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Nitrous oxide (N2O) is the third most important long-lived GHG and an important stratospheric ozone depleting substance. Agricultural practices and the use of N-fertilizers have greatly enhanced emissions of N2O. Here, we present estimates of N2O emissions determined from three global atmospheric inversion frameworks during the period 1998–2016. We find that global N2O emissions increased substantially from 2009 and at a faster rate than estimated by the IPCC emission factor approach. The regions of East Asia and South America made the largest contributions to the global increase. From the inversion-based emissions, we estimate a global emission factor of 2.3 ± 0.6%, which is significantly larger than the IPCC Tier-1 default for combined direct and indirect emissions of 1.375%. The larger emission factor and accelerating emission increase found from the inversions suggest that N2O emission may have a nonlinear response at global and regional scales with high levels of N-input.

Intimate partner violence claims millions of victims worldwide leading to infringement of fundamental human rights, serious physical and mental heath consequences and leading behind in its wake broken relationships and affected children. Despite its prevalence, its is not a well understood phenomenon. Through this article, we briefly review the literature on this subject; emphasizing on epidemiology and typologies of IPV, perpetuating factors and outcomes, the relevant legislations in India and the screening and intervention steps.

Atmospheric CO2 inversions estimate surface carbon fluxes from an optimal fit to atmospheric CO2 measurements, usually including prior constraints on the flux estimates. Eleven sets of carbon flux estimates are compared, generated by different inversions systems that vary in their inversions methods, choice of atmospheric data, transport model and prior information. The inversions were run for at least 5 yr in the period between 1990 and 2010. Mean fluxes for 2001-2004, seasonal cycles, interannual variability and trends are compared for the tropics and northern and southern extra-tropics, and separately for land and ocean. Some continental/basin-scale subdivisions are also considered where the atmospheric network is denser. Four-year mean fluxes are reasonably consistent across inversions at global/latitudinal scale, with a large total (land plus ocean) carbon uptake in the north (-3.4 Pg C yr-1 (±0.5 Pg C yr-1 standard deviation), with slightly more uptake over land than over ocean), a significant although more variable source over the tropics (1.6 ± 0.9 Pg C yr-1 ) and a compensatory sink of similar magnitude in the south (-1.4 ± 0.5 Pg C yr-1 ) corresponding mainly to an ocean sink. Largest differences across inversions occur in the balance between tropical land sources and southern land sinks. Interannual variability (IAV) in carbon fluxes is larger for land than ocean regions (standard deviation around 1.06 versus 0.33 Pg C yr-1 for the 1996-2007 period), with much higher consistency among the inversions for the land. While the tropical land explains most of the IAV (standard deviation ~ 0.65 Pg C yr-1 ), the northern and southern land also contribute (standard deviation ~ 0.39 Pg C yr-1 ). Most inversions tend to indicate an increase of the northern land carbon uptake from late 1990s to 2008 (around 0.1 Pg C yr-1 , predominantly in North Asia. The mean seasonal cycle appears to be well constrained by the atmospheric data over the northern land (at the continental scale), but still highly dependent on the prior flux seasonality over the ocean. Finally we provide recommendations to interpret the regional fluxes, along with the uncertainty estimates.

Increasing atmospheric carbon dioxide (CO 2 ) is the principal driver of anthropogenic climate change. Asia is an important region for the global carbon budget, with 4 of the world’s 10 largest national emitters of CO 2 . Using an ensemble of seven atmospheric inverse systems, we estimated land biosphere fluxes (natural, land-use change and fires) based on atmospheric observations of CO 2 concentration. The Asian land biosphere was a net sink of −0.46 (−0.70–0.24) PgC per year (median and range) for 1996–2012 and was mostly located in East Asia, while in South and Southeast Asia the land biosphere was close to carbon neutral. In East Asia, the annual CO 2 sink increased between 1996–2001 and 2008–2012 by 0.56 (0.30–0.81) PgC, accounting for ∼35% of the increase in the global land biosphere sink. Uncertainty in the fossil fuel emissions contributes significantly (32%) to the uncertainty in land biosphere sink change. Land biosphere uptake of carbon is important in mitigating the anthropogenic increase in atmospheric CO 2 and its climate forcing. Here, the authors show that land biosphere uptake of carbon in Asia has increased substantially since the mid 1990s, likely owing to reforestation and regional climate change.

