ALBERT

Description: We present a dataset of dissolved methane (CH4) in the East China Sea (ECS) during five cruises in March, May, August, October and December 2011. CH4 distribution in this region showed pronounced spatial and seasonal variability due to the complex mixing of different water masses and other variables. Surface CH4 concentrations gradually decreased from the coast to the open sea, with maximum values occurring near Changjiang estuary or outside the Hangzhou Bay. The annual mean CH4 concentration of the surface layer was 9.1 ± 1.6 nmol L-1 in the coastal area, which was nearly twice as large as that in the open sea (4.3 ± 1.3 nmol L-1). CH4 was distributed evenly from the surface to the bottom in the shelf region during March and December, while it increased gradually with depth during May and October. CH4 depth profiles exhibited various distribution features along the coast, in the middle and on the edge of continental shelf. CH4 levels at the bottom were generally higher than at the surface during all seasons, indicating obvious CH4 sources from sediments. Incubation experiments of sediment cores onboard suggested that sediment release was an important source of CH4 in the water column of the ECS. We estimated that the annual average CH4 release rate from sediments was about 1.11 μmol·m-2·d-1 on the continental shelf of the ECS. The maximum CH4 concentration and sediment-water CH4 flux both occurred in summer, which might be related with the occurrence of hypoxia in the bottom water. Surface seawater of the ECS was oversaturated with CH4 relative to the atmosphere over most of the five cruises, indicating that the ECS was a net source of atmospheric CH4. The annual mean area-weighted sea-air flux density of CH4 in the ECS was estimated to be about 10.7 μmol·m-2·d-1 in 2011. Accordingly, an area-weighted, seasonally adjusted annual rate of CH4 efflux was determined to be 2.98 × 109 mol yr-1 (∼0.05 Tg CH4 yr-1) from the ECS to the atmosphere.

Description: Streptomyces, a branch of aerobic Gram-positive bacteria represents the largest genus of actinobacteria. The streptomycetes are characterized by a complex secondary metabolism and produce over two-thirds of the clinically used natural antibiotics today. Here we report the draft genome sequence of a Streptomyces strain PP-C42 isolated from the marine environment. A subset of unique genes and gene clusters for diverse secondary metabolites as well as antimicrobial peptides (AMPs) could be identified from the genome, showing great promise as a source for novel bioactive compounds

Description: Air pollution is one of the most pressing environmental issues in the Kathmandu Valley, where the capital city of Nepal is located. We estimated emissions from two of the major source types in the valley (vehicles and brick kilns) and analyzed the corresponding impacts on regional air quality. First, we estimated the on-road vehicle emissions in the valley using the International Vehicle Emissions (IVE) model with local emissions factors and the latest available data for vehicle registration. We also identified the locations of the brick kilns in the Kathmandu Valley and developed an emissions inventory for these kilns using emissions factors measured during the Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE) field campaign in April 2015. Our results indicate that the commonly used global emissions inventory, the Hemispheric Transport of Air Pollution (HTAP_v2.2), underestimates particulate matter emissions from vehicles in the Kathmandu Valley by a factor greater than 100. HTAP_v2.2 does not include the brick sector and we found that our sulfur dioxide (SO2) emissions estimates from brick kilns are comparable to 70 % of the total SO2 emissions considered in HTAP_v2.2. Next, we simulated air quality using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) for April 2015 based on three different emissions scenarios: HTAP only, HTAP with updated vehicle emissions, and HTAP with both updated vehicle and brick kilns emissions. Comparisons between simulated results and observations indicate that the model underestimates observed surface elemental carbon (EC) and SO2 concentrations under all emissions scenarios. However, our updated estimates of vehicle emissions significantly reduced model bias for EC, while updated emissions from brick kilns improved model performance in simulating SO2. These results highlight the importance of improving local emissions estimates for air quality modeling. We further find that model overestimation of surface wind leads to underestimated air pollutant concentrations in the Kathmandu Valley. Future work should focus on improving local emissions estimates for other major and underrepresented sources (e.g., crop residue burning and garbage burning) with a high spatial resolution, as well as the model's boundary-layer representation, to capture strong spatial gradients of air pollutant concentrations.