Measurements Of Suspended Particulate Matter Research Articles

The Impact of Flocculation on In Situ and Ex Situ Particle Size Measurements by Laser Diffraction

AbstractAccurate particle size distribution (PSD) measurements of suspended particulate matter (SPM) composed of flocs and aggregates are important to improve understanding of ecological and geomorphological processes, and for environmental engineering applications. PSDs can be measured in situ (in the field) using a submersible sensor, or ex situ (in the laboratory) using samples. The methodological choice is often guided by logistical factors, and the differences in PSDs acquired by in situ and ex situ measurements is of concern. In this study, a laser‐diffraction instrument (the LISST‐200X) was used to compare in situ and ex situ PSD measurements. Samples measured ex situ were stored for three consecutive weeks and measured each week in a laboratory using different stirrer speeds. We observed that ex situ measurements display a higher D50 (median particle size) than in situ measurements of the same sample (up to 613% larger, 112% on average). Our experiments show that the difference between in situ and ex situ measurements can be explained by flocculation of the riverine sediments during the first week of storage. During the subsequent ex situ measurements, the stirring results in a significantly lower D50. Ex situ measurements are therefore unsuitable for flocculated SPM. This study provides recommendations for optimizing PSD measurements by calculating the measurement times required to obtain robust PSD measurements (exceeding 3 min per sample), which are larger for field samples with coarser particles and wider PSDs.

The Potential of Multibeam Sonars as 3D Turbidity and SPM Monitoring Tool in the North Sea

Monitoring turbidity is essential for sustainable coastal management because an increase in turbidity leading to diminishing water clarity has a detrimental ecological impact. Turbidity in coastal waters is strongly dependent on the concentration and physical properties of particles in the water column. In the Belgian part of the North Sea, turbidity and suspended particulate matter (SPM) concentrations have been monitored for decades by satellite remote sensing, but this technique only focuses on the surface layer of the water column. Within the water column, turbidity and SPM concentrations are measured in stations or transects with a suite of optical and acoustic sensors. However, the dynamic nature of SPM variability in coastal areas and the recent construction of offshore windmill parks and dredging and dumping activities justifies the need to monitor natural and human-induced SPM variability in 3D instead. A possible solution lies in modern multibeam echosounders (MBES), which, in addition to seafloor bathymetry data, are also able to deliver acoustic backscatter data from the water column. This study investigates the potential of MBES as a 3D turbidity and SPM monitoring tool. For this purpose, a novel empirical approach is developed, in which 3D MBES water column and in-situ optical sensor datasets were collected during ship transects to yield an empirical relation using linear regression modeling. This relationship was then used to predict SPM volume concentrations from the 3D acoustic measurements, which were further converted to SPM mass concentrations using calculated densities. Our results show that these converted mean mass concentrations at the Kwinte and Westdiep swale areas are within the limits of the reported yearly averages. Moreover, they are in the same order of magnitude as the measured mass concentrations from Niskin water samples during each campaign. While there is still need for further improvement of acquisition and processing workflows, this study presents a promising approach for converting MBES water column data to turbidity and SPM measurements. This opens possibilities for improving future monitoring tools, both in scientific and industrial sectors.

Remote estimates of suspended particulate matter in global lakes using machine learning models

