Found 9719 publications. Showing page 385 of 389:
Water column distribution of mercury species in permanently stratified aqueous environments
Biogeochemical structures of three permanently stratified waterbodies were studied: a sea water basin (the Black Sea), an estuary (Hunnbunn fjord), and a freshwater lake (Nordbytjernet), with focus on the distributions of methylmercury (MeHg) and total mercury (THg). THg concentrations were similar in the sea water basin (0.2–1.8 ng/L) and the freshwater lake (0.8–1.2 ng/L), but significantly higher in the estuary (0.6–9.4 ng/L). An increase in the MeHg concentration and MeHg/THg ratio were found in the redox zone in all three basins, indicating bacterial production of MeHg in the aqueous phase. In the lake and estuary, the maximum MeHg concentration and MeHg/THg ratio were found in samples located closest to the bottom sediments, likely due to the formation of MeHg in surface sediments and subsequent diffusion to the overlying waters.
Springer
2018
Hulun Lake, the largest inland steppe lake in China, is encountering severe water quality degradation. Estuaries play important roles in material and energetic exchange between rivers and lakes. The water quality at the estuaries of Hulun Lake directly reflects the impact of both human activities and natural factors on the lake’s overall water quality, especially during rainfall events. From July 28, 2021, to August 4, 2021, water samples from 62 sites were collected in the three estuaries of Hulun Lake before and after a moderate rainfall event. 13 water parameters, including dissolved oxygen (DO), Turbidity (Tur), Total Nitrogen (TN), Total Phosphorus (TP), Total Organic Nitrogen (TON), and Total Organic Phosphorus (TOP) were measured. The spatio-temporal distribution of water quality in the estuaries was assessed based on water quality index (WQI). Besides, an improved approach integrating stepwise linear regression (SLR) and principal component analysis (PCA) was utilized to construct a WQImin model for an effective assessment of water quality in these estuaries. Furthermore, the absolute principal component scores-multiple linear regression (APCS-MLR) model was employed to identify and quantify the environmental drivers underlying the water quality in the estuaries. The results of WQI indicated that the water quality of the sites in the estuaries of Hulun Lake was “medium” or “poor”, both before and after the rainfall, with a general deterioration in water quality in response to the rainfall. The simplified WQImin model consisted of 5 crucial parameters (i.e., TN, TP, ammonium (NH4+-N), Tur, and permanganate index (CODMn)), and it performed well without parameter weights. Spatial differences in some water parameters among the estuaries were detected, which were attributed to the natural factors and human activities upstream. The principal environmental factors affecting the water quality in the estuaries consisted of hydrodynamic processes, internal phosphorus release, external phosphorus input, external nitrogen input, nitrification in the estuaries, and external organic input and internal organic release. Therefore, we propose basin management strategies such as limiting grazing pressure, adopting enclosed pasture, wetland restoration, optimizing water renewal cycle in Hulun Lake, and transboundary water quality management to tackle water contamination in Hulun Lake.
Elsevier
2024
2012
2017
2017
2019
In this study we apply two methods for data collection that are relatively new in the field of atmospheric science. The two developed methods are designed to collect essential geo-localized information to be used as input data for a high resolution emission inventory for residential wood combustion (RWC). The first method is a webcrawler that extracts openly online available real estate data in a systematic way, and thereafter structures them for analysis. The webcrawler reads online Norwegian real estate advertisements and it collects the geo-position of the dwellings. Dwellings are classified according to the type (e.g., apartment, detached house) they belong to and the heating systems they are equipped with. The second method is a model trained for image recognition and classification based on machine learning techniques. The images from the real estate advertisements are collected and processed to identify wood burning installations, which are automatically classified according to the three classes used in official statistics, i.e., open fireplaces, stoves produced before 1998 and stoves produced after 1998. The model recognizes and classifies the wood appliances with a precision of 81%, 85% and 91% for open fireplaces, old stoves and new stoves, respectively. Emission factors are heavily dependent on technology and this information is therefore essential for determining accurate emissions. The collected data are compared with existing information from the statistical register at county and national level in Norway. The comparison shows good agreement for the proportion of residential heating systems between the webcrawled data and the official statistics. The high resolution and level of detail of the extracted data show the value of open data to improve emission inventories. With the increased amount and availability of data, the techniques presented here add significant value to emission accuracy and potential applications should also be considered across all emission sectors.
2018
Public Health Institute of Belgrade
2019
Vinca Institute of Nuclear Sciences
2021
2013
2015
2017
Wetland emission and atmospheric sink changes explain methane growth in 2020
Atmospheric methane growth reached an exceptionally high rate of 15.1 ± 0.4 parts per billion per year in 2020 despite a probable decrease in anthropogenic methane emissions during COVID-19 lockdowns. Here we quantify changes in methane sources and in its atmospheric sink in 2020 compared with 2019. We find that, globally, total anthropogenic emissions decreased by 1.2 ± 0.1 teragrams of methane per year (Tg CH4 yr−1), fire emissions decreased by 6.5 ± 0.1 Tg CH4 yr−1 and wetland emissions increased by 6.0 ± 2.3 Tg CH4 yr−1. Tropospheric OH concentration decreased by 1.6 ± 0.2 per cent relative to 2019, mainly as a result of lower anthropogenic nitrogen oxide (NOx) emissions and associated lower free tropospheric ozone during pandemic lockdowns. From atmospheric inversions, we also infer that global net emissions increased by 6.9 ± 2.1 Tg CH4 yr−1 in 2020 relative to 2019, and global methane removal from reaction with OH decreased by 7.5 ± 0.8 Tg CH4 yr−1. Therefore, we attribute the methane growth rate anomaly in 2020 relative to 2019 to lower OH sink (53 ± 10 per cent) and higher natural emissions (47 ± 16 per cent), mostly from wetlands. In line with previous findings, our results imply that wetland methane emissions are sensitive to a warmer and wetter climate and could act as a positive feedback mechanism in the future. Our study also suggests that nitrogen oxide emission trends need to be taken into account when implementing the global anthropogenic methane emissions reduction pledge.
2022
2011
WG1: Ammonia emission datasets and deposition measurements in Europe. Powerpoint presentation. NILU F
2005