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To address and mitigate the environmental impacts of synthetic greenhouse gases it's crucial to quantify their emissions to the atmosphere on different spatial scales. Atmospheric Inverse modelling is becoming a widely used method to provide observation-based estimates of greenhouse gas emissions with the potential to provide an independent verification tool for national emission inventories. A sensitivity study of the FLEXINVERT+ model for the optimisation of the spatial and temporal emissions of long-lived greenhouse gases at the regional-to-country scale is presented. A test compound HFC-134a, the most widely used refrigerant in mobile air conditioning systems, has been used to evaluate its European emissions in 2011 to be compared with a previous study. Sensitivity tests on driving factors like—observation selection criteria, prior data, background mixing ratios, and station selection—assessed the model's performance in replicating measurements, reducing uncertainties, and estimating country-specific emissions. Across all experiments, good prior (0.5–0.8) and improved posterior (0.6–0.9) correlations were achieved, emphasizing the reduced sensitivity of the inversion setup to different a priori information and the determining role of observations in constraining the emissions.The posterior results were found to be very sensitive to background mixing ratios, with even slight increases in the baseline leading to significant decrease of emissions. [ABSTRACT FROM AUTHOR]

To address and mitigate the environmental impacts of synthetic greenhouse gases it’s crucial to quantify their emissions to the atmosphere on different spatial scales. Atmospheric Inverse modelling is becoming a widely used method to provide observation-based estimates of greenhouse gas emissions with the potential to provide an independent verification tool for national emission inventories. A sensitivity study of the FLEXINVERT+ model for the optimisation of the spatial and temporal emissions of long-lived greenhouse gases at the regional-to-country scale is presented. A test compound HFC-134a, the most widely used refrigerant in mobile air conditioning systems, has been used to evaluate its European emissions in 2011 to be compared with a previous study. Sensitivity tests on driving factors like—observation selection criteria, prior data, background mixing ratios, and station selection—assessed the model’s performance in replicating measurements, reducing uncertainties, and estimating country-specific emissions. Across all experiments, good prior (0.5–0.8) and improved posterior (0.6–0.9) correlations were achieved, emphasizing the reduced sensitivity of the inversion setup to different a priori information and the determining role of observations in constraining the emissions.The posterior results were found to be very sensitive to background mixing ratios, with even slight increases in the baseline leading to significant decrease of emissions.

In a scenario when haze and smog events are wreaking havoc in many parts of the world, accurate information on ambient sulfur dioxide (SO 2) sources is a required input to models for prediction and mitigation of air pollution. Globally, India is one of the highest emitters of anthropogenic SO 2. However, the Ozone Monitoring Instrument (OMI) data reveal that unlike many other anthropogenic air pollutants, the strongest anthropogenic SO 2 sources are not located in the Indo-Gangetic plain (IGP) but over the coal belts of North Eastern peninsular India. In this study, we report SO 2 measurements conducted at Bhubaneswar, a rapidly developing smart city in the Eastern Coast of India. The city is ideally located just downwind of the Indian SO 2 hotspots during winter, when SO 2 concentrations are the highest, reaching 14.3 ppbv for hourly averaged data. The measurements, reported here from the summer of 2010 to the summer of 2012, show that despite being a rapidly developing location, SO 2 over Bhubaneswar is dominated by regional emissions rather than local sources like vehicular exhausts. The influence of regional emissions is strongest in winter as the city is directly downwind of 6 of the 10 largest thermal power plants and 7 out of the 13 largest integrated steel plants in India with a mean SO 2 concentration of 3.2 ppbv. This is evinced by multiple pointers viz. Concentration-Weighted Trajectory (CWT) analysis for surface SO 2 data, correlation analysis for OMI SO 2 data, analysis of surface concentrations of SO 2 , organic carbon, black carbon and carbon monoxide; which reveal SO 2 emissions from the industrial and mining regions of Chhattisgarh and north-west Odisha. This is the same region that shows up as hotspots of SO 2 in OMI retrievals over India. However, despite being downwind of major SO 2 sources during winter, SO 2 concentrations in Bhubaneswar are lower than over some other cities (Kolkata, Kanpur) in the IGP, due to influence of strong local sources in the later cases. Unlike most other urban regions in India, the diurnal variation of SO 2 over Bhubaneswar shows elevated daytime values due to predominant influence of regional emissions. • SO 2 measurements reported over a city downwind of Indian SO 2 hotspots in winter. • Multiple proxies: Trajectory, satellite & chemical analysis to find source regions. • SO 2 concentrations increasing over Bhubaneswar. [ABSTRACT FROM AUTHOR]

