mean concentration of 2.02 ng?m^?3, surpassing the EU annual limit value. The target carcinogenic risks were equal than the health-based guideline level set by USEPA (10^?6) at the studied site, with the cancer risks of eight PAHs reaching senior levels of 9.98?×?10^?7 in PM₁₀ and 1.06?×?10^?6 in air. The applied statistical methods, correlation matrix, cluster analysis, and principal component analysis, were in agreement in the grouping of the PAHs. The groups were formed according to their chemical structure (number of rings), phase distribution, and emission sources. PAH diagnostic ratios were also calculated to evaluate the main emission sources. Diesel vehicular emissions were the major source of PAHs at the studied site. Besides that source, emissions from residential heating and oil refinery were identified to contribute to PAH levels at the respective area. Additionally, principal component regression indicated that SO₂, NO₂, PM₁₀, CO, and solar radiation had positive correlation with PAHs concentrations, while O₃, temperature, relative humidity, and wind speed were negatively correlated.     

Interactions of Environmental Factors on the Sensitivity of Plants to Air Pollution

Before potential damage to vegetation can be adequately forecast, even after an air pollution alert has been placed in effect, a clear understanding of the interactions of environment on plant sensitivity must be ascertained. This involves detailed study of single factors and then multiple factors using the phytotoxicants in question. Factors studied or suggested include light (quality, intensity, and duration), temperature, carbon dioxide concentration, humidity, wind, soil moisture, soil aeration, nutrient levels, and soil texture. This paper presents a review of the work relating plant injury to specific air pollutants as conditioned by several environmental conditions supported by research on the interactions of ozone with these environmental conditions.     

Enhancing mixed toluene and formaldehyde pollutant removal by Zamioculcas zamiifolia combined with Sansevieria trifasciata and its CO2 emission

Indoor air pollutants comprise both polar and non-polar volatile organic compounds (VOCs). Indoor potted plants are well known for their innate ability to improve indoor air quality (IAQ) by detoxification of indoor air pollutants. In this study, a combination of two different plant species comprising a C3 plant (Zamioculcas zamiifolia) and a crassulacean acid metabolism (CAM) plant (Sansevieria trifasciata) was used to remove polar and non-polar VOCs and minimize CO₂ emission from the chamber. Z. zamiifolia and S. trifasciata, when combined, were able to remove more than 95% of pollutants within 48 h and could do so for six consecutive pollutant’s exposure cycles. The CO₂ concentration was reduced from 410 down to 160 ppm inside the chamber. Our results showed that using plant growth medium rather than soil had a positive effect on decreasing CO₂. We also re-affirmed the role of formaldehyde dehydrogenase in the detoxification and metabolism of formaldehyde and that exposure of plants to pollutants enhances the activity of this enzyme in the shoots of both Z. zamiifolia and S. trifasciata. Overall, a mixed plant of Z. zamiifolia and S. trifasciata was more efficient at removing mixed pollutants and reducing CO₂ than individual plants.

     

Process analysis of a regional air pollution episode over Pearl River Delta Region,China, using the MM5-CMAQ model

This study focuses on the influences of a warm high-pressure meteorological system on aerosol pollutants, employing the simulations by the Models-3/CMAQ system and the observations collected during October 10–12, 2004, over the Pearl River Delta (PRD) region. The results show that the spatial distributions of air pollutants are generally circular near Guangzhou and Foshan, which are cities with high emissions rates. The primary pollutant is particulate matter (PM) over the PRD. MM5 shows reasonable performance for major meteorological variables (i.e., temperature, relative humidity, wind direction) with normalized mean biases (NMB) of 4.5–38.8% and for their time series. CMAQ can capture one peak of all air pollutant concentrations on October 11, but misses other peaks. The CMAQ model systematically underpredicts the mass concentrations of all air pollutants. Compared with chemical observations, SO₂ and O₃ are predicted well with a correlation coefficient of 0.70 and 0.65. PM_2.5 and NO are significantly underpredicted with an NMB of 43% and 90%, respectively. The process analysis results show that the emission, dry deposition, horizontal transport, and vertical transport are four main processes affecting air pollutants. The contributions of each physical process are different for the various pollutants. The most important process for PM₁₀ is dry deposition, and for NO_x it is transport. The contributions of horizontal and vertical transport processes vary during the period, but these two processes mostly contribute to the removal of air pollutants at Guangzhou city, whose emissions are high. For this high-pressure case, the contributions of the various processes show high correlations in cities with the similar geographical attributes. According to the statistical results, cities in the PRD region are divided into four groups with different features. The contributions from local and nonlocal emission sources are discussed in different groups.

