The relative humidity (RH) and the dewpoint temperature (td) are two widely used indicators of the amount of moisture in air. The exact conversion from RH to td, as well as highly accurate approximations, are too complex to be done easily without the help of a calculator or computer. However, there is a very simple rule of thumb that can be very useful for approximating the conversion for moist air (RH > 50%), which does not appear to be widely known by the meteorological community: td decreases by about 1°C for every 5% decrease in RH (starting at td = t, the dry bulb temperature, when RH = 100%). This article examines the mathematical basis and accuracy of this and other relationships between the dewpoint and relative humidity. Several useful applications of the simple conversion are presented, in particular the computation of the cumulus cloud-base level (or lifting condensation level) as zLCL ≈ (20 + t/5) (100 − RH), where zLCL is in meters when t is in degrees Celcius and RH in percent. Fina... Abstract The relative humidity (RH) and the dewpoint temperature (td) are two widely used indicators of the amount of moisture in air. The exact conversion from RH to td, as well as highly accurate approximations, are too complex to be done easily without the help of a calculator or computer. However, there is a very simple rule of thumb that can be very useful for approximating the conversion for moist air (RH > 50%), which does not appear to be widely known by the meteorological community: td decreases by about 1°C for every 5% decrease in RH (starting at td = t, the dry bulb temperature, when RH = 100%). This article examines the mathematical basis and accuracy of this and other relationships between the dewpoint and relative humidity. Several useful applications of the simple conversion are presented, in particular the computation of the cumulus cloud-base level (or lifting condensation level) as zLCL ≈ (20 + t/5) (100 − RH), where zLCL is in meters when t is in degrees Celcius and RH in percent. Fina...

Objective To evaluate the existing meta-analytic evidence of associations between exposure to ultra-processed foods, as defined by the Nova food classification system, and adverse health outcomes. Design Systematic umbrella review of existing meta-analyses. Data sources MEDLINE, PsycINFO, Embase, and the Cochrane Database of Systematic Reviews, as well as manual searches of reference lists from 2009 to June 2023. Eligibility criteria for selecting studies Systematic reviews and meta-analyses of cohort, case-control, and/or cross sectional study designs. To evaluate the credibility of evidence, pre-specified evidence classification criteria were applied, graded as convincing (“class I”), highly suggestive (“class II”), suggestive (“class III”), weak (“class IV”), or no evidence (“class V”). The quality of evidence was assessed using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework, categorised as “high,” “moderate,” “low,” or “very low” quality. Results The search identified 45 unique pooled analyses, including 13 dose-response associations and 32 non-dose-response associations (n=9 888 373). Overall, direct associations were found between exposure to ultra-processed foods and 32 (71%) health parameters spanning mortality, cancer, and mental, respiratory, cardiovascular, gastrointestinal, and metabolic health outcomes. Based on the pre-specified evidence classification criteria, convincing evidence (class I) supported direct associations between greater ultra-processed food exposure and higher risks of incident cardiovascular disease related mortality (risk ratio 1.50, 95% confidence interval 1.37 to 1.63; GRADE=very low) and type 2 diabetes (dose-response risk ratio 1.12, 1.11 to 1.13; moderate), as well as higher risks of prevalent anxiety outcomes (odds ratio 1.48, 1.37 to 1.59; low) and combined common mental disorder outcomes (odds ratio 1.53, 1.43 to 1.63; low). Highly suggestive (class II) evidence indicated that greater exposure to ultra-processed foods was directly associated with higher risks of incident all cause mortality (risk ratio 1.21, 1.15 to 1.27; low), heart disease related mortality (hazard ratio 1.66, 1.51 to 1.84; low), type 2 diabetes (odds ratio 1.40, 1.23 to 1.59; very low), and depressive outcomes (hazard ratio 1.22, 1.16 to 1.28; low), together with higher risks of prevalent adverse sleep related outcomes (odds ratio 1.41, 1.24 to 1.61; low), wheezing (risk ratio 1.40, 1.27 to 1.55; low), and obesity (odds ratio 1.55, 1.36 to 1.77; low). Of the remaining 34 pooled analyses, 21 were graded as suggestive or weak strength (class III-IV) and 13 were graded as no evidence (class V). Overall, using the GRADE framework, 22 pooled analyses were rated as low quality, with 19 rated as very low quality and four rated as moderate quality. Conclusions Greater exposure to ultra-processed food was associated with a higher risk of adverse health outcomes, especially cardiometabolic, common mental disorder, and mortality outcomes. These findings provide a rationale to develop and evaluate the effectiveness of using population based and public health measures to target and reduce dietary exposure to ultra-processed foods for improved human health. They also inform and provide support for urgent mechanistic research. Systematic review registration PROSPERO CRD42023412732.

