Average mass concentrations of TSP, PM10 and PM2.5 in Erzurum urban atmosphere, Turkey

In this study, particulate matters (TSP, PM₁₀, PM_2.5 and PM_10–2.5) which are hazardous for environment and human health were investigated in Erzurum urban atmosphere at a sampling point from February 2005 to February 2006. During sampling, two low volume samplers were used and each sampling period lasted approximately 24 h. In order for detection of representative sampling region and point of Erzurum, Kriging method was applied to the black smoke concentration data for winter seasons. Mass concentrations of TSP, PM₁₀ and PM_2.5 of Erzurum urban atmosphere were measured on average, as 129, 31 and 13 μg/m³, respectively, in the sampling period. Meteorological factors, such as temperature, wind speed, wind direction and rainfall were typically found to be affecting PMs, especially PM_2.5. Air temperature did not seem to be significantly affecting TSP and PM₁₀ mass concentrations, but had a considerably negative induction on PM_2.5 mass concentrations. However, combustion sourced PM_2.5 was usually diluted from the urban atmosphere by the speed of wind, soil sourced coarse mode particle concentrations (TSP, PM₁₀) were slightly affected by the speed of wind. Rainfall was found to be decreasing concentrations to 48% in all fractions (TSP, PM₁₀, PM_10–2.5, PM_2.5) and played an important role on dilution of the atmosphere. Fine mode fraction of PM (PM_2.5) showed significant daily and seasonal variations on mass concentrations. On the other hand, coarse mode fractions (TSP, PM₁₀ and PM_10–2.5) revealed more steady variations. It was observed that fine mode fraction variations were affected by the heating in residences during winter seasons.     

Vertical structures of PM10 and PM 2.5 and their dynamical character in low atmosphere in Beijing urban areas

The vertical structures and their dynamical character of PM2.5 and PM10 over Beijing urban areas are revealed using the 1 min mean continuous mass concentration data of PM2.5 and PM10 at 8, 100, and 320 m heights of the meteorological observation tower of 325 m at Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP CAS tower hereafter) on 10―26 August, 2003, as well as the daily mean mass concentration data of PM2.5 and PM10 and the continuous data of CO and NO2 at 8, 100 (low layer), 200 (middle layer), and 320 m (high layer) heights, in combination with the same period meteorological field observation data of the meteorological tower. The vertical distributions of aerosols observed on IAP CAS tower in Beijing can be roughly divided into two patterns: gradually and rapidly decreasing patterns, I.e. The vertical distribution of aerosols in calm weather or on pollution day belongs to the gradually decreasing pattern, while one on clean day or weak cold air day belongs to the rapidly decreasing pattern. The vertical distributive characters of aerosols were closely related with the dynamical/thermal structure and turbulence character of the atmosphere boundary layer. On the clean day, the low layer PM2.5 and PM10 concentrations were close to those at 8 m height, while the concentrations rapidly decreased at the high layer, and their values were only one half of those at 8 m, especially, the concentration of PM2.5 dropped even more. On the clean day, there existed stronger turbulence below 150 m, aerosols were well mixed, but blocked by the more stronger inversion layer aloft, and meanwhile, at various heights, especially in the high layer, the horizontal wind speed was larger, resulting in the rapid decrease of aerosol concentration, I.e. Resulting in the obvious vertical difference of aerosol concentrations between the low and high layers. On the pollution day, the concentrations of PM2.5 and PM10 at the low, middle, and high layers dropped successively by, on average, about 10% for each layer in comparison with those at 8 m height. On pollution days, in company with the low wind speed, there existed two shallow inversion layers in the boundary layer, but aerosols might be, to some extent, mixed below the inversion layer, therefore, on the pollution day the concentrations of PM2.5 and PM10 dropped with height slowly; and the observational results also show that the concentrations at 320 m height were obviously high under SW and SE winds, but at other heights, the concentrations were not correlated with wind directions. The computational results of footprint analysis suggest that this was due to the fact that the 320 m height was impacted by the pollutants transfer of southerly flow from the southern peripheral heavier polluted areas, such as Baoding, and Shijiazhuang of Hebei Province, Tianjin, and Shandong Province, etc., while the low layer was only affected by Beijing's local pollution source. The computational results of power spectra and periods preliminarily reveal that under the condition of calm weather, the periods of PM10 concentration at various heights of the tower were on the order of minutes, while in cases of larger wind speed, the concentrations of PM2.5 and PM10 at 320 m height not only had the short periods of minute-order, but also the longer periods of hour order. Consistent with the conclusion previously drawn by Ding et al., that air pollutants at different heights and at different sites in Beijing had the character of "in-phase" variation, was also observed for the diurnal variation and mean diurnal variation of PM2.5 and PM10 at various heights of the tower in this experiment, again confirming the "in-phase" temporal/spatial distributive character of air pollutants in the urban canopy of Beijing. The gentle double-peak character of the mean diurnal variation of PM2.5 and PM10 was closely related with the evident/similar diurnal variation of turbulent momentum fluxes, sensible heat fluxes, and turbulent kinetic energy at various heights in the urban canopy. Besides, under the condition of calm weather, the concentration of PM2.5 and PM10 declined with height slowly, it was 90% of 8 m concentration at the low layer, a little lesser than 90% at the middle layer, and 80% at the high layer, respectively. Under the condition of weak cold air weather, the concentration remarkably dropped with height, it was 70% of 8 m concentration at the low layer, and 20%―30% at the middle and high layers, especially the concentration of PM2.5 was even lower.     