Implications: The characteristics of aerosol pollution episodes are intensively studied in this work using the high-resolution modeling system MM5/SMOKE/CMAQ, with special efforts on examining the contributions of different physical and chemical processes to air concentrations for each city over the PRD region by a process analysis method, so as to provide a scientific basis for understanding the formation mechanism of regional aerosol pollution under the high-pressure system over PRD.     

Root growth responses of Anagallis arvensis L., primulaceae to air pollution

The root growth response to air pollution in populations of Anagallis arvensis growing about 0.5, 2, 6, 12 and 20 km leeward from a power plant complex varied with the level of pollution, age of the stand and meteorological conditions. The roots were more affected by the pollutants at a young stage and the loss in net primary productivity was proportional to the pollution level. The populations up to 2 km from the source of pollution completed their life cycle quickly. The coal consumption rate at the power plant, relative humidity, wind direction and other environmental factors were found to influence the degree of growth response to air pollution.     

The effect of humidity and state of water surfaces on deposition of aerosol particles onto a water surface

Deposition processes of particles with dry diameter larger than about 10 μm are dominated by gravitational settling, while molecular diffusion and Brownian motion predominate the deposition processes of particles smaller than 0.1 μm in dry diameter. Many air pollution derived elements exhibit characteristics common to sub-micron particles. The objective of the present study is to examine the effects of meteorological conditions within the turbulent transfer layer on the deposition velocity of particles with dry diameter between 0.1 and 1 μm. It is for these sub-micron particles that particle growth by condensation in the deposition layer, the broken water surface effect and the enhanced transfer process due to atmospheric turbulence in the turbulent transfer layer play important roles in controlling the particle deposition velocity. Results of the present study show that the `dry air’ assumption of Williams’ model is unrealistic. Effects of ambient air relative humidity and water surface temperature cannot be ignored in determining the deposition velocity over a water surface. Neglecting effects of ambient air relative humidity and water surface temperature will result in defining atmospheric stability incorrectly. It is found that the largest effect of air relative humidity on deposition velocity occurs at an air–water temperature difference corresponding to the point of `displaced neutral stability'. For a given wind speed of U=5 m s⁻¹ the additive effects of water surface temperature, T_w, changes from 5 to 25°C and ambient air relative humidity variations from 85 to 60%, respectively, lead to a maximum difference in v_d of about 20%. For a higher wind speed of 10 m s⁻¹, however, the corresponding change in v_d reduces to less than 5%. This is further confirmation that wind speed is one of the strongest variables that governs the magnitude of v_d. The present study also found that the broken surface transfer coefficient, k_bs, given as a multiple of the smooth surface transfer coefficient, k_ss, is physically more meaningful than assigning it a constant value independent of particle size. The method used in this study requires only a single level of atmospheric data coupled with the surface temperature measurement. The present method is applicable for determining deposition velocity not only at the conventional measurement height of 10 m but also at any other heights that are different from the measurement height.     

Air Pollution Research Needs: Herbaceous and Ornamental Plants and Agriculturally Generated Pollutants

Effects of various air pollutants on economically important crops and ornamentals have been studied since before the turn of the century.

