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From 2013 to 2017, with the implementation of the toughest-ever clean air policy in China, significant declines in fine particle (PM2.5) concentrations occurred nationwide. Here we estimate the drivers of the improved PM2.5 air quality and the associated health benefits in China from 2013 to 2017 based on a measure-specific integrated evaluation approach, which combines a bottom-up emission inventory, a chemical transport model, and epidemiological exposure-response functions. The estimated national population–weighted annual mean PM2.5 concentrations decreased from 61.8 (95%CI: 53.3–70.0) to 42.0 μg/m³ (95% CI: 35.7–48.6) in 5 y, with dominant contributions from anthropogenic emission abatements. Although interannual meteorological variations could significantly alter PM2.5 concentrations, the corresponding effects on the 5-y trends were relatively small. The measure-by-measure evaluation indicated that strengthening industrial emission standards (power plants and emission-intensive industrial sectors), upgrades on industrial boilers, phasing out outdated industrial capacities, and promoting clean fuels in the residential sector were major effective measures in reducing PM2.5 pollution and health burdens. These measures were estimated to contribute to 6.6- (95% CI: 5.9–7.1), 4.4- (95% CI: 3.8–4.9), 2.8- (95% CI: 2.5–3.0), and 2.2- (95% CI: 2.0–2.5) μg/m³ declines in the national PM2.5 concentration in 2017, respectively, and further reduced PM2.5-attributable excess deaths by 0.37 million (95% CI: 0.35–0.39), or 92% of the total avoided deaths. Our study confirms the effectiveness of China’s recent clean air actions, and the measure-by-measure evaluation provides insights into future clean air policy making in China and in other developing and polluting countries.

To tackle the problem of severe air pollution, China has implemented active clean air policies in recent years. As a consequence, the emissions of major air pollutants have decreased and the air quality has substantially improved. Here, we quantified China's anthropogenic emission trends from 2010 to 2017 and identified the major driving forces of these trends by using a combination of bottom-up emission inventory and index decomposition analysis (IDA) approaches. The relative change rates of China's anthropogenic emissions during 2010–2017 are estimated as follows: −62 % for SO2, −17 % for NOx, +11 % for nonmethane volatile organic compounds (NMVOCs), +1 % for NH3, −27 % for CO, −38 % for PM10, −35 % for PM2.5, −27 % for BC, −35 % for OC, and +16 % for CO2. The IDA results suggest that emission control measures are the main drivers of this reduction, in which the pollution controls on power plants and industries are the most effective mitigation measures. The emission reduction rates markedly accelerated after the year 2013, confirming the effectiveness of China's Clean Air Action that was implemented since 2013. We estimated that during 2013–2017, China's anthropogenic emissions decreased by 59 % for SO2, 21 % for NOx, 23 % for CO, 36 % for PM10, 33 % for PM2.5, 28 % for BC, and 32 % for OC. NMVOC emissions increased and NH3 emissions remained stable during 2010–2017, representing the absence of effective mitigation measures for NMVOCs and NH3 in current policies. The relative contributions of different sectors to emissions have significantly changed after several years' implementation of clean air policies, indicating that it is paramount to introduce new policies to enable further emission reductions in the future.

Here, we highlight seven chemical separation processes that, if improved, would reap great global benefits. Our list is not exhaustive; almost all commercial chemicals arise from a separation process that could be improved.

Abstract The social cost of carbon dioxide (SC-CO 2 ) measures the monetized value of the damages to society caused by an incremental metric tonne of CO 2 emissions and is a key metric informing climate policy. Used by governments and other decision-makers in benefit–cost analysis for over a decade, SC-CO 2 estimates draw on climate science, economics, demography and other disciplines. However, a 2017 report by the US National Academies of Sciences, Engineering, and Medicine 1 (NASEM) highlighted that current SC-CO 2 estimates no longer reflect the latest research. The report provided a series of recommendations for improving the scientific basis, transparency and uncertainty characterization of SC-CO 2 estimates. Here we show that improved probabilistic socioeconomic projections, climate models, damage functions, and discounting methods that collectively reflect theoretically consistent valuation of risk, substantially increase estimates of the SC-CO 2 . Our preferred mean SC-CO 2 estimate is $185 per tonne of CO 2 ($44–$413 per tCO 2 : 5%–95% range, 2020 US dollars) at a near-term risk-free discount rate of 2%, a value 3.6 times higher than the US government’s current value of $51 per tCO 2 . Our estimates incorporate updated scientific understanding throughout all components of SC-CO 2 estimation in the new open-source Greenhouse Gas Impact Value Estimator (GIVE) model, in a manner fully responsive to the near-term NASEM recommendations. Our higher SC-CO 2 values, compared with estimates currently used in policy evaluation, substantially increase the estimated benefits of greenhouse gas mitigation and thereby increase the expected net benefits of more stringent climate policies.

