Commercial returns of sun-protection products: the L’Oréal France case
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The AERMOD-ISC dispersion model has been used to study the impact SO 2 emitted from power stations in Kuwait.SO 2 emissions from fifteen stacks were studied to evaluate the pollutant dispersion patterns and the risk of nearby populations being negatively affected by such emission.One year's meteorological data was used for simulating the ground level concentrations of SO 2 .The level was estimated based on a model simulating the concentration on an hourly, daily and annual basis.The air quality was monitored at four different residential areas over the course of a year.The simulated concentrations were validated by comparing them with the observed values at four locations in residential areas.The results demonstrated that there is a great similarity in the simulated concentrations with observed values.The model performance was also found to be satisfactory.The hourly and daily concentrations of the simulated model exceeded the KW-EPA limits.This indicates that there is a significant influence of SO 2 emission from the power station in ambient air quality.
AERMOD
Ground level
Emission inventory
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SWAT model
Baseline (sea)
Representative Concentration Pathways
Chesapeake bay
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Moderate-resolution imaging spectroradiometer
Spectroradiometer
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Urban runoff
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Despite covering only 2–6% of land, wetland ecosystems play an important role at the local and global scale. They provide various ecosystem services (carbon dioxide sequestration, pollution removal, water retention, climate regulation, etc.) as long as they are in good condition. By definition, wetlands are rich in water ecosystems. However, ongoing climate change with an ambiguous balance of rain in a temperate climate zone leads to drought conditions. Such periods interfere with the natural processes occurring on wetlands and restrain the normal functioning of wetland ecosystems. Persisting unfavorable water conditions lead to irreversible changes in wetland habitats. Hence, the monitoring of habitat changes caused by an insufficient amount of water (plant water stress) is necessary. Unfortunately, due to the specific conditions of wetlands, monitoring them by both traditional and remote sensing techniques is challenging, and research on wetland water stress has been insufficient. This paper describes the adaptation of the thermal water stress index, also known as the crop water stress index (CWSI), for wetlands. This index is calculated based on land surface temperature and meteorological parameters (temperature and vapor pressure deficit—VPD). In this study, an unmanned aerial system (UAS) was used to measure land surface temperature. Performance of the CWSI was confirmed by the high correlation with field measurements of a fraction of absorbed photosynthetically active radiation (R = −0.70) and soil moisture (R = −0.62). Comparison of the crop water stress index with meteorological drought indices showed that the first phase of drought (meteorological drought) cannot be detected with this index. This study confirms the potential of using the CWSI as a water stress indicator in wetland ecosystems.
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Water quality is a key consideration for urban stormwater harvesting via aquifers. This study assessed catchment spill management options based on a calibrated dynamic wave routing model of stormwater flow in an urban catchment. The study used measured travel times, pluviometer and gauging station observations from 21 storms to calibrate a stormwater model to simulate transport of pollutants from spill locations to the point of harvest. The simulations considered the impact of spill locations, spill durations, storm intensities and storm durations on the pollutant concentration at the point of harvest and travel time of a pollutant spill to the harvesting point. During dry weather, spill events travelled slower than spills occurring during wet weather. For wet weather spills, the shortest travel times tended to occur in higher intensity storms with shorter duration, particularly when a spill occurred in the middle of the storm. Increasing the intensity of rainfall reduced the peak concentration of pollutant at the harvest point via dilution, but it also reduced the time of travel. On a practical level, due to the short response times in urban catchments, management of spills should be supported by automated detection/diversion systems to protect stormwater harvesting schemes.