Influence of cryptogamic crust disturbance to wind erosion on sand and loam rangeland soils

A portable field wind tunnel was used to assess the sediment flux rates of loam and sand textured soils in the Mallee region of southeastern Australia. Three levels of crust disturbance (nil, moderate and severe) simulating stock trampling were investigated. The results demonstrated the importance of cryptogamic crusts in binding the soil surface and providing roughness after the soil was moderately disturbed. On the loamy soil, the crust helped maintain sediment flux rates below the erosion control target to 5 g m⁻¹ s⁻¹ for a 65 km h⁻¹ wind measured at 10 m height. Once the crust was severely disturbed, sediment fluxes increased to 1·6 times the erosion target. On the sandy soil, even with no crust disturbance the sediment flux was 1·6 times the erosion control target. Disturbing the crust increased sediment fluxes to a maximum of 6·7 times the erosion control target. Removal of the crust also decreased the threshold wind velocity that resulted in an increase to the risk of erosion from <5 per cent to 20 per cent. © 1998 John Wiley & Sons, Ltd.     

Three-dimensional analysis of ozone and PM<Subscript>2.5</Subscript> distributions obtained by observations of tethered balloon and unmanned aerial vehicle in Shanghai,China

A lightweight unmanned aerial vehicle (UAV) and a tethered balloon platform were jointly used to investigate three-dimensional distributions of ozone and PM_2.5 concentrations within the lower troposphere (1000 m) at a localized coastal area in Shanghai, China. Eight tethered balloon soundings and three UAV flights were conducted on May 25, 2016. Generalized additive models (GAMs) were used to quantitatively describe the relationships between air pollutants and other obtained parameters. Field observations showed that large variations were captured both in the vertical and horizontal distributions of ozone and PM_2.5 concentrations. Significant stratified layers of ozone and PM_2.5 concentrations as well as wind directions were observed throughout the day. Estimated bulk Richardson numbers indicate that the vertical mixing of air masses within the lower troposphere were heavily suppressed throughout the day, leading to much higher concentrations of ozone and PM_2.5 in the planetary boundary layer (PBL). The NO and NO₂ concentrations in the experimental field were much lower than that in the urban area of Shanghai and demonstrated totally different vertical distribution patterns from that of ozone and PM_2.5. This indicates that aged air masses of different sources were transported to the experimental field at different heights. Results derived from the GAMs showed that the aggregate impact of the selected variables for the vertical variations can explain 94.3% of the variance in ozone and 94.5% in PM_2.5. Air temperature, relative humidity and atmospheric pressure had the strongest effects on the variations of ozone and PM_2.5. As for the horizontal variations, the GAMs can explain 56.3% of the variance in ozone and 57.6% in PM_2.5. The strongest effect on ozone was related to air temperature, while PM_2.5 was related to relative humidity. The output of GAMs also implied that fine aerosol particles were in the stage of growth in the experimental field, which is different from ozone (aged air parcels of ozone). Geographical parameters influenced the horizontal variations of ozone and PM_2.5 concentrations by changing underlying surface types. The differences of thermodynamic properties between land and sea resulted in quick changes of PBL height, air temperature and dew point over the coastal area, which was linked to the extent of vertical mixing at different locations. The results of GAMs can be used to analyze the sources and formation mechanisms of ozone and PM_2.5 pollutions at a localized area.     