Seasonal variations of atmospheric carbon dioxide (CO₂) in the Northern Hemisphere have increased since the 1950s, but sparse observations have prevented a clear assessment of the patterns of long-term change and the underlying mechanisms. We compare recent aircraft-based observations of CO₂ above the North Pacific and Arctic Oceans to earlier data from 1958 to 1961 and find that the seasonal amplitude at altitudes of 3 to 6 km increased by 50% for 45° to 90° N but by less than 25% for 10° to 45°N. An increase of 30 to 60% in the seasonal exchange of CO₂ by northern extratropical land ecosystems, focused on boreal forests, is implicated, substantially more than simulated by current land ecosystem models. The observations appear to signal large ecological changes in northern forests and a major shift in the global carbon cycle.

Observations of methyl chloroform combined with an atmospheric transport model predict a Northern to Southern Hemisphere hydroxyl ratio of slightly less than 1, whereas commonly used atmospheric chemistry models predict ratios 15–45% higher. The north–south distribution of atmospheric OH The hydroxyl radical is an important atmospheric oxidant, but our knowledge of its global distribution remains imprecise, with estimates for the ratio of Northern Hemisphere to Southern Hemisphere hydroxyl radical concentration varying from 0.85 to 1.4. These authors use a three-dimensional chemistry-transport model that has been well validated for interhemispheric transport using sulphur hexafluoride measurements, to obtain an interhemispheric hydroxyl radical ratio of 0.97±0.12. This information can help improve our understanding of the fate of atmospheric pollutants and greenhouse gases. The hydroxyl radical (OH) is a key oxidant involved in the removal of air pollutants and greenhouse gases from the atmosphere 1 , 2 , 3 . The ratio of Northern Hemispheric to Southern Hemispheric (NH/SH) OH concentration is important for our understanding of emission estimates of atmospheric species such as nitrogen oxides and methane 4 , 5 , 6 . It remains poorly constrained, however, with a range of estimates from 0.85 to 1.4 (refs 4 , 7 , 8 , 9 , 10 ). Here we determine the NH/SH ratio of OH with the help of methyl chloroform data (a proxy for OH concentrations) and an atmospheric transport model that accurately describes interhemispheric transport and modelled emissions. We find that for the years 2004–2011 the model predicts an annual mean NH–SH gradient of methyl chloroform that is a tight linear function of the modelled NH/SH ratio in annual mean OH. We estimate a NH/SH OH ratio of 0.97 ± 0.12 during this time period by optimizing global total emissions and mean OH abundance to fit methyl chloroform data from two surface-measurement networks and aircraft campaigns 11 , 12 , 13 . Our findings suggest that top-down emission estimates of reactive species such as nitrogen oxides in key emitting countries in the NH that are based on a NH/SH OH ratio larger than 1 may be overestimated.

Biochar application in the soil has shown its potential for improved plant growth, root structure, and nutrient availability. However, uncertainties remain regarding the optimal depth for biochar application and its interaction with roots, which significantly influence plant growth and development. This transparent rhizobox trial consists of five treatments: control treatment (T1) with recommended dose of fertilizer, and four biochar addition treatments with different depths viz. 5 (T2), 10 (T3), 15 (T4) and 20 cm (T5). FESEM, EDX-Spectroscopy was performed to elucidate the change in morphology and element distribution pattern of biochar after application in soil. Fresh biochar has 53.7% carbon and 19.9% oxygen, however, aged biochar shown 37.4% carbon and 36.4% oxygen content. The T5 exhibit the best outcomes, with the most significant increment in maize root traits over the control treatment (T1). In particular, T5 recorded a maximum improvement in root length (+ 48.2%), root volume (+ 42.7%) and root dry biomass (+ 56.7%) compared to the control treatment when biochar was applied at 20 cm soil depth. Shoot traits at 20 cm biochar incorporation revealed an increase in shoot fresh biomass (+ 23.1%), shoot dry biomass (+ 15%), leaf area (+ 50.5%) and number of leaves (+ 40.7%) as compared to the control treatment. As compared to the control, a considerable rise in soil nitrogen, phosphorus, and potassium was observed in biochar amendment at 20 cm depth, with the highest nitrogen in T5 (20.9%), phosphorus in T5 (103%), and the percentage increase in potassium in T5 (55.5%). One of the most consistently prevalent molecules examined by GC–MS was methyl stearate, a fatty acid ester detected in all five treatments. Methyl stearate content increased as the depth of biochar increased: T1 (10.26%), T2 (8.67%), T3 (12.40%), T4 (12.93%), and T5 (14.65%). Overall, the findings of this study suggest that uniform application of biochar in the top soil layer significantly enhances the above- and below-ground attributes of plants.