Suspended particulate matter (SPM) in lakes exerts strong impact on light propagation, aquatic ecosystem productivity, which co-varies with nutrients, heavy metal and micro-pollutant in waters. In lakes, SPM exerts strong absorption and backscattering, ultimately affects water leaving signals that can be detected by satellite sensors. Simple regression models based on specific band or hand ratios have been widely used for SPM estimate in the past with moderate accuracy. There are still rooms for model accuracy improvements, and machine learning models may solve the non-linear relationships between spectral variable and SPM in waters. We assembled more than 16,400 in situ measured SPM in lakes from six continents (excluding the Antarctica continent), of which 9640 samples were matched with Landsat overpasses within ±7 days. Seven machine learning algorithms and two simple regression methods (linear and partial least squares models) were used to estimate SPM in lakes and the performance were compared. To overcome the problem of imbalance datasets in regression, a Synthetic Minority Over-Sampling technique for regression with Gaussian Noise (SMOGN) was adopted in this study. Through comparison, we found that gradient boosting decision tree (GBDT), random forest (RF), and extreme gradient boosting (XGBoost) models demonstrated good spatiotemporal transferability with SMOGN processed dataset, and has potential to map SPM at different year with good quality of Landsat land surface reflectance images. In all the tested modeling approaches, the GBDT model has accurate calibration (n = 6428, R2 = 0.95, MAPE = 29.8%) from SPM collected in 2235 lakes across the world, and the validation (n = 3214, R2 = 0.84, MAPE = 38.8%) also exhibited stable performance. Further, the good performances were also exhibited by RF model with calibration (R2 = 0.93) and validation (R2 = 0.86, MAPE = 24.2%) datasets. We applied GBDT and RF models to map SPM of typical lakes, and satisfactory result was obtained. In addition, the GBDT model was evaluated by historical SPM measurements coincident with different Landsat sensors (L5-TM, L7-ETM+, and L8-OLI), thus the model has the potential to map SPM of lakes for monitoring temporal variations, and tracks lake water SPM dynamics in approximately the past four decades (1984–2021) since Landsat-5/TM was launched in 1984.

Spatio-temporal dynamics of suspended particulate matter in the middle Niger River using in-situ and satellite radiometric measurements

Study Region: Middle Niger River Basin (MNRB), Ansongo to Niamey, Sahel, West Africa.Study Focus: Although MNRB hydrology and the red flood phenomena have been addressed in the past literature, water quality parameters and suspended particulate matter (SPM) dynamics remain poorly known. SPM impacts dam silting, exacerbating flooding, and microbial water quality. This study couples in-situ SPM measurements to radiometric measurements by in-situ and satellite sensors to analyse the temporal and spatial evolution of SPM in the MNRB and assess the contribution of the local flood (red flood) to SPM in Niamey.New Hydrological Insights for the Region: SPM is composed of very fine kaolinites with a major mode around 200–300 nanometers which results in high reflectance in the visible and infrared bands. Radiometric measurements by both radiometer and Sentinel-2 MSI sensors are well correlated to in-situ SPM, allowing efficient spatio-temporal monitoring of SPM concentration. SPM increases very rapidly at the beginning of the rainy season, reaching a peak, characterized by very high SPM values, about one month before the red flood. Satellite data highlight the significant contribution of the right bank tributaries to SPM in the MNRB during this period. SPM then decreases and remains low despite the second runoff increase (black flood) arriving in Niamey after the end of the rainy season from the upper basin.

A Simple Empirical Band-Ratio Algorithm to Assess Suspended Particulate Matter from Remote Sensing over Coastal and Inland Waters of Vietnam: Application to the VNREDSat-1/NAOMI Sensor

VNREDSat-1 is the first Vietnamese satellite enabling the survey of environmental parameters, such as vegetation and water coverages or surface water quality at medium spatial resolution (from 2.5 to 10 m depending on the considered channel). The New AstroSat Optical Modular Instrument (NAOMI) sensor on board VNREDSat-1 has the required spectral bands to assess the suspended particulate matter (SPM) concentration. Because recent studies have shown that the remote sensing reflectance, Rrs(λ), at the blue (450–520 nm), green (530–600 nm), and red (620–690 nm) spectral bands can be assessed using NAOMI with good accuracy, the present study is dedicated to the development and validation of an algorithm (hereafter referred to as V1SPM) to assess SPM from Rrs(λ) over inland and coastal waters of Vietnam. For that purpose, an in-situ data set of hyper-spectral Rrs(λ) and SPM (from 0.47 to 240.14 g·m−3) measurements collected at 205 coastal and inland stations has been gathered. Among the different approaches, including four historical algorithms, the polynomial algorithms involving the red-to-green reflectance ratio presents the best performance on the validation data set (mean absolute percent difference (MAPD) of 18.7%). Compared to the use of a single spectral band, the band ratio reduces the scatter around the polynomial fit, as well as the impact of imperfect atmospheric corrections. Due to the lack of matchup data points with VNREDSat-1, the full VNREDSat-1 processing chain (atmospheric correction (RED-NIR) and V1SPM), aiming at estimating SPM from the top-of-atmosphere signal, was applied to the Landsat-8/OLI match-up data points with relatively low to moderate SPM concentration (3.33–15.25 g·m−3), yielding a MAPD of 15.8%. An illustration of the use of this VNREDSat-1 processing chain during a flooding event occurring in Vietnam is provided.