Lockdown as an Empirical Strategy to Curb Air Pollution: Evidence from a Quasi-Natural Experiment

In this study, three approaches namely parallel, sequential, and multiple linear regression are applied to analyze the local air quality improvements during the COVID-19 lockdowns. In the present work, the authors have analyzed the monitoring data of the following primary air pollutants: particulate matter (PM₁₀ and PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and carbon monoxide (CO). During the lockdown period, the first phase has most noticeable impact on airquality evidenced by the parallel approach, and it has reflected a significant reduction in concentration levels of PM₁₀ (27%), PM_2.5 (19%), NO₂ (74%), SO₂ (36%), and CO (47%), respectively. In the sequential approach, a reduction in pollution levels is also observed for different pollutants, however, these results are biased due to rainfall in that period. In the multiple linear regression approach, the concentrations of primary air pollutants are selected, and set as target variables to predict their expected values during the city's lockdown period.The obtained results suggest that if a 21-days lockdown is implemented, then a reduction of 42 µg m⁻³ in PM₁₀, 23 µg m⁻³ in PM_2.5, 14 µg m⁻³ in NO₂, 2 µg m⁻³ in SO₂, and 0.7 mg m⁻³ in CO can be achieved.     

Wind erosion and dust emissions in central Asia: Spatiotemporal simulations in a typical dust year

The prediction of wind erosion and dust emissions is important for controlling erosion and identifying dust sources in arid and semiarid regions of the world. This study predicts quantitatively wind erosion and dust emissions in Xinjiang Province, central Asia. The wind erosion prediction system (WEPS) was used to simulate annual soil and PM10 (particulate matter ≤10 μm in aerodynamic diameter) loss at 64 meteorological stations across the province. Soil and PM10 loss were simulated from bare surfaces at all 64 stations and from cotton and wheat fields at 11 stations. Simulated annual bare soil and PM10 loss were lowest in the Junggar (soil and PM10 loss were, respectively, 121.7 and 7.6 kg m^-2) and Tarim basins (soil loss was 78.2 kg ha^-1 and PM10 loss was 6.5 kg m^-2) and highest in the Tu-ha Basin (soil and PM10 loss were, respectively, 638.2 and 37.7 kg m^-2). Stations with the highest annual soil loss in the Tarim and Tu-ha basins also had the highest number of days with wind speeds >8 m s^-1. This indicated wind influenced erosion, but other factors such as soil type also affect wind erosion. The maximum monthly bare soil and PM10 loss occurred in May in the three basins, substantiating that dust storms occur most frequently during spring in the region. Simulated soil and PM10 loss were lower for cotton and wheat than bare soil, thus suggesting that maintaining vegetative cover during a portion of the year provided some protection to the soil surface from wind erosion. © 2018 John Wiley & Sons, Ltd.     

Forecasting Hourly Roadside Particulate Matter in Taipei County of Taiwan Based on First‐Order and One‐Variable Grey Model

In this study, seven types of first‐order and one‐variable grey differential equation model (abbreviated as GM (1, 1) model) were used to forecast hourly roadside particulate matter (PM) including PM₁₀ and PM_2.5 concentrations in Taipei County of Taiwan. Their forecasting performance was also compared. The results indicated that the minimum mean absolute percentage error (MAPE), mean squared error (MSE), root mean squared error (RMSE), and maximum correlation coefficient (R) was 11.70%, 60.06, 7.75, and 0.90%, respectively when forecasting PM₁₀. When forecasting PM_2.5, the minimum MAPE, MSE, RMSE, and maximum R‐value of 16.33%, 29.78, 5.46, and 0.90, respectively could be achieved. All statistical values revealed that the forecasting performance of GM (1, 1, x⁽⁰⁾), GM (1, 1, a), and GM (1, 1, b) outperformed other GM (1, 1) models. According to the results, it revealed that GM (1, 1) was an efficiently early warning tool for providing PM information to the roadside inhabitants.     

