The influence of storage atmosphere on the color development and myoglobin (Mb) redox state of beef was investigated. Beef samples were packaged in 6 different atmospheres including different degrees of vacuum, levels of oxygen, nitrogen, and a mixture with 20% CO2 and stored at 2°C for 14 days. Over this time, color and reflection of the packaged samples were measured. The used method allows quick, easy, and non-invasive measurement of the packaged samples, without using time consuming chemical assays. The method could be implemented in beef production lines, with potential for automatization. The data was used to illustrate the L*a*b* values for insights regarding qualitative color changes. Quantitative color changes were analyzed by calculation of color difference ΔE2000. Additionally, the relative levels of the deoxymyoglobin (DMb), oxymyoglobin (OMb) and metmyoglobin (MMb) were calculated from reflection spectra. The most important findings are: there is a strong correlation (rsp = 0.80 to 0.99 with one exception at rsp = 0.69 (high vacuum), p ≤ 0.05) between a* values and relative OMb levels. Storage atmospheres containing high oxygen concentrations lead to an attractive meat color, but a decreased overall color and Mb stability (ΔE = 5.02 (synthetic air) and ΔE = 2.23 (high oxygen) after 14 days of storage). Vacuum packaged samples are most stable in regards of color and Mb stability (ΔE = 1.79 (high vacuum) and ΔE = 1.63 (low vacuum) after 14 days of storage), but lack in the vibrant red color desired for sale. The experiments showed that color measurement can be a fast, non-invasive marker for meat quality. PRACTICAL APPLICATION: In this research article, six different storage atmospheres are compared regarding their influence on color stability and color quality of beef during storage in packaging. The results suggest which atmospheres to use in various sales-related scenarios. The method described can easily be applied in the meat industry to quickly monitor changes during storage and wet-aging without damaging the meat or opening the meat packages.

Atmospheric nitrogen dioxide (NO2) pollution is a major health and social challenge in South African induced mainly by fossil fuel combustions for power generation, transportation and domestic biomass burning for indoor activities. The pollution level is moderated by various environmental and social factors, yet previous studies made use of limited factors or focussed on only industrialised regions ignoring the contributions in large parts of the country. There is a need to assess how socio-environmenral factors, which inherently exhibit variations across space, influence the pollution levels in South Africa. This study therefore aimed to predict annual tropospheric NO2 column density using socio-environmental variables that are widely proven in the literature as sources and sinks of pollution. The environmental variables used to predict NO2 included remotely sensed Enhanced Vegetation Index (EVI), Land Surface Temperature and Aerosol Optical Depth (AOD) while the social data, which were obtained from national household surveys, included energy sources data, settlement patterns, gender and age statistics aggregated at municipality scale. The prediction was accomplished by applying the Multiscale Geographically Weighted Regression that fine-tunes the spatial scale of each variable when building geographically localised relationships. The model returned an overall R2 of 0.92, indicating good predicting performance and the significance of the socio-environmental variables in estimating NO2 in South Africa. From the environmental variables, AOD had the most influence in increasing NO2 pollution while vegetation represented by EVI had the opposite effect of reducing the pollution level. Among the social variables, household electricity and wood usage had the most significant contributions to pollution. Communal residential arrangements significantly reduced NO2, while informal settlements showed the opposite effect. The female proportion was the most important demographic variable in reducing NO2. Age groups had mixed effects on NO2 pollution, with the mid-age group (20-29) being the most important contributor to NO2 emission. The findings of the current study provide evidence that NO2 pollution is explained by socio-economic variables that vary widely across space. This can be achieved reliably using the MGWR approach that produces strong models suited to each locality.

Fine-mode aerosol optical depth (fAOD) is a vital proxy for the concentration of anthropogenic aerosols in the atmosphere. Currently, the limited data length and high uncertainty of the satellite-based data diminish the applicability of fAOD for climate research. Here, we propose a novel pretrained deep learning framework that can extract information underlying each satellite pixel and use it to create new latent features that can be employed for improving retrieval accuracy in regions without in situ data. With the proposed model, we developed a new global fAOD (at 0.5 μm) data from 2001 to 2020, resulting in a 10% improvement in the overall correlation coefficient (R) during site-based independent validation and a 15% enhancement in non-AERONET site areas validation. Over the past two decades, there has been a noticeable downward trend in global fAOD (-1.39 × 10-3/year). Compared to the general deep-learning model, our method reduces the global trend\'s previously overestimated magnitude by 7% per year. China has experienced the most significant decline (-5.07 × 10-3/year), which is 3 times greater than the global trend. Conversely, India has shown a significant increase (7.86 × 10-4/year). This study bridges the gap between sparse in situ observations and abundant satellite measurements, thereby improving predictive models for global patterns of fAOD and other climate factors.