Abstract: Three Earth System models are used to derive surface temperature responses to removal of U.S. anthropogenic SO2 emissions. Using multicentury perturbation runs with and without U.S. anthropogenic SO2 emissions, the local and remote surface temperature changes are estimated. In spite of a temperature drift in the control and large internal variability, 200 year simulations yield statistically significant regional surface temperature responses to the removal of U.S. SO2 emissions. Both local and remote surface temperature changes occur in all models, and the patterns of changes are similar between models for northern hemisphere land regions. We find a global average temperature sensitivity to U.S. SO2 emissions of 0.0055 K per Tg(SO2) per year with a range of (0.0036, 0.0078). We examine global and regional responses in SO4 burdens, aerosol optical depths (AODs), and effective radiative forcing (ERF). While changes in AOD and ERF are concentrated near the source region (United States), the temperature response is spread over the northern hemisphere with amplification of the temperature increase toward the Arctic. In all models, we find a significant response of dust concentrations, which affects the AOD but has no obvious effect on surface temperature. Temperature sensitivity to the ERF of U.S. SO2 emissions is found to differ from the models' sensitivity to radiative forcing of doubled CO2. [ABSTRACT FROM AUTHOR]

A precise and high-resolution spatiotemporal distribution of atmospheric carbon dioxide (CO2) is important in identifying and quantifying the CO2 source and sinks on regional scales and emissions from discrete point sources. We propose the use of a regional gap-filling method by modeling the spatiotemporal correlation structures of column-averaged CO2 dry air mole fractions (Xco2) on a regional scale, using data from the Atmospheric CO2 Observations from Space retrievals of the Greenhouse Gases Observing Satellite (ACOS-GOSAT) measurements over mainland China. The accuracy of the gap-filling results is verified by cross-validation and comparison with ground-based measurements. As the results of the spatiotemporal gap-filling method are applied to mainland China, the correlation coefficient (r2) between the predicted values and true ones is greater than 0.85, the mean absolute prediction error is less than 1.5 ppm in cross-validation, and the seasonal cycle of the gap-filled data is generally in agreement with ground-based measurements. Finally, we compare the prediction accuracy based on our method with that based on the commonly used spatial-only kriging to further demonstrate the improved prediction accuracy. The applied regional gap-filling method, which makes full use of the multitemporal ACOS-GOSAT data, can generate a regional regular spatial distribution map of (Xco2) at high spatial and temporal resolutions. [ABSTRACT FROM PUBLISHER]

This paper provides new empirical evidence on regional–national disparities in environmental efficiency, based on analyses of NAMEA data referring to Italy and the Lazio region, where Rome is the main city. Shift-share analyses provide evidence on the drivers of environmental efficiency and on sector specificity. Our evidence shows that although the region around Rome has achieved higher environmental performance compared to Italy mainly thank to its being less industry based, some critical points in the energy sector and in some services should be taken into account in shaping the future development of the region. In addition, the use of regional NAMEA for econometric investigations of emission efficiency drivers at national level shows that though north south disparities favour northern and richer regions, in accordance with development oriented dynamics, environmental hot spots driven by specialisation and efficiency related issues also appear in some northern industrial regions. Further, the role of public ad private R&D is of main relevance in enhancing emission on economic value ratios. Environmental, industrial and sector-oriented policy making may derive valuable information from the evidence provided by our study, that highlights how analytical exploitation of NAMEA offers rich array of insights for regional policy making. [Copyright &y& Elsevier]

Abstract: Ozone (O3) concentrations in East Asia were simulated using the Community Multi-scale Air Quality model and their reproducibility was confirmed by comparing with observation data at Japanese monitoring sites. The model can reproduce the seasonal variation of surface O3 over Japan. In particular, for the southern parts of Japan, simulated surface O3 concentrations are strongly correlated with observations. Surface O3 distribution over East Asia varies dynamically from season to season according to the meteorological condition. In May and June, 2-month average O3 concentrations in the boundary layer are highest, 55–70ppbv over East China and Japan at 35–40°N. We estimated the seasonal variation of the contribution of chemically produced O3 by east Asian regional emissions. In the summertime, the contribution of the regional Asian emissions to O3 concentrations is around 40–70% over most of China, and the highest is 60–70% (<35ppbv) at the mouth area of Yantze River. This suggests that O3 concentrations over East Asia are strongly influenced by the chemical production by regional emissions during summer season. However, the inflow from outside of this model domain also contributes substantial O3 concentration over East Asia and its contribution is predominant in winter and early spring. The seasonal change of O3 concentrations over Japan is characterized by two peaks in spring and autumn and summer minimum. The spring peak event in 2002 consists of split peaks: the first peak in Mar–Apr is mainly influenced by the inflow from outside of this model domain, the second spring peak between May and June is mainly influenced by chemically produced O3 by regional emissions. During the summer season, O3 concentrations are the lowest over year because of the weak Asian outflow and northward penetration of the marine air mass. [Copyright &y& Elsevier]