Quantifying the effect of geomorphology on aeolian dust emission potential in northern China

Representation of dust sources remains a key challenge in quantifying the dust cycle and its environmental and climatic impacts. Direct measurements of dust fluxes from different landform types are useful in understanding the nature of dust emission and characterizing the dynamics of soil erodibility. In this study we used the PI-SWERL® instrument over a seasonal cycle to quantify the potential for PM₁₀ (particles with diameter ≤10 μm) emission from several typical landform types across the Tengger Desert and Mu Us Sandy Land, northern China. Our results indicate that sparse grasslands and coppice dunes showed relatively high emission potentials, with emitted fluxes ranging from 10⁻¹ to 10¹ mg m⁻² s⁻¹. These values were up to five times those emitted from sand dunes, and one to two orders of magnitude greater than the emissions from dry lake beds, stone pavements and dense grasslands. Generally, PM₁₀ emission fluxes were seen to peak in the spring months, with significant reductions in summer and autumn (by up to 95%), and in winter (by up to 98%). Variations in soil moisture were likely a primary controlling factor responsible for this seasonality in PM₁₀ emission. Our data provide a relative quantification of differences in dust emission potential from several key landform types. Such data allow for the evaluation of current dust source schemes proposed by prior researchers. Moreover, our data will allow improvements in properly characterizing the erodibility of dust source regions and hence refine the parameterization of dust emission in climate models. © 2019 John Wiley & Sons, Ltd. © 2019 John Wiley & Sons, Ltd.     

Modelling air pollution data by the skew-normal distribution

Particulate matter with an aerodynamic equivalent diameter of up 10 μm is commonly referred to as PM₁₀ and its harmful effects on human health are well known. We model annual means of daily concentrations of PM₁₀ in Italy by the skew-normal distribution, giving theoretical as well as empirical motivations for the model’s choice. Its adequacy is checked through Anderson–Darling statistic. The skew-normal distribution gives a very good fit to the data and it is particularly useful in estimating probabilities of high PM₁₀ concentrations.     

大型浅水湖泊与大气之间的动量和水热交换系数——以太湖为例

湖泊水面与大气之间垂直方向的动量、水汽和热量通量与风速、湿度和温度梯度之间存在比例关系,因此在湖泊水-气相互作用研究中,这比例系数(交换系数)是关键因子.在以往的研究中,交换系数通常直接采用水面梯度观测法或海洋大气近地层的参数化方案进行计算.本文采用涡度相关系统和小气候系统仪器在太湖平台上直接观测的通量和气象要素,对上述交换系数(最小均方差原则)进行优化,结果为:动量交换系数C_D10N=1.52×10^-3、水汽交换系数C_E10N=0.82×10^-3、热量交换系数CH10N=1.02×10^-3,与其他内陆湖泊涡度相关观测数据的推导结果一致.本文的研究结果表明:与海洋参数化方案相比,在相同的风速条件下,湖面的空气动力学粗糙度比海洋高,这可能是由于受到水深的影响;如果采用海洋参数化方案,会导致湖泊年蒸发量的估算值偏大40%.太湖的动量、水汽和热量交换系数可以视为常数,可以不考虑稳定度和风速的影响.这是因为本文中83%的数据为近中性条件.敏感性分析表明:如果考虑稳定度的影响,LE模拟值的平均误差降低了0.5 W/m²,H的平均误差降低了0.4 W/m²,u*的计算值没有变化;如果考虑风速的影响,u*模拟值的平均误差降低了0.004 m/s,LE的平均误差升高了1.3 W/m²,H的模拟结果几乎不受影响.这一结果能为湖气相互作用研究提供参考.     