Human impact on suspended particulate matter in the Yellow River Estuary, China: Evidence from remote sensing data fusion using an improved spatiotemporal fusion method

Transport of suspended particulate matter (SPM) in estuarine waters plays an important role in regulating erosion-accretion and biogeochemical processes. In the Yellow River Estuary (YRE), artificial water and sediment regulation scheme (WSRS) and coastal engineering structures are the 2 typical anthropogenic activities affecting the spatiotemporal dynamics of estuarine SPM. The monitoring of SPM transport affected by such human activities requires SPM mapping at both high spatial and high temporal resolutions. In this study, we presented an improved Flexible Spatiotemporal Data Fusion (FSDAF) strategy with consideration of highly dynamic SPM variations in estuarine waters, and generated 30-m hourly SPM concentrations based on Landsat 8 OLI and GOCI datasets. The new strategy produced higher SPM estimation accuracy than the original FSDAF, with the relative percentage difference (RPD) decreasing from 29.75% to 5.31% using GOCI-derived hourly SPM as reference. With in situ SPM measurements as reference, the fused SPM concentrations had an RMSE of 12.09 mg/L and an RPD of 27.17%. Investigation of interday SPM variations before, during, and after the WSRS in 2018 revealed that the first WSRS significantly increased the SPM concentration and plume extent; new wetland with an area of 12.56 km2 was formed due to sediment accretion near the river mouth. The two groins offshore from the coastlines on the north and south sides of YRE exhibited obvious sediment trapping effects in that higher SPM concentrations on one side of each groin were found regardless of the turbidity modes and diurnal SPM variations; the trapping effects were associated with the number of groins and groin length. Intraday variations of SPM were influenced by tidal currents, with plume direction following the ebb and flooding tidal current direction. The inter- and intraday characteristics of the 30-m hourly SPM dynamics facilitate the detailed analysis of the sediment transport associated with human activities.

An Algorithm to Estimate Suspended Particulate Matter Concentrations and Associated Uncertainties from Remote Sensing Reflectance in Coastal Environments

Suspended Particulate Matter (SPM) is a major constituent in coastal waters, involved in processes such as light attenuation, pollutant propagation, and waterways blockage. The spatial distribution of SPM is an indicator of deposition and erosion patterns in estuaries and coastal zones and a necessary input to estimate the material fluxes from the land through rivers to the sea. In-situ methods to estimate SPM provide limited spatial data in comparison to the coverage that can be obtained remotely. Ocean color remote sensing complements field measurements by providing estimates of the spatial distributions of surface SPM concentration in natural waters, with high spatial and temporal resolution. Existing methods to obtain SPM from remote sensing vary between purely empirical ones to those that are based on radiative transfer theory together with empirical inputs regarding the optical properties of SPM. Most algorithms use a single satellite band that is switched to other bands for different ranges of turbidity. The necessity to switch bands is due to the saturation of reflectance as SPM concentration increases. Here we propose a multi-band approach for SPM retrievals that also provides an estimate of uncertainty, where the latter is based on both uncertainties in reflectance and in the assumed optical properties of SPM. The approach proposed is general and can be applied to any ocean color sensor or in-situ radiometer system with red and near-infra-red bands. We apply it to six globally distributed in-situ datasets of spectral water reflectance and SPM measurements over a wide range of SPM concentrations collected in estuaries and coastal environments (the focus regions of our study). Results show good performance for SPM retrieval at all ranges of concentration. As with all algorithms, better performance may be achieved by constraining empirical assumptions to specific environments. To demonstrate the flexibility of the algorithm we apply it to a remote sensing scene from an environment with highly variable sediment concentrations.

Coupled approach for radiometric calibration and parameter retrieval to improve SPM estimations in turbid inland/coastal waters.