During the negotiations of the Kyoto Protocol the delegation of Brazil presented an approach for distributing the burden of emissions reductions among the Parties based on the effect of their cumulative historical emissions on the global-average near-surface temperature. The Letter to the Parties does not limit the emissions to be considered to be only greenhouse gas (GHG) emissions. Thus, in this paper we explore the importance of anthropogenic SOx emissions that are converted to sulfate aerosol in the atmosphere, together with the cumulative greenhouse gas emissions, in attributing historical temperature change. We use historical emissions and our simple climate model to estimate the relative contributions to global warming of the regional emissions by four Parties: OECD90, Africa and Latin America, Asia, and Eastern Europe and the Former Soviet Union. Our results show that for most Parties the large warming contributed by their GHG emissions is largely offset by the correspondingly large cooling by their SOx emissions. Thus, OECD90 has become the dominant contributor to recent global warming following its large reduction in SOx emissions after 1980. [ABSTRACT FROM AUTHOR]

• The regional impacts of storage operation on CO 2 emissions are studied. • A new method of determining regional emissions factors was developed. • Emissions factors found using linear regression and a power flow model. • Large differences in emissions across storage operating scenarios and regions. • Differences in Great Britain can be equivalent to fitting coal power with CCS. While energy storage is key to increasing the penetration of variable renewables, the near-term effects of storage on greenhouse gas emissions are uncertain. Several studies have shown that storage operation can increase emissions even if the storage has 100% turnaround efficiency. Furthermore, previous studies have relied on national-level data and given very little attention to the impacts of storage on emissions at local scales. This is an important omission, as carbon intensities can vary very significantly at sub-national scales. We introduce a novel approach to calculating regional marginal emissions factors, based on a validated power system model and regression analysis. The techniques are used to investigate the impacts of storage operation on CO 2 emissions in Great Britain in 2019, under a range of operating scenarios. It is found that there are significant regional differences in storage emissions factors, with storage tending to increase emissions when used for wind balancing in areas with little wind curtailment. In contrast, the greatest emissions reductions are achieved when charging storage with otherwise-curtailed renewables and discharging to reduce peak demands in areas consuming high volumes of fossil fuel power. Over all regions and operating modes studied, the difference between the highest reduction in emissions and the highest increase in emissions is considerable, at 741 gCO 2 per kWh discharged. We conclude that power system regulators should pay increased attention to the impact of storage operation on system CO 2 emissions. [ABSTRACT FROM AUTHOR]

Humic-like substances (HULIS) are complex mixtures that are highly associated with brown carbon (BrC) and are important components of biomass burning (BB) emissions. In this study, we investigated the light absorption, emission factors (EFs), and amounts of HULIS emitted from the simulated burning of 27 types of regionally important rainforest biomass in Southeast Asia. We observed that HULIS had a high mass absorption efficiency at 365 nm (MAE 365), with an average value of 2.6 ± 0.83 m2 g−1 C. HULIS emitted from BB accounted for 65% ± 13% of the amount of water-soluble organic carbon (WSOC) and 85% ± 10% of the light absorption of WSOC at 365 nm. The EFs of HULIS from BB averaged 2.3 ± 2.1 g kg−1 fuel, and the burning of the four vegetation subtypes (herbaceous plants, shrubs, evergreen trees, and deciduous trees) exhibited different characteristics. The differences in EFs among the subtypes were likely due to differences in lignin content in the vegetation, the burning conditions, or other factors. The light absorption characteristics of HULIS were strongly associated with the EFs. The annual emissions (minimum–maximum) of HULIS from BB in this region in 2016 were 200–371 Gg. Furthermore, the emissions from January to April accounted for 99% of the total annual emissions of HULIS, which is likely the result of the burning activities during this season. The most significant emission regions were Cambodia, Burma, Thailand, and Laos. This study, which evaluated emissions of HULIS by simulating open BB, contributes to a better understanding of the light-absorbing properties and regional budgets of BrC in this region. Image 1 • Humic-like substances exhibit strong wavelength dependence and light absorption. • Emission factors of humic-like substances are different among burning biomasses. • Emissions of humic-like substances from biomass burning occur mainly in January–April. [ABSTRACT FROM AUTHOR]