Predicting spatio-temporal concentrations of PM<Subscript>2.5</Subscript> using land use and meteorological data in Yangtze River Delta,China

The prediction of PM_2.5 concentrations with high spatiotemporal resolution has been suggested as a potential method for data collection to assess the health effects of exposure. This work predicted the weekly average PM_2.5 concentrations in the Yangtze River Delta, China, by using a spatio-temporal model. Integrating land use data, including the areas of cultivated land, construction land, and forest land, and meteorological data, including precipitation, air pressure, relative humidity, temperature, and wind speed, we used the model to estimate the weekly average PM_2.5 concentrations. We validated the estimated effects by using the cross-validated R² and Root mean square error (RMSE); the results showed that the model performed well in capturing the spatiotemporal variability of PM_2.5 concentration, with a reasonably large R² of 0.86 and a small RMSE of 8.15 (μg/m³). In addition, the predicted values covered 94% of the observed data at the 95% confidence interval. This work provided a dataset of PM_2.5 concentration predictions with a spatiotemporal resolution of 3 km × week, which would contribute to accurately assessing the potential health effects of air pollution.     

Geographies of uncertainty in the health benefits of air quality improvements

Assessing the long-term benefits of marginal improvements in air quality from regulatory intervention is methodologically challenging. In this study, we explore how the relative risks (RRs) of mortality from air pollution exposure change over time and whether patterns in the RRs can be attributed to air quality improvements. We employed two-stage multilevel Cox models to describe the association between air pollution and mortality for 51 cities with data from the American Cancer Society (ACS) cohort (N = 264,299, deaths = 69,819). New pollution data were computed through models that predict yearly average fine particle (PM_2.5) concentrations throughout the follow-up (1982–2000). Average PM_2.5 concentrations from 1999 to 2000 and sulfate concentrations from 1980 were also examined. We estimated the RRs of mortality associated with air pollution separately for five time periods (1982–1986, 1987–1990, 1991–1994, 1995–1998, and 1999–2000). Mobility models were implemented with a sub-sample of 100,557 subjects to assist with interpreting the RR estimates. Sulfate RRs exhibit a large decline from the 1980s to the 1990s. In contrast, PM_2.5 RRs follow the opposite pattern, with larger RRs later in the 1990s. The reduction in sulfate RR may have resulted from air quality improvements that occurred through the 1980s and 1990s in response to the acid rain control program. PM_2.5 concentrations also declined in many places, but toxic mobile sources are now the largest contributors to PM in urban areas. This may account for the heightened RR of mortality associated with PM_2.5 in the 1990s. The paper concludes with a three alternative explanations for the temporal pattern of RRs, each emphasizing the uncertainty in ascribing health benefits to air quality improvements.     

Fine Particles (PM2.5) in Residential Areas of Lucknow City and Factors Influencing the Concentration

Urban populations are exposed to a high level of fine and ultrafine particles from motor vehicle emissions which affect human health. To assess the hourly variation of fine particle (PM_2.5) concentration and the influence of temperature and relative humidity (RH) on the ambient air of Lucknow city, monitoring of PM_2.5 along with temperature and RH was carried out at two residential locations, namely Vikas Nagar and Alambagh, during November 2005. The 24 h mean PM_2.5 concentration at Alambagh was 131.74 μg/m³ and showed an increase of 13.74%, which was significantly higher (p < 0.05) than the Vikas Nagar level. The 24 h mean PM_2.5 on weekdays for both locations was found to be 142.74 μg/m³ (an increase of 66.23%) which was significantly higher (p < 0.01) than the weekend value, indicating that vehicular pollution is one of the important sources of PM_2.5. The mean PM_2.5 at night for all the monitoring days was 157.69 μg/m³ and was significantly higher (p < 0.01) than the daytime concentration (89.87 μg/m³). Correlation and multiple regressions showed that the independent variables, i. e., time, temperature, and RH together accounted for 54%, whereas RH alone accounted for 53% of total variations of PM_2.5, suggesting that RH is the best influencing variable to predict the PM_2.5 concentration in the urban area of Lucknow city. The 24 h mean PM_2.5 for all the monitoring days was found to be higher than the NAAQS recommended by the US‐EPA (65 μg/m³) and can be considered to be an alarming indicator of adverse health effects for city dwellers.     