High-precision radiometric calibration (RC) coefficients are required to retrieve reliable water quality parameter products in turbid inland/coastal waters. However, unreliable RC coefficients when satellite sensors lack accurate and in-time RC may lead to pronounced uncertainties in the products through error propagation. To address this issue, a novel approach for estimating water quality parameters, taking suspended particulate matter (SPM) as a case, was proposed by coupling the procedures of RC and SPM model development. The coupled models were established using digital numbers (DNs) from target sensors and "in-situ" SPM measurements from concurrent well-calibrated reference sensors, with the RC coefficients introduced as unknown model parameters. The approach was tested and validated in varied Chinese inland/coastal regions, including the Hongze lake (HL), Taihu lake (TL), and Hangzhou bay (HB). The results show: (1) the DN-based SPM models can achieve a degree of accuracy comparable to reflectance-based SPM models with determination coefficients (R2) of 0.94, 0.92, and 0.72, and root-mean-square errors (RMSE) of 7.02 mg/L, 15.73 mg/L, and 619.2 mg/L for the HL, TL, and HB, respectively, and the biases less than 3% between the derived and official gain RC coefficients; (2) the uncertainty of SPM products increases exponentially as the RC uncertainty increases for exponential reflectance-based SPM models; (3) the DN-based SPM models are less sensitive to the uncertainties of atmospheric correction and RC coefficients, while the reflectance-based models suffer deeply. This study provides encouraging results to the improvement of SPM retrieval using the DN-based models by coupling RC and SPM retrieving processes, especially for sensors without precise RC coefficients.

Réévaluation des apports moyens de matières en suspension de l'Arve au Rhône

L'Arve est le principal contributeur au flux de matières en suspension (MES) du Rhône entre le lac Léman et Lyon. Une évaluation fiable des apports moyens de MES de l'Arve est cruciale pour la connaissance et la gestion des flux sédimentaires sur ce secteur du Rhône et à travers ses aménagements hydroélectriques. Cette étude vise à réévaluer les flux moyens de l'Arve en suspension fine, en croisant les données historiques avec les flux de MES de référence pour les années 2012 à 2017 issus du suivi turbidimétrique en continu à la station de Genève Bout-du-Monde de l'Observatoire des sédiments du Rhône. Ce jeu de données a permis d'évaluer les deux méthodes de calcul des flux mises en œuvre par le Service hydrologique national suisse pour les périodes avec des mesures discontinues des MES : la méthode des débits classés et la courbe de tarage sédimentaire à deux segments. En combinant au mieux ces méthodes, le flux moyen interannuel entre 1965 et 2017 est estimé à 0,68 Mt/an avec un écart-type de 0,29 Mt/an. Cette valeur est cohérente avec le flux moyen mesuré par la station turbidimétrique entre 2012 et 2017 (0,63 Mt) et avec un suivi historique pour l'année 1890 (0,71 Mt) ; en revanche, elle est nettement inférieure à l'estimation précédemment proposée par l'étude globale Rhône (2000), comprise entre 1,0 et 3,6 Mt/an, qui inclut sans doute la suspension graduée de sables et limons grossiers, très mal connue. À partir de relevés bathymétriques et granulométrique des dépôts, nous avons estimé que la retenue de Verbois intercepte approximativement 0,1 Mt/an de particules grossières issues de l'Arve et environ la moitié des apports de MES.

The optical properties of river and floodplain waters in the Amazon River Basin: Implications for satellite‐based measurements of suspended particulate matter

AbstractSatellite images can now be used to assess river sediment discharge, and systematic studies over rivers and lakes are required to support such applications and document the variability of inland water optical properties at the watershed scale. The optical properties of the Amazon Basin waters were analyzed from in situ measurements of the remote sensing reflectance (Rrs) at 279 stations and downwelling diffuse attenuation coefficients (Kd) at 133 stations. Measurements of the apparent optical properties, suspended particulate matter (SPM) contents, and characteristics and colored dissolved organic matter (CDOM) absorption spectra were performed during 16 cruises along the main Amazonian Rivers draining the Andes and for some tributaries. Surface‐suspended sediment granulometry and mineralogy showed a stable distribution at the catchment scale, even over large distances and between tributaries. The particle number‐size distribution was best described using a segmented distribution with a slope of 2.2 for the fine range (1–15 µm), and the CDOM absorption coefficient at 440 nm varied from 1.8 to 7.9 m−1. Overall, both Rrs and Kd were strongly correlated with SPM, although strong CDOM absorption limited the use of the blue spectrum. Reflectance saturation from blue to red was observed at approximately 100 g m−3, whereas the near‐infrared (NIR) wavelength enabled the monitoring of the full SPM range (5–620 g m−3). In contrast, Kd showed no saturation for SPM from green to NIR, and a linear model was calculated. The use of the reflectance ratio was investigated and shown to improve the suspended sediment concentration retrieval performance.