Summaries of this research on the effects of air pollutants, that have appeared in criteria documents developed by the Environmental Protection Agency, should be reviewed with respect to differences in plant susceptibility found in various regions of the country. These susceptibility differences are associated with variations in both environmental conditions and distribution of pollutants. Research efforts on air pollution injury to vegetation have often been poorly coordinated leaving many gaps in our knowledge. A better assessment of the impact of air pollution on vegetation is required to attain realistic controls for pollutants affecting agriculture. Research areas of major concern include: baseline information on effects of pollutants on agricultural productivity; dose-response information to support predictive mathematical models for acute and chronic studies of growth, yield, and quality effects; effects of pollutants interacting with other pollutants and with insects and plant diseases; mechanisms of pollutant action; genetic changes related to pollutant effects; effects of environmental stresses on plant response to pollutants; evaluation of plants including soil microbes as pollutant sinks; development of techniques to minimize pollutant effects; and, the effects of agricultural chemicals as air pollutants. There is a need for studies that consider the whole plant in its natural environment. Conceptual models interrelating pollutant effects and their interactions and ultimately mathematical models will be needed to develop an intelligent approach to land management. The effects of agriculturally produced pollutants on plants and other receptors must be identified and quantified.     

Daily Mortality and Air Pollution in the Netherlands

ABSTRACT

We studied the association of daily mortality with short-term variations in the ambient concentrations of major gaseous pollutants and PM in the Netherlands. The magnitude of the association in the four major urban areas was compared with that in the remainder of the country. Daily cause-specific mortality counts, air quality, temperature, relative humidity, and influenza data were obtained from 1986 to 1994. The relationship between daily mortality and air pollution was modeled using Poisson regression analysis. We adjusted for potential confounding due to long-term and seasonal trends, influenza epidemics, ambient temperature and relative humidity, day of the week, and holidays, using generalized additive models.

Influenza episodes were associated with increased mortality up to 3 weeks later. Daily mortality was significantly associated with the concentration of all air pollutants. An increase in the PM₁₀ concentration by 100 u.g/m³ was associated with a relative risk (RR) of 1.02 for total mortality. The largest RRs were found for pneumonia deaths. Ozone had the most consistent, independent association with mortality. Particulate air pollution (e.g., PM₁₀, black smoke [BS]) was not more consistently associated with mortality than were the gaseous pollutants SO₂ and NO₂. Aerosol SO₄ ^-2, NO₃ ^-, and BS were more consistently associated with total mortality than was PM₁₀. The RRs for all pollutants were substantially larger in the summer months than in the winter months. The RR of total mortality for PM₁₀ was 1.10 for the summer and 1.03 for the winter. There was no consistent difference between RRs in the four major urban areas and the more rural areas.     

Seasonal differences in the levels of suspended particulate matter and heavy metals in the vicinity of a waste dump

Total suspended particulate matter and heavy metal (Pb, Mn, Cd and Hg) concentrations were measured at the location in the vicinity of the waste dump to determine the air pollution level of these pollutants prior to the operation of the Mobile Thermal Treatment Plant. Samples were collected over one year period. Seasonal differences, and the influence of meteorological parameters (temperature, relative humidity, pressure and wind direction) on the air pollution levels were studied. Results show relatively low concentrations of TSP, Pb, Mn and Cd, while Hg levels were higher compared to the guideline values. Good weather conditions are connected to long range transport of particulate matter, while higher temperatures result in elevated mercury concentrations. Because of the predominant northeast wind direction, the contribution of air pollution from the direction of the waste dump at the measuring site is significant, but that does not necessarily mean that the pollutants originated from that source.     

Passive sampling of ambient, gaseous air pollutants: an assessment from an ecological perspective

During some past two decades there has been a growing interest among air pollution-vegetation effects-scientists to use passive sampling systems for quantifying ambient, gaseous air pollutant concentrations, particularly in remote and wilderness areas. On the positive side, excluding the laboratory analysis costs, passive samplers are inexpensive, easy to use and do not require electricity to operate. Therefore, they are very attractive for use in regional-scale air quality assessments. Passive samplers allow the quantification of cumulative air pollutant exposures, as total or average pollutant concentrations over a sampling duration. Such systems function either by chemical absorption or by physical adsorption of the gaseous pollutant of interest onto the sampling medium. Selection of a passive sampler must be based on its known or tested characteristics of specificity and linearity of response to the chemical constituent being collected. In addition, the effects of wind velocity, radiation, temperature and relative humidity must be addressed in the context of absorbent/adsorbent performance and sampling rate. Because of all these considerations, passive samplers may provide under- or overestimations of the cumulative exposures, compared to the corresponding data from co-located continuous monitors or active samplers, although such statistical variance can be minimized by taking necessary precautions. On the negative side, cumulative exposures cannot identify short-term (相似文献   