Black carbon aerosols and their radiative properties in the Pearl River Delta region

The climatic and environmental effects of atmospheric aerosols are a hot topic in global science community, and radiative properties of the aerosols are one of the important parameters in assessing climatic change. Here we studied the black carbon concentration and absorption coefficient measured with aethalometers, scattering coefficient measured with nephelometers, and single scattering albedo derived at an atmospheric composition watch station in Guangzhou from 2004 to 2007. Our main results are as follows. The data of black carbon concentration and absorption coefficients measured with instruments cannot be directly used until they are measured in parallel with internationally accepted instruments for comparison, calibration, and reduction. After evaluation of the data, the result shows that the monthly mean of BC concentration varies 3.1–14.8 μg·m⁻³ and the concentration decreases by about 1 μg·m⁻³ in average over the four years; It is higher in the dry season with a multi-year mean of 8.9 μg/m³ and lower in the rainy season with a multi-year mean of 8.0 μg·m⁻³; The extreme maximum of monthly mean concentration occurred in December 2004 and extreme minimum in July 2007, and a 4-year mean is 8.4 μg·m⁻³. It is also shown that monthly mean scattering coefficient derived varies 129 −565 Mm⁻¹, monthly mean absorption coefficient 32–139 Mm⁻¹, and monthly mean single scattering albedo 0.71–0.91, with annual mean values of 0.80, 0.82, 0.79 and 0.84 for 2004, 2005, 2006 and 2007, respectively. Three instruments were used to take simultaneous measurements of BC in PM₁₀, PM_2.5, and PM₁ and the results showed that PM_2.5 took up about 90% of PM₁₀ and PM₁ accounted for about 68% of PM_2.5, and BC aerosols are mainly present in fine particulates. The variability of BC concentrations is quite consistent between the Nancun station (141 m above sea level) and the Panyu station (13 m above sea level), which are 8 km apart from each other. The concentration in higher altitude station (Panyu) is consistently lower than the lower altitude station (Nancun), and the difference of annual mean is about 4 μg·m⁻³. Supported by Natural Science Foundation of China (Grant Nos. U0733004, 40375002, 40418008, 40775011), National High Technology R & D Program of China (Grant Nos. 2006AA06A306 and 2006AA06A308) and National Basic Research Program of China (Grant No. 2005CB422207)     

Seasonal variation of fluxes and distributions of dissolved methane in the North Yellow Sea

The concentrations and sea-to-air fluxes of dissolved methane (CH₄) were investigated in the North Yellow Sea during August 2006, January, April and October 2007. Dissolved CH₄ concentrations showed obvious seasonal variation, with maximum values occurring in summer and lowest values occurring in winter. The saturations of dissolved CH₄ in surface waters ranged from 78.7% to 1679.7% with an average of 252.4%. The estimated atmospheric CH₄ fluxes using the Liss and Merlivat (LM86), and Wanninkhof formulae (W92) were (4.2±4.7), (11.6±10.3), (8.5±12.7) and (0.2±1.0), and (6.9±7.3), (14.6±22.3), (13.8±14.3) and (0.4±1.7) μmol·(m² d)⁻¹, respectively, for spring, summer, autumn and winter. Based on the average annual atmospheric CH₄ flux and the area of the North Yellow Sea, the annual CH₄ emission was estimated to be (2.4×10⁻²–4.2×10⁻²) Tg a⁻¹, which suggests that the North Yellow Sea was a net source of atmospheric CH₄.     

Windblown dust influenced by conventional and undercutter tillage within the Columbia Plateau,USA