Reductions of PM2.5 Air Concentrations and Possible Effects on Premature Mortality in Japan

The current study estimates premature mortality caused by long-term exposure to elevated concentrations of PM2.5 (particulate matter with aerodynamic diameter equal to or less than 2.5 μm) in Japan from 2006 to 2009. The premature mortality is calculated based on a relative risk of 1.04 (95 % CI, 1.01–1.08) per 10 μg m−3 increase above the annual mean limit of 10 μg m−3 taken from the World Health Organization Air Quality Guidelines. The spatiotemporal variations of PM2.5 are estimated based on the measurements of suspended particulate matter (SPM) (with aerodynamic diameter approximately less than 7.0 μm) at 1,843 monitors. The improvements of air quality in Japan by reducing the emissions of SPM from 2006 to 2009 could save 3,602 lives based on a reduction target of 10 μg m−3 annual mean concentration. This finding could be a tangible benefit gained by reducing the emissions of particulate matter in Japan.

Fine sediment transport model for river influenced microtidal shelf seas with application to the Thermaikos Gulf (NW Aegean Sea)

Modelling the transport of fine sediments in the marine environment is a highly complex task with a broad field of application. Various processes take place and interact with one another to determine the movement of fine sedimentary particles in the aquatic domain. Amongst these processes stratification significantly affects the vertical propagation of a sedimentary plume, especially in areas of freshwater influence, with the possibility of matter entrapment and accumulation along the interface; this possibility is higher the finer the sedimentary matter is. The proposed modelling approach describes the physical processes that take place in the water column (advection, dispersion, coagulation, settling, effects of stratification), at the boundary of the seabed (benthic shear) and the mass-exchanges between the two (deposition, consolidation, resuspension, erosion). The Fine Sediment Transport Model was applied in the gulf of Thermaikos (NW Aegean Sea), an area of significant freshwater and riverine sediment inflow, considering the major rivers of the domain as sources of particulate matter. The results were, generally, in agreement with available in-situ measurements of suspended particulate matter. In cases of significant deviations between simulation and measurement, the source of the error did not lie within the modelling approach, but was due to the considered input parameters. The investigation revealed the existence of transport and sedimentation patterns related to the riverine source of the material and the individual parts of the gulf. The sedimentation rates were estimated at 18, 7 and 3mm/yr locally at the outflows of Aliakmon, Axios and Pinios, respectively, while the areas of high sediment accumulation coincided with locations where the benthic material ranges from very fine to fine silt.

Estimating sediment and caesium-137 fluxes in the Ribble Estuary through time-series airborne remote sensing

High spatial and temporal resolution airborne imagery were acquired for the Ribble Estuary, North West England in 1997 and 2003, to assess the application of time-series airborne remote sensing to quantify total suspended sediment and radionuclide fluxes during a flood and ebb tide sequence. Concomitant measurements of suspended particulate matter (SPM) and water column turbidity were obtained during the time-series image acquisition for the flood and ebb tide sequence on the 17th July 2003 to verify the assumption of a vertically well mixed estuary and thus justifying the vertical extrapolation of spatially integrated estimate of surface SPM. The 137Cs activity concentrations were calculated from a relatively stable relationship between SPM and 137Cs for the Ribble Estuary. Total estuary wide budgets of sediment and 137Cs were obtained by combining the image-derived estimates of surface SPM and 137Cs with estimates of water volume from a two-dimensional hydrodynamic model (VERSE) developed for the Ribble Estuary. These indicate that around 10,000 tonnes of sediment and 2.72 GBq of 137Cs were deposited over the tidal sequence monitored in July 2003. This compared favourably with bed height elevation change estimated from field work. An uncertainty analysis on the total sediment and 137Cs flux yielded a total budget of the order of 40% on the final estimate. The results represent a novel approach to providing a spatially integrated estimate of the total net sediment and radionuclide flux in an intertidal environment over a flood and ebb tide sequence.