Atmospheric methane (CH4) increased from ~900 ppb (parts per billion, or nanomoles per mole of dry air) in 1900 to ~1800 ppb in 2010 at a rate unprecedented in any observational records. However, the contributions of the various methane sources and sinks to the CH4 increase are poorly understood. Here we use initial emissions from bottom-up inventories for anthropogenic sources, emissions from wetlands and rice paddies simulated by a~terrestrial biogeochemical model, and an atmospheric general circulation model (AGCM)-based chemistry-transport model (i.e. ACTM) to simulate atmospheric CH4 concentrations for 1910–2010. The ACTM simulations are compared with the CH4 concentration records reconstructed from Antarctic and Arctic ice cores and firn air samples, and from direct measurements since the 1980s at multiple sites around the globe. The differences between ACTM simulations and observed CH4 concentrations are minimized to optimize the global total emissions using a mass balance calculation. During 1910–2010, the global total CH4 emission doubled from ~290 to ~580 Tg yr−1. Compared to optimized emission, the bottom-up emission data set underestimates the rate of change of global total CH4 emissions by ~30% during the high growth period of 1940–1990, while it overestimates by ~380% during the low growth period of 1990–2010. Further, using the CH4 stable carbon isotopic data (δ13C), we attribute the emission increase during 1940–1990 primarily to enhancement of biomass burning. The total lifetime of CH4 shortened from 9.4 yr during 1910–1919 to 9 yr during 2000–2009 by the combined effect of the increasing abundance of atomic chlorine radicals (Cl) and increases in average air temperature. We show that changes of CH4 loss rate due to increased tropospheric air temperature and CH4 loss due to Cl in the stratosphere are important sources of uncertainty to more accurately estimate the global CH4 budget from δ13C observations.

Cold‐season methane (CH4) emissions may be poorly constrained in wetland models. We examined cold‐season CH4 emissions simulated by 16 models participating in the Global Carbon Project model intercomparison and analyzed temporal and spatial patterns in simulation results using prescribed inundation data for 2000–2020. Estimated annual CH4 emissions from northern (>60°N) wetlands averaged 10.0 ± 5.5 Tg CH4 yr−1. While summer CH4 emissions were well simulated compared to in‐situ flux measurement observations, the models underestimated CH4 during September to May relative to annual total (27 ± 9%, compared to 45% in observations) and substantially in the months with subzero air temperatures (5 ± 5%, compared to 27% in observations). Because of winter warming, nevertheless, the contribution of cold‐season emissions was simulated to increase at 0.4 ± 0.8% decade−1. Different parameterizations of processes, for example, freezing–thawing and snow insulation, caused conspicuous variability among models, implying the necessity of model refinement. Plain Language Summary Wetlands in the northern high latitudes are a major source of methane (CH4) to the atmosphere, mainly during the warm season. Previously, models have assumed that cold‐season CH4 emissions are low, but recent observations suggest high‐latitude wetlands can be substantial sources even in winter. We compared CH4 emissions simulated by 16 state‐of‐the‐art wetland models, participating in a model intercomparison project with a focus on the cold‐season in northern wetlands. The model simulations indicated that nearly one third of annual emissions were simulated to occur from September to May, and CH4 emissions to the atmosphere were not negligible even under freezing air temperatures, although the results differed greatly among the models. However, field studies suggest cold‐season emissions account for an even larger fraction of annual emissions. These results highlight the contribution of cold‐season emissions to the annual CH4 budget, which future climatic warming is expected to affect severely, and they also show that simulations of cold‐season CH4 emissions from wetlands need to be improved. Key Points Cold‐season methane (CH4) emissions simulated by 16 Global Carbon Project‐CH4 wetland models were analyzed Most models underestimate the cold‐season emissions in comparison with observational data Further model improvement by including cold‐season processes is required to reduce the model bias and uncertainty