Airborne microplastics (MPs) are important pollutants that have been present in the environment for many years and are characterized by their universality, persistence, and potential toxicity. This study investigated the effects of terrestrial and marine transport of MPs in the atmosphere of a coastal city and compared the difference between daytime and nighttime. Laser direct infrared imaging (LDIR) and polarized light microscopy were used to characterize the physical and chemical properties of MPs, including number concentration, chemical types, shape, and size. Backward trajectories were used to distinguish the air masses from marine and terrestrial transport. Twenty chemical types were detected by LDIR, with rubber (16.7%) and phenol-formaldehyde resin (PFR; 14.8%) being major components. Three main morphological types of MPs were identified, and fragments (78.1%) are the dominant type. MPs in the atmosphere were concentrated in the small particle size segment (20-50 µm). The concentration of MPs in the air mass from marine transport was 14.7 items/m3 - lower than that from terrestrial transport (32.0 items/m3). The number concentration of airborne MPs was negatively correlated with relative humidity. MPs from terrestrial transport were mainly rubber (20.2%), while those from marine transport were mainly PFR (18%). MPs in the marine transport air mass were more aged and had a lower number concentration than those in the terrestrial transport air mass. The number concentration of airborne MPs is higher during the day than at night. These findings could contribute to the development of targeted control measures and methods to reduce MP pollution.

To explore air contamination resulting from special biomass combustion and suspended dust in Lhasa, the present study focused on the size distribution and chemical characteristics of particulate matter (PM) emission resulting from 7 types of non-fossil pollution sources. We investigated the concentration and size distribution of trace elements from 7 pollution sources collected in Lhasa. Combining Lhasa\'s atmospheric particulate matter data, enrichment factors (EFs) have been calculated to examine the potential impact of those pollution sources on the atmosphere quality of Lhasa. The highest mass concentration of total elements of biomass combustion appeared at PM0.4, and the second highest concentration existed in the size fraction 0.4-1 µm; the higher proportion (12 %) of toxic metals was produced by biomass combustion. The elemental composition of suspended dust and atmospheric particulate matter was close (except for As and Cd); the highest concentration of elements was all noted in PM2.5-10 (PM3-10). Potassium was found to be one of the main biomass markers. The proportion of Cu in suspended dust is significantly lower than that of atmospheric particulate matter (0.53 % and 3.75 %), which indicates that there are other anthropogenic sources. The EFs analysis showed that the Cr, Cu, Zn, and Pb produced by biomass combustion were highly enriched (EFs > 100) in all particle sizes. The EFs of most trace elements increased with decreasing particle size, indicating the greater influence of humanfactors on smaller particles.

The chemistry of sulfur cycle contributes significantly to the atmospheric nucleation process, which is the first step of new particle formation (NPF). In the present study, cycloaddition reaction mechanism of sulfur trioxide (SO3) to hydrogen sulfide (H2S) which is a typical air pollutant and toxic gas detrimental to the environment were comprehensively investigate through theoretical calculations and Atmospheric Cluster Dynamic Code simulations. Gas-phase stability and nucleation potential of the product thiosulfuric acid (H2S2O3, TSA) were further analyzed to evaluate its atmospheric impact. Without any catalysts, the H2S + SO3 reaction is infeasible with a barrier of 24.2 kcal/mol. Atmospheric nucleation precursors formic acid (FA), sulfuric acid (SA), and water (H2O) could effectively lower the reaction barriers as catalysts, even to a barrierless reaction with the efficiency of cis-SA > trans-FA > trans-SA > H2O. Subsequently, the gas-phase stability of TSA was investigated. A hydrolysis reaction barrier of up to 61.4 kcal/mol alone with an endothermic isomerization reaction barrier of 5.1 kcal/mol under the catalytic effect of SA demonstrates the sufficient stability of TSA. Furthermore, topological and kinetic analysis were conducted to determine the nucleation potential of TSA. Atmospheric clusters formed by TSA and atmospheric nucleation precursors (SA, ammonia NH3, and dimethylamine DMA) were thermodynamically stable. Moreover, the gradually decreasing evaporation coefficients for TSA-base clusters, particularly for TSA-DMA, suggests that TSA may participate in NPF where the concentration of base molecules are relatively higher. The present new reaction mechanism may contributes to a better understanding of atmospheric sulfur cycle and NPF.

Heterogeneous oxidation by gas-phase oxidants is an important chemical transformation pathway of secondary organic aerosol (SOA) and plays an important role in controlling the abundance, properties, as well as climate and health impacts of aerosols. However, our knowledge on this heterogeneous chemistry remains inadequate. In this study, the heterogeneous oxidation of α-pinene ozonolysis SOA by hydroxyl (OH) radicals was investigated under both low and high relative humidity (RH) conditions, with an emphasis on the evolution of molecular composition of SOA and its RH dependence. It is found that the heterogeneous oxidation of SOA at an OH exposure level equivalent to 12 hr of atmospheric aging leads to particle mass loss of 60% at 25% RH and 95% at 90% RH. The heterogeneous oxidation strongly changes the molecular composition of SOA. The dimer-to-monomer signal ratios increase dramatically with rising OH exposure, in particular under high RH conditions, suggesting that aerosol water stimulates the reaction of monomers with OH radicals more than that of dimers. In addition, the typical SOA tracer compounds such as pinic acid, pinonic acid, hydroxy pinonic acid and dimer esters (e.g., C17H26O8 and C19H28O7) have lifetimes of several hours against heterogeneous OH oxidation under typical atmospheric conditions, which highlights the need for the consideration of their heterogeneous loss in the estimation of monoterpene SOA concentrations using tracer-based methods. Our study sheds lights on the heterogeneous oxidation chemistry of monoterpene SOA and would help to understand their evolution and impacts in the atmosphere.