Towards continuous long-term measurements of suspended particulate matter (SPM) in turbid coastal waters

The dynamics of sediment transport in the East Frisian Wadden Sea are important for the coastal zone and for ecosystem functioning. The tidal inlets between the East Frisian islands connect the back-barrier intertidal flats to the North Sea. Here, concentrations of suspended particulate matter (SPM) in the water column are highly variable, depending on weather conditions and tides. In order to estimate the nature and quantity of sediment transport, in situ measurements were carried out at a Time Series Station in the tidal inlet between the islands of Spiekeroog and Langeoog. This study shows the suitability of multispectral transmissometry (MST) for obtaining long-term SPM measurements with high resolution. The comparability of this technique to the standard filter method and the laser diffraction method [laser in situ scattering and transmissometry (LISST)] is demonstrated. In addition, the Junge coefficients derived from both MST and LISST measurements are compared. A time series of SPM data covering nearly 4 months is presented. As a major result, the data reveal that a single storm surge can have less impact on SPM dynamics than longer-lasting gales. This high-resolution long-term data set is very valuable for modelling suspended matter flux. It also provides background information for studying the influence of SPM dynamics on coastal sediments.

Aerosol characteristics at Patiala during ICARB—2006

The spectral AOD measurements have been made for the first time over Patiala during multi-platform field campaign ICARB—2006 using a Multi-Wavelength Radiometer (MWR) along with the suspended particulate matter measurements with a high volume sampler. Spectral AOD has higher values in May in comparison to March and April. The monthly mean AOD values at 500 nm are 0.26 ± 0.08, 0.36 ± 0.19 and 0.58 ± 0.20 for the months of March, April and May respectively. The mean AOD is more during afternoon in comparison to forenoon at all wavelengths. The atmospheric turbidity is higher in May and is attributed to dust transported by southerly winds prevailing during this month. The Angstrom parameter α varies between zero and 0.68 while β ranges from 0.1 to 0.9. The columnar water vapour content ranges from 0.12 to 2.92 cm, having a mean value of 1.06 ± 0.648 cm. The mean total suspended particulate matter is 334.41 ± 97.56 μgm/m3, an indication of high aerosol loading over Patiala during the campaign period.

Retrieval of suspended particulate matter concentrations in the Danube River from Landsat ETM data

Alternations in river channel morphology result in a disturbed natural transport of suspended particulate matter (SPM). Suspended particulate matter serves as a transport medium for various pollutants, e.g. heavy metals. It is therefore important to understand how artificial obstructions alter the natural transport of suspended matter. Measurements of SPM in rivers are traditionally carried out during in situ sampling campaigns, which can provide only a limited view of the actual spatial distribution of suspended matter over large distances. Several authors have studied how space-borne remote sensing could be used for mapping of water quality in standing waters, but with only little attention paid to rivers. This paper describes the methodology how a Landsat ETM image was used to map the spatial patterns of SPM in the Slovak portion of the Danube River. Results of our investigation reveal that the Danube River in Slovakia exhibits gradual longitudinal decrease in concentrations of SPM. Based on a strong relationship between the Landsat near-infrared band (TM4) and field measurements, we developed a map of suspended particulate matter in the Danube River with a standard error (SE) of 2.92 mg/L. This study aims to show how archived satellite data and historical water quality data can be used for monitoring of SPM in large rivers. A methodology describing the minimum samples required for sufficiently accurate results is discussed in this paper also.

An assessment of soil erosion and freshwater suspended solid estimates for continental‐scale environmental modelling

AbstractIn modelling the environmental fate of chemicals, suspended matter in surface water may play a relevant role as it controls the partitioning of substances between dissolved and adsorbed form. This is particularly important for hydrophobic/non‐polar chemicals with high octanol/water partition coefficient (Kow).For a wide class of chemicals, it is then important to evaluate suspended solids concentration in surface waters in order to model the mechanisms of their transport in the environment. Reported values of suspended particulate matter (SPM) or total suspended solids (TSS) range from less than 1 to more than 200 mg l−1, with peaks even orders of magnitude higher. A number of studies highlight that a huge variability is intrinsic for this parameter. Nevertheless, predictive models and estimation methods have been proposed that can provide information on relevant spatial patterns of SPM or TSS. The paper examines two families of models, namely models oriented to sediment concentration or flux estimates and models oriented to soil erosion estimates, which have been widely used at the European scale. Predicted sediment concentration from these models is compared with available TSS and SPM measurements. The analysis points out how soil erosion oriented models can be seen as favourable to depict the fate of pollutants removed from soil, while sediment yield oriented models better fit for pollutants directly emitted to water and then subject to sequestration by solids. Based on the results of the analyses, a blueprint for description of the sediment compartment in chemical fate and transport models is proposed. Copyright © 2007 John Wiley & Sons, Ltd.

