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Cellular senescence in normal physiology

Science - Thu, 06/20/2024 - 05:58
Science, Volume 384, Issue 6702, Page 1300-1301, June 2024.

Sex-based differences affect conservation

Science - Thu, 06/20/2024 - 05:58
Science, Volume 384, Issue 6702, Page 1309-1310, June 2024.

Plastic foam pollution from Chinese fisheries

Science - Thu, 06/20/2024 - 05:58
Science, Volume 384, Issue 6702, Page 1310-1310, June 2024.

Sustainable development in global border regions

Science - Thu, 06/20/2024 - 05:58
Science, Volume 384, Issue 6702, Page 1309-1309, June 2024.

No place like home

Science - Thu, 06/20/2024 - 05:58
Science, Volume 384, Issue 6702, Page 1286-1290, June 2024.

Wheat scientists unveil historic ‘gold mine’

Science - Thu, 06/20/2024 - 05:58
Science, Volume 384, Issue 6702, Page 1280-1281, June 2024.

As U.K. election nears, major parties reveal their science plans

Science - Thu, 06/20/2024 - 05:58
Science, Volume 384, Issue 6702, Page 1281-1282, June 2024.

Settlement over China funding puts institutions on notice

Science - Thu, 06/20/2024 - 05:58
Science, Volume 384, Issue 6702, Page 1282-1283, June 2024.

Republicans float plan to overhaul NIH

Science - Thu, 06/20/2024 - 05:58
Science, Volume 384, Issue 6702, Page 1283-1283, June 2024.

Wild poliovirus makes comeback in Afghanistan and Pakistan

Science - Thu, 06/20/2024 - 05:58
Science, Volume 384, Issue 6702, Page 1284-1284, June 2024.

Ancient earthquake likely rerouted the Ganges

Science - Thu, 06/20/2024 - 05:58
Science, Volume 384, Issue 6702, Page 1285-1285, June 2024.

News at a glance

Science - Thu, 06/20/2024 - 05:58
Science, Volume 384, Issue 6702, Page 1278-1279, June 2024.

Reducing nuclear dangers

Science - Thu, 06/20/2024 - 05:58
Science, Volume 384, Issue 6702, Page 1277-1277, June 2024.

GPTs are GPTs: Labor market impact potential of LLMs

Science - Thu, 06/20/2024 - 05:58
Science, Volume 384, Issue 6702, Page 1306-1308, June 2024.

In Science Journals

Science - Thu, 06/20/2024 - 05:58
Science, Volume 384, Issue 6702, Page 1311-1313, June 2024.

Soil Moisture, Soil NOx and Regional Air Quality in the Agricultural Central United States

JGR–Atmospheres - Wed, 06/19/2024 - 19:47
Abstract

Agricultural soils containing nitrogen-rich fertilizers are a substantial source of reactive nitrogen to the atmosphere with potential to impact air quality. One form of reactive nitrogen, nitrogen oxides (NOx = NO + NO2), are a harmful air pollutant and form secondary pollutants, including particulate matter (PM) and ozone (O3). Soil nitrogen oxide emissions (SNOx) are heavily influenced by environmental conditions, however the understanding of the influence of environmental drivers on the behavior of SNOx is limited. Here, we implement a modified soil moisture-dependent SNOx parameterization into the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and investigate the impact on regional air quality in the central U.S. Evaluating against TROPOspheric Monitoring Instrument (TROPOMI) column NO2 observations, WRF-Chem columns better capture the TROPOMI column magnitudes earlier in the growing season when using the updated SNOx parametrization, with modeled column bias improved to −1.1% over the most heavily fertilized regions. Evaluating against Environmental Protection Agency (EPA) surface NO2 observations, the relationship between surface NO2 and soil moisture is better represented in agriculturally-dominant regions when using the updated parameterization, with greatest surface NO2 concentrations at moderate soil moisture and lower concentrations at wetter or drier soil conditions. In simulations, these SNOx lead to increased O3 in select urban regions, with more than double the occurrences of O3 exceeding the EPA 8-hr O3 standard of 70 ppb.

Deriving cloud droplet number concentration from surface-based remote sensors with an emphasis on lidar measurements

Atmos. Meas. techniques - Wed, 06/19/2024 - 19:09
Deriving cloud droplet number concentration from surface-based remote sensors with an emphasis on lidar measurements
Gerald G. Mace
Atmos. Meas. Tech., 17, 3679–3695, https://doi.org/10.5194/amt-17-3679-2024, 2024
The number of cloud droplets per unit volume, Nd, in a cloud is important for understanding aerosol–cloud interaction. In this study, we develop techniques to derive cloud droplet number concentration from lidar measurements combined with other remote sensing measurements such as cloud radar and microwave radiometers.  We show that deriving Nd is very uncertain, although a synergistic algorithm seems to produce useful characterizations of Nd and effective particle size. 

Alternate materials for the capture and quantification of gaseous oxidized mercury in the atmosphere

Atmos. Meas. techniques - Wed, 06/19/2024 - 19:09
Alternate materials for the capture and quantification of gaseous oxidized mercury in the atmosphere
Livia Lown, Sarrah M. Dunham-Cheatham, Seth N. Lyman, and Mae S. Gustin
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-50,2024
Preprint under review for AMT (discussion: open, 1 comment)
New sorbent materials are needed to preconcentrate atmospheric oxidized mercury for analysis by developing mass spectrometry methods. Chitosan, α-Al2O3, and γ-Al2O3 were tested for quantitative gaseous oxidized mercury sorption in ambient air under laboratory and field conditions. Although these materials sorbed gaseous oxidized mercury without sorbing elemental mercury, less oxidized mercury was recovered from these materials compared to cation exchange membranes.

Robust handling of extremes in quantile mapping – "Murder your darlings"

Geoscientific Model Development - Wed, 06/19/2024 - 19:00
Robust handling of extremes in quantile mapping – "Murder your darlings"
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-98,2024
Preprint under review for GMD (discussion: open, 4 comments)
When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger range of data is likely encountered outside the calibration period. The end result is highly dependent on the method used, and we show that one needs to exclude data in the calibration range to activate the extrapolation functionality also in that time period, else there will be discontinuities in the timeseries.

Assessing effects of climate and technology uncertainties in large natural resource allocation problems

Geoscientific Model Development - Wed, 06/19/2024 - 18:19
Assessing effects of climate and technology uncertainties in large natural resource allocation problems
Jevgenijs Steinbuks, Yongyang Cai, Jonas Jaegermeyr, and Thomas W. Hertel
Geosci. Model Dev., 17, 4791–4819, https://doi.org/10.5194/gmd-17-4791-2024, 2024
This paper applies a cutting-edge numerical method, SCEQ, to show how uncertain climate change and technological progress affect the future utilization of the world's scarce land resources. The paper's key insight is to illustrate how much global cropland will expand when future crop yields are unknown. The study finds the range of outcomes for land use change to be smaller when using this novel method compared to existing deterministic models. 

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