Exceedance of the US Environmental Protection Agency national ambient air quality standard for PM10 (particulate matter ≤10 µm in aerodynamic diameter) within the Columbia Plateau region of the Pacific Northwest US is largely caused by wind erosion of agricultural lands managed in a winter wheat–summer fallow rotation. Land management practices, therefore, are sought that will reduce erosion and PM10 emissions during the summer fallow phase of the rotation. Horizontal soil flux and PM10 concentrations above adjacent field plots (>2 ha), with plots subject to conventional or undercutter tillage during summer fallow, were measured using creep and saltation/suspension collectors and PM10 samplers installed at various heights above the soil surface. After wheat harvest in 2004 and 2005, the plots were either disked (conventional) or undercut with wide sweeps (undercutter) the following spring and then periodically rodweeded prior to sowing wheat in late summer. Soil erosion from the fallow plots was measured during six sampling periods over two years; erosion or PM10 loss was not observed during two periods due to the presence of a crust on the soil surface. For the remaining sampling periods, total surface soil loss from conventional and undercutter tillage ranged from 3 to 40 g m^–2 and 1 to 27 g m^–2 while PM10 loss from conventional and undercutter tillage ranged from 0·2 to 5·0 g m^–2 and 0·1 to 3·3 g m^–2, respectively. Undercutter tillage resulted in a 15% to 65% reduction in soil loss and 30% to 70% reduction in PM10 loss as compared with conventional tillage at our field sites. Therefore, based on our results at two sites over two years, undercutter tillage appears to be an effective management practice to reduce dust emissions from agricultural land subject to a winter wheat–summer fallow rotation within the Columbia Plateau. Copyright © 2009 John Wiley & Sons, Ltd.     

Wind erosion characteristics of Sahelian surface types

The assessment of wind erosion magnitudes for a given area requires knowledge of wind erosion susceptibilities of the dominant local surface types. Relative wind erosion potentials of surfaces can hardly be compared under field conditions, as each erosion event is unique in terms of duration, intensity and extent. The objective of this study was to determine and compare relative wind erosion potentials of the most representative surface types over a transect comprising most parts of southwestern Niger. For this purpose, mobile wind tunnel experiments were run on 26 dominant surface types. The effects of surface disturbance were additionally determined for 13 of these surfaces. The results, namely measurements of wind fields and mass fluxes, can be classified according to specific surface characteristics. Three basic surface groups with similar emission behaviour and aerodynamic characteristics were identified: (1) sand surfaces, (2) rough stone surfaces and (3) flat crusted surfaces. Sand surfaces feature a turbulent zone close to the surface due to the development of a saltation layer. Their surface roughness is medium to high, as a consequence of the loss of kinetic energy of the wind field to saltating particles. Sand surfaces show the highest mass fluxes due to the abundance of loose particles, but also fairly high PM10 fluxes, as potential dust particles are not contained in stable crusts or aggregates. Rough stone surfaces, due to their fragmented and irregular surface, feature the highest surface roughness and the most intense turbulence. They are among the weakest emitters but, due to their relatively high share of potential dust particles, PM10 emissions are still average. Flat crusted surfaces, in contrast, show low turbulence and the lowest surface roughness. This group of surfaces shows rather heterogeneous mass fluxes, which range from moderate to almost zero, although the share of PM10 particles is always relatively high. Topsoil disturbance always results in higher total and PM10 emissions on sand surfaces and also on flat crusted surfaces. Stone surfaces regularly exhibit a decrease in emission after disturbance, which can possibly be attributed to a reorganization which protects finer particles from entrainment. The results are comparable with field studies of natural erosion events and similar wind tunnel field campaigns. The broad range of tested surfaces and the standardized methodology are a precondition for the future regionalization of the experimental point data. Copyright © 2010 John Wiley & Sons, Ltd.     

Mass fraction spatiotemporal geostatistics and its application to map atmospheric polycyclic aromatic hydrocarbons after 9/11

This work proposes a space/time estimation method for atmospheric PM_2.5 components by modelling the mass fraction at a selection of space/time locations where the component is measured and applying the model to the extensive PM_2.5 monitoring network. The method we developed utilizes the nonlinear Bayesian maximum entropy framework to perform the geostatistical estimation. We implemented this approach using data from nine carcinogenic, particle-bound polycyclic aromatic hydrocarbons (PAHs) measured from archived PM_2.5 samples collected at four locations around the World Trade Center (WTC) from September 22, 2001 to March 27, 2002. The mass fraction model developed at these four sites was used to estimate PAH concentrations at additional PM_2.5 monitors. Even with limited PAH data, a spatial validation showed the application of the mass fraction model reduced the mean squared error (MSE) by 7–22%, while in the temporal validation there was an exponential improvement in MSE positively associated with the number of days of PAH data removed. Our results include space/time maps of atmospheric PAH concentrations in the New York area after 9/11.     