First flush
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Soil moisture impacts the biosphere–atmosphere exchange of CO2 and CH4 and plays an important role in the terrestrial carbon cycle. A better representation of soil moisture would improve coupled carbon–water dynamics in terrestrial ecosystem models and could potentially improve model estimates of large-scale carbon fluxes and climate feedbacks. Here, we investigate using soil moisture observations from the Soil Moisture Active Passive (SMAP) satellite mission to inform simulated carbon fluxes in the global terrestrial ecosystem model LPJ-wsl. Results suggest that the direct insertion of SMAP reduces the bias in simulated soil moisture at in situ measurement sites by 40%, with a greater improvement at temperate sites. A wavelet analysis between the model and measurements from 26 FLUXNET sites suggests that the assimilated run modestly reduces the bias of simulated carbon fluxes for boreal and subtropical sites at 1–2-month time scales. At regional scales, SMAP soil moisture can improve the estimated responses of CO2 and CH4 fluxes to extreme events such as the 2018 European drought and the 2019 rainfall event in the Sudd (Southern Sudan) wetlands. The simulated improvements to land–surface carbon fluxes using the direct insertion of SMAP are shown across a variety of timescales, which suggests the potential of SMAP soil moisture in improving the model representation of carbon–water coupling.
Soil carbon
Terrestrial ecosystem
Water cycle
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Ten-year water quality,eutrophication condition and main pollution indices in Taihu Lake were analyzed using monitoring data from 1997 to 2006.The results show that Taihu Lake was mostly polluted by organic matter,and water quality deteriorated with eutrophication.Great effort is needed to control water pollution in Taihu Lake.
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Spatially disaggregated estimates of over 131 stream-flow, ground water, and reservoir evaporation monthly time series in California have been created for 12 different climate warming scenarios for a 72-year period. Such disaggregated hydrologic estimates of multiple hydrologic cycle components are important for impact and adaptation studies of California's water system. A statewide trend of increased winter and spring runoff and decreased summer runoff is identified. Without operations modeling, approximate changes in water availability are estimated for each scenario. Even most scenarios with increased precipitation result in less available water because of the current storage systems' inability to catch increased winter streamflow in compensation for reduced summer runoff. The water availability changes are then compared with estimated changes in urban and agricultural water uses in California between now and 2100. The methods used in this study are relatively simple, but the results are qualitatively consistent with other studies focusing on the hydrologies of single basins or surface water alone.
Water cycle
Hydrological modelling
Potential evaporation
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Abstract. The Paris Agreement set a long-term temperature goal of holding the global average temperature increase to below 2.0 ℃ above pre-industrial levels, and pursuing efforts to limit this to 1.5 ℃, it is therefore important to understand the impacts of climate change under 1.5 ℃ and 2.0 ℃ warming scenarios for climate adaptation and mitigation. Here, climate scenarios by four Global Circulation Models (GCMs) for the baseline (2006–2015), 1.5 ℃ and 2.0 ℃ warming scenarios (2106–2115) were used to drive the validated Variable Infiltration Capacity (VIC) hydrological model to investigate the impacts of global warming on river runoff and Terrestrial Ecosystem Water Retention (TEWR) in China. The trends in annual mean temperature, precipitation, river runoff and TEWR were analysed at the grid and basin scale. Results showed that there were large uncertainties in climate scenarios from the different GCMs, which led to large uncertainties in the impact assessment. The differences among the four GCMs were larger than differences between the two warming scenarios. The interannual variability of river runoff increased notably in areas where it was projected to increase, and the interannual variability increased notably from 1.5 ℃ warming scenario to 2.0 ℃ warming scenario. By contrast, TEWR would remain relatively stable. Both extreme low and high river runoff would increase under the two warming scenarios in most areas in China, with high river runoff increasing more. And the risk of extreme river runoff events would be higher under 2.0 ℃ warming scenario than under 1.5 ℃ warming scenario in term of both extent and intensity. River runoff was significantly positively correlated to precipitation, while increase in maximum temperature would generally cause river runoff to decrease through increasing evapotranspiration. Likewise, precipitation also played a dominant role in affecting TEWR. Our findings highlight climate change mitigation and adaptation should be taken to reduce the risks of hydrological extreme events.
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