Tropospheric ozone (O3) is a strong greenhouse gas, particularly in the upper troposphere (UT). Limited observations point to a continuous increase in UT O3 in recent decades, but the attribution of UT O3 changes is complicated by large internal climate variability. We show that the anthropogenic signal (\"fingerprint\") in the patterns of UT O3 increases is distinguishable from the background noise of internal variability. The time-invariant fingerprint of human-caused UT O3 changes is derived from a 16-member initial-condition ensemble performed with a chemistry-climate model (CESM2-WACCM6). The fingerprint is largest between 30°S and 40°N, especially near 30°N. In contrast, the noise pattern in UT O3 is mainly associated with the El Niño-Southern Oscillation (ENSO). The UT O3 fingerprint pattern can be discerned with high confidence within only 13 years of the 2005 start of the OMI/MLS satellite record. Unlike the UT O3 fingerprint, the lower tropospheric (LT) O3 fingerprint varies significantly over time and space in response to large-scale changes in anthropogenic precursor emissions, with the highest signal-to-noise ratios near 40°N in Asia and Europe. Our analysis reveals a significant human effect on Earth\'s atmospheric chemistry in the UT and indicates promise for identifying fingerprints of specific sources of ozone precursors.

The photolysis of particulate nitrate (pNO3-) has been suggested to be an important source of nitrous acid (HONO) in the troposphere. However, determining the photolysis rate constant of pNO3- (jpNO3-) suffers from high uncertainty. Prior laboratory measurements of jpNO3- using aerosol filters have been complicated by the \"shadow effect\"─a phenomenon of light extinction within aerosol layers that potentially skews these measurements. We developed a method to correct the shadow effect on the photolysis rate constant of pNO3- for HONO production (jpNO3- → HONO) using aerosol filters with identical chemical compositions but different aerosol loadings. We applied the method to quantify jpNO3- → HONO over the North China Plain (NCP) during the winter haze period. After correcting for the shadow effect, the normalized average jpNO3- → HONO at 5 °C increased from 5.89 × 10-6 s-1 to 1.72 × 10-5 s-1. The jpNO3- → HONO decreased with increasing pH and nitrate proportions in PM2.5 and had no correlation with nitrate concentrations. A parametrization for jpNO3- → HONO was developed for model simulation of HONO production in NCP and similar environments.

Current strategies to hold surface warming below a certain level, e. g., 1.5 or 2°C, advocate limiting total anthropogenic cumulative carbon emissions to ∼0.9 or ∼1.25 Eg C (1018 grams carbon), respectively. These allowable emission budgets are based on a near-linear relationship between cumulative emissions and warming identified in various modeling efforts. The IPCC assesses this near-linear relationship with high confidence in its Summary for Policymakers (§D1.1 and Figure SPM.10). Here we test this proportionality in specially designed simulations with a latest-generation Earth system model (ESM) that includes an interactive carbon cycle with updated terrestrial ecosystem processes, and a suite of CMIP simulations (ZecMIP, ScenarioMIP). We find that atmospheric CO2 concentrations can differ by ∼100 ppmv and surface warming by ∼0.31°C (0.46°C over land) for the same cumulated emissions (≈1.2 Eg C, approximate carbon budget for 2°C target). CO2 concentration and warming per 1 Eg of emitted carbon (Transient Climate Response to Cumulative Carbon Emissions; TCRE) depend not just on total emissions, but also on the timing of emissions, which heretofore have been mainly overlooked. A decomposition of TCRE reveals that oceanic heat uptake is compensating for some, but not all, of the pathway dependence induced by the carbon cycle response. The time dependency clearly arises due to lagged carbon sequestration processes in the oceans and specifically on land, viz., ecological succession, land-cover, and demographic changes, etc., which are still poorly represented in most ESMs. This implies a temporally evolving state of the carbon system, but one which surprisingly apportions carbon into land and ocean sinks in a manner that is independent of the emission pathway. Therefore, even though TCRE differs for different pathways with the same total emissions, it is roughly constant when related to the state of the carbon system, i. e., the amount of carbon stored in surface sinks. While this study does not fundamentally invalidate the established TCRE concept, it does uncover additional uncertainties tied to the carbon system state. Thus, efforts to better understand this state dependency with observations and refined models are needed to accurately project the impact of future emissions.