The effect of wave-induced turbulence on intertidal mudflats: Impact of boat traffic and wind

Semi-diurnal and fortnightly surveys were carried out to quantify the effects of wind- and navigation-induced high-energy events on bed sediments above intertidal mudflats. The mudflats are located in the upper fluvial part (Oissel mudflat) and at the mouth (Vasière Nord mudflat) of the macrotidal Seine estuary. Instantaneous flow velocities and mudflat bed elevation were measured at a high frequency and high resolution with an acoustic doppler velocimeter (ADV) and an ALTUS altimeter, respectively. Suspended particulate matter concentrations were estimated by calibrating the ADV acoustic backscattered intensity with bed sediments collected at the study sites. Turbulent bed shear stress values were estimated by the turbulent kinetic energy method, using velocity variances filtered from the wave contribution. Wave shear stress and maximum wave–current shear stress values were calculated with the wave–current interaction (WCI) model, which is based on the bed roughness length, wave orbital velocities and the wave period (T_S). In the fluvial part of the estuary, boat passages occurred unevenly during the surveys and were characterized by long waves (T_S>50 s) induced by the drawdown effect and by short boat-waves (T_S<10 s). Boat waves generated large bottom shear stress values of 0.5 N m⁻² for 2–5 min periods and, in burst of several seconds, larger bottom shear stress values up to 1 N m⁻². At the mouth of the estuary, west south-west wind events generated short waves (T_S<10 s) of H_S values ranging from 0.1 to 0.3 m. In shallow-water environment (water depth <1.5 m), these waves produced bottom shear stress values between 1 and 2 N m⁻². Wave–current shear stress values are one order of magnitude larger than the current-induced shear stress and indicate that navigation and wind are the dominant hydrodynamic forcing parameters above the two mudflats. Bed elevation and SPM concentration time series showed that these high energy events induced erosion processes of up to several centimetres. Critical erosion shear stress (τ_ce) values were determined from the SPM concentration and bed elevation measurements. Rough τ_ce values were found above 0.2 N m⁻² for the Oissel mudflat and about 1 N m⁻² for the Vasière Nord mudflat.     

Characteristics of low-frequency oscillation intensity of air-sea turbulent heat fluxes over the northwest Pacific

Based on the daily turbulent heat fluxes and related meteorological variables datasets (1985–2006) from Objectively Analyzed air-sea Fluxes (OAFlux) Project of Woods Hole Oceanographic Institution (WHOI), characteristics of low-frequency oscillation intensity of air-sea turbulent heat fluxes over the northwest Pacific are analyzed by linear perturbation method and correlation analysis. It can be concluded that: 1) the distribution of low-frequency oscillation intensity of latent heat flux (LHF) over the northwest Pacific is mainly affected by that of low-frequency oscillation intensity of anomalous air-sea humidity gradient (Δq′) as well as mean air-sea humidity gradient (), while the distribution of low-frequency oscillation intensity of sensible heat flux (SHF) is mainly affected by that of low-frequency oscillation intensity of anomalous air-sea temperature gradient (ΔT′). 2) The low-frequency oscillation of turbulent heat fluxes over the northwest Pacific is the strongest in winter and the weakest in summer. And the seasonal transition of low-frequency oscillation intensity of LHF is jointly influenced by those of low-frequency oscillation intensity of Δq′, low-frequency oscillation intensity of anomalous wind speed (U′), and mean wind speed (Ū), while the seasonal transition of low-frequency oscillation intensity of SHF is mainly influenced by those of low-frequency oscillation intensity of ΔT′ and Ū. 3) Over the tropical west Pacific and sea areas north of 20°N, the low-frequency oscillation of LHF (SHF) is mainly influenced by atmospheric variables q _a ′ (T _a ′) and U′, indicating an oceanic response to overlying atmospheric forcing. In contrast, over the tropical eastern and central Pacific south of 20°N, q _s ′ (T _s ′) also greatly influences the low-frequency oscillation of LHF (SHF). Supported by National Natural Science Foundation of China (Grant No. 40675028) and National Basic Research Program of China (Grant No. 2006CB403600)