The Mediterranean Intensive Oxidant Study, performed in the summer of 2001, uncovered air pollution layers from the surface to an altitude of 15 kilometers. In the boundary layer, air pollution standards are exceeded throughout the region, caused by West and East European pollution from the north. Aerosol particles also reduce solar radiation penetration to the surface, which can suppress precipitation. In the middle troposphere, Asian and to a lesser extent North American pollution is transported from the west. Additional Asian pollution from the east, transported from the monsoon in the upper troposphere, crosses the Mediterranean tropopause, which pollutes the lower stratosphere at middle latitudes.

We use 23 atmospheric chemistry transport models to calculate current and future (2030) deposition of reactive nitrogen (NO_y, NH_x) and sulfate (SO_x) to land and ocean surfaces. The models are driven by three emission scenarios: (1) current air quality legislation (CLE); (2) an optimistic case of the maximum emissions reductions currently technologically feasible (MFR); and (3) the contrasting pessimistic IPCC SRES A2 scenario. An extensive evaluation of the present‐day deposition using nearly all information on wet deposition available worldwide shows a good agreement with observations in Europe and North America, where 60–70% of the model‐calculated wet deposition rates agree to within ±50% with quality‐controlled measurements. Models systematically overestimate NH_x deposition in South Asia, and underestimate NO_y deposition in East Asia. We show that there are substantial differences among models for the removal mechanisms of NO_y, NH_x, and SO_x, leading to ±1 σ variance in total deposition fluxes of about 30% in the anthropogenic emissions regions, and up to a factor of 2 outside. In all cases the mean model constructed from the ensemble calculations is among the best when comparing to measurements. Currently, 36–51% of all NO_y, NH_x, and SO_x is deposited over the ocean, and 50–80% of the fraction of deposition on land falls on natural (nonagricultural) vegetation. Currently, 11% of the world's natural vegetation receives nitrogen deposition in excess of the “critical load” threshold of 1000 mg(N) m⁻² yr⁻¹. The regions most affected are the United States (20% of vegetation), western Europe (30%), eastern Europe (80%), South Asia (60%), East Asia (40%), southeast Asia (30%), and Japan (50%). Future deposition fluxes are mainly driven by changes in emissions, and less importantly by changes in atmospheric chemistry and climate. The global fraction of vegetation exposed to nitrogen loads in excess of 1000 mg(N) m⁻² yr⁻¹ increases globally to 17% for CLE and 25% for A2. In MFR, the reductions in NO_y are offset by further increases for NH_x deposition. The regions most affected by exceedingly high nitrogen loads for CLE and A2 are Europe and Asia, but also parts of Africa.

Global tropospheric ozone distributions, budgets, and radiative forcings from an ensemble of 26 state‐of‐the‐art atmospheric chemistry models have been intercompared and synthesized as part of a wider study into both the air quality and climate roles of ozone. Results from three 2030 emissions scenarios, broadly representing “optimistic,” “likely,” and “pessimistic” options, are compared to a base year 2000 simulation. This base case realistically represents the current global distribution of tropospheric ozone. A further set of simulations considers the influence of climate change over the same time period by forcing the central emissions scenario with a surface warming of around 0.7K. The use of a large multimodel ensemble allows us to identify key areas of uncertainty and improves the robustness of the results. Ensemble mean changes in tropospheric ozone burden between 2000 and 2030 for the 3 scenarios range from a 5% decrease, through a 6% increase, to a 15% increase. The intermodel uncertainty (±1 standard deviation) associated with these values is about ±25%. Model outliers have no significant influence on the ensemble mean results. Combining ozone and methane changes, the three scenarios produce radiative forcings of −50, 180, and 300 mW m⁻², compared to a CO₂ forcing over the same time period of 800–1100 mW m⁻². These values indicate the importance of air pollution emissions in short‐ to medium‐term climate forcing and the potential for stringent/lax control measures to improve/worsen future climate forcing. The model sensitivity of ozone to imposed climate change varies between models but modulates zonal mean mixing ratios by ±5 ppbv via a variety of feedback mechanisms, in particular those involving water vapor and stratosphere‐troposphere exchange. This level of climate change also reduces the methane lifetime by around 4%. The ensemble mean year 2000 tropospheric ozone budget indicates chemical production, chemical destruction, dry deposition and stratospheric input fluxes of 5100, 4650, 1000, and 550 Tg(O₃) yr⁻¹, respectively. These values are significantly different to the mean budget documented by the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report (TAR). The mean ozone burden (340 Tg(O₃)) is 10% larger than the IPCC TAR estimate, while the mean ozone lifetime (22 days) is 10% shorter. Results from individual models show a correlation between ozone burden and lifetime, and each model's ozone burden and lifetime respond in similar ways across the emissions scenarios. The response to climate change is much less consistent. Models show more variability in the tropics compared to midlatitudes. Some of the most uncertain areas of the models include treatments of deep tropical convection, including lightning NO_x production; isoprene emissions from vegetation and isoprene's degradation chemistry; stratosphere‐troposphere exchange; biomass burning; and water vapor concentrations.