Multi-year trend in fine and coarse particle mass, carbon, and ions in downtown Tokyo, Japan

Long-term measurements of suspended particulate matter (SPM, <7 μm), PM fine (<2.1 μm), and PM coarse (2.1–7 μm) were obtained from a traffic-dominated site in Tokyo, Japan for the period 1994–2004 to evaluate the effects of emission reduction measures for motor-vehicle emissions. SPM decreased from 1996 forward, with all of the downward trend attributable to the PM fine fraction. Annual average PM coarse was constant over the 10-yr period. From 1996 to 2004, PM fine decreased at a rate of 2.37 μg m −3 yr −1 for PM 2.1 mass. Most of this decrease was attributable to decreases in organic and elemental carbon. This decrease is consistent with fleet penetration of engines and fuels that complied with a stringent Japanese emission reduction limit which began to take effect in 1994. Sulfate and nitrate concentrations did not decrease over this period. Evidence of Asian dust storm contributions was found in elevated PM coarse and water-soluble calcium levels during the spring.

Improved regional algorithm to retrieve total suspended particulate matter using IRS-P4 ocean colour monitor data

Data from seven validation campaigns in the coastal waters of the Bay of Bengal (BOB) were used to develop a regional SPM (suspended particulate matter) algorithm. The in situ data sets for this algorithm are obtained from 86 stations with optical and 68 stations with total SPM measurements encompassing SPM concentrations between 10 and 189 mg l −1 ,w here most of the observations are in shallow (case 2, average depth ∼45 m) waters and a limited number of samples in open case 1 waters. From simple statistical analyses we found a close relationship between SPM concentration and diffuse attenuation coefficient at 555 nm (K 555) in the BOB coastal waters. The linear regression to the fit has ac oeff icient of determination (r 2 ) 0.96 with a standard error of estimates (σ )12. 5m g l −1 for the above SPM range. The algorithm relating K 555 to [L wn443/L wn670] has been evaluated through a regression analysis of radiometric profiles in the BOB. However, the new SPM algorithm overestimates in case 1 waters (SPM range 0.05–25. 0m g l −1 ), wher ea spectra lr eflectance ratio algorithm (Tassan 1994 Appl. Opt. 33 2369–78) appears to produce better results. An integration of both the approaches performs better in generating the routine IRS-P4 OCM (ocean colour monitor) SPM mapped product.

Results from an intensive measurement programme for suspended particulate matter in a region of the Irish Sea between Anglesey and the Isle of Man

Suspended particulate matter (SPM) plays an important role in the transport of metals and other contaminants in the marine environment. To varying degrees dissolved metals are scavenged by suspended particles and this can have a significant impact on the transport and dispersion of the metal. In contaminated areas, such as the Irish Sea, the SPM becomes increasingly important in understanding the transport and fate of contaminants. Despite its importance, measurements of SPM in the Irish Sea are sparse. This paper presents measured SPM concentrations from a long-term sampling campaign from 25 sites in an area of the Irish Sea between Anglesey and the Isle of Man which were sampled over 14 months (July 1998–August 1999) at 5 and 30 m depth. In total 585 measurements were made. A transmissometer was also deployed on some occasions to look at the depth dependence of SPM. Results showed an average SPM concentration of 2.14 mg l −1 with a maximum value of 6.28 mg l −1 and a minimum of 0.30 mg l −1. The strongest relationship found was between the SPM and the spring-neap tidal cycle, which outweighed any seasonal variation. Spatially, the SPM was highest in the south and east of the region sampled and is probably due to higher tidal velocities and greater availability of fine sediment in these areas. There was no evidence of SPM varying with depth in the water column.