Development of a versatile experimental setup for the evaluation of the photocatalytic properties of construction materials under realistic outdoor conditions

The interest on outdoor photocatalytic materials is growing in the last years. Nevertheless, most of the experimental devices designed for the assessment of their performance operate at controlled laboratory conditions, i.e., pollutant concentration, temperature, UV irradiation, and water vapor contents, far from those of real outdoor environments. The aim of the present study was the design and development of an experimental device for the continuous test of photocatalytic outdoor materials under sun irradiation using real outdoor air as feed, with the concomitant fluctuation of pollutant concentration, temperature, and water vapor content. A three-port measurement system based on two UV-transparent chambers was designed and built. A test chamber contained the photoactive element and a reference chamber to place the substrate without the photoactive element were employed. The third sampling point, placed outdoors, allowed the characterization of the surrounding air, which feeds the test chambers. Temperature, relative humidity (RH), and UV-A irradiance were monitored at each sampling point with specific sensors. NO _x concentration was measured by a chemiluminescence NO _x analyzer. Three automatic valves allowed the consecutive analysis of the concentration at the three points at fixed time intervals. The reliability of the analytical system was demonstrated by comparing the NO _x concentration data with those obtained at the nearest weather station to the experimental device location. The use of a chamber-based reaction system leads to an attenuation of NO _x and atmospheric parameter profiles, but maintaining the general trends. The air characterization results showed the wide operating window under which the photoactive materials should work outdoors, depending on the traffic intensity and the season, which are reproduced inside the test chambers. The designed system allows the measurement of the photoactivity of outdoor materials or the comparison of several samples at the same time. The suitability of the system for the evaluation of the DeNO _x properties of construction elements at realistic outdoor conditions was demonstrated. The designed experimental device can be used 24/7 for testing materials under real fluctuations of NO _x concentration, temperature, UV irradiation, and relative humidity and the presence of other outdoor air pollutants such as VOCs, SO _x , or NH₃. The chamber-based design allows comparing a photocatalytic material with respect to a reference substrate without the photoactive phase, or even the comparison of several outdoor elements at the same time. Figure

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A wide area of air pollutant impact downwind of a freeway during pre-sunrise hours

We have observed a wide area of air pollutant impact downwind of a freeway during pre-sunrise hours in both winter and summer seasons. In contrast, previous studies have shown much sharper air pollutant gradients downwind of freeways, with levels above background concentrations extending only 300 m downwind of roadways during the day and up to 500 m at night. In this study, real-time air pollutant concentrations were measured along a 3600 m transect normal to an elevated freeway 1–2 h before sunrise using an electric vehicle mobile platform equipped with fast-response instruments. In winter pre-sunrise hours, the peak ultrafine particle (UFP) concentration (～95 000 cm^?3) occurred immediately downwind of the freeway. However, downwind UFP concentrations as high as ～40 000 cm^?3 extended at least 1200 m from the freeway, and did not reach background levels (～15 000 cm^?3) until a distance of about 2600 m. UFP concentrations were also elevated over background levels up to 600 m upwind of the freeway. Other pollutants, such as NO and particle-bound polycyclic aromatic hydrocarbons, exhibited similar long-distance downwind concentration gradients. In contrast, air pollutant concentrations measured on the same route after sunrise, in the morning and afternoon, exhibited the typical daytime downwind decrease to background levels within ～300 m as found in earlier studies. Although pre-sunrise traffic volumes on the freeway were much lower than daytime congestion peaks, downwind UFP concentrations were significantly higher during pre-sunrise hours than during the daytime. UFP and NO concentrations were also strongly correlated with traffic counts on the freeway. We associate these elevated pre-sunrise concentrations over a wide area with a nocturnal surface temperature inversion, low wind speeds, and high relative humidity. Observation of such wide air pollutant impact area downwind of a major roadway prior to sunrise has important exposure assessment implications since it demonstrates extensive roadway impacts on residential areas during pre-sunrise hours, when most people are at home.