Our special report examines the role of renewables, nuclear power and carbon capture in reaching this ambitious goal.

The capture and use of carbon dioxide to create valuable products might lower the net costs of reducing emissions or removing carbon dioxide from the atmosphere. Here we review ten pathways for the utilization of carbon dioxide. Pathways that involve chemicals, fuels and microalgae might reduce emissions of carbon dioxide but have limited potential for its removal, whereas pathways that involve construction materials can both utilize and remove carbon dioxide. Land-based pathways can increase agricultural output and remove carbon dioxide. Our assessment suggests that each pathway could scale to over 0.5 gigatonnes of carbon dioxide utilization annually. However, barriers to implementation remain substantial and resource constraints prevent the simultaneous deployment of all pathways.

Global investment in counteracting climate change has galvanized increasing interest in carbon capture and sequestration (CCS) as a versatile emissions mitigation technology. As decarbonization efforts accelerate, CCS can target the emissions of large point-source emitters, such as coal- or natural gas-fired power plants, while also supporting the production of renewable or low-carbon fuels. Furthermore, CCS can enable decarbonization of difficult-to-abate industrial processes and can support net CO2 removal from the atmosphere through bioenergy coupled with CCS or direct air capture. Here we review the development of porous materials as next-generation sorbents for CO2 capture applications. We focus on stream- and sector-specific challenges while highlighting case studies within the context of the rapidly shifting energy landscape. We conclude with a discussion of key needs from the materials community to expand deployment of carbon capture technologies. Porous materials can selectively and reversibly adsorb large quantities of gas. This Review highlights progress made in using this class of materials for CO2 capture processes and discusses key gaps that the materials community can address to accelerate greater adoption of adsorptive carbon capture technologies.

Through its important role in the formation of particulate matter, atmospheric ammonia affects air quality and has implications for human health and life expectancy . Excess ammonia in the environment also contributes to the acidification and eutrophication of ecosystems and to climate change . Anthropogenic emissions dominate natural ones and mostly originate from agricultural, domestic and industrial activities . However, the total ammonia budget and the attribution of emissions to specific sources remain highly uncertain across different spatial scales . Here we identify, categorize and quantify the world's ammonia emission hotspots using a high-resolution map of atmospheric ammonia obtained from almost a decade of daily IASI satellite observations. We report 248 hotspots with diameters smaller than 50 kilometres, which we associate with either a single point source or a cluster of agricultural and industrial point sources-with the exception of one hotspot, which can be traced back to a natural source. The state-of-the-art EDGAR emission inventory mostly agrees with satellite-derived emission fluxes within a factor of three for larger regions. However, it does not adequately represent the majority of point sources that we identified and underestimates the emissions of two-thirds of them by at least one order of magnitude. Industrial emitters in particular are often found to be displaced or missing. Our results suggest that it is necessary to completely revisit the emission inventories of anthropogenic ammonia sources and to account for the rapid evolution of such sources over time. This will lead to better health and environmental impact assessments of atmospheric ammonia and the implementation of suitable nitrogen management strategies.

Tropospheric nitrogen dioxide (NO2) column densities detected from space are widely used to infer trends in terrestrial nitrogen oxide (NO x ) emissions. We study changes in NO2 column densities using the Ozone Monitoring Instrument (OMI) over China from 2005 to 2015 and compare them with the bottom-up inventory to examine NO x emission trends and their driving forces. From OMI measurements we detect the peak of NO2 column densities at a national level in the year 2011, with average NO2 column densities deceasing by 32% from 2011 to 2015 and corresponding to a simultaneous decline of 21% in bottom-up emission estimates. A significant variation in the peak year of NO2 column densities over regions is observed. Because of the reasonable agreement between the peak year of NO2 columns and the start of deployment of denitration devices, we conclude that power plants are the primary contributor to the NO2 decline, which is further supported by the emission reduction of 56% from the power sector in the bottom-up emission inventory associated with the penetration of selective catalytic reduction (SCR) increasing from 18% to 86% during 2011–2015. Meanwhile, regulations for vehicles also make a significant contribution to NO x emission reductions, in particular for a few urbanized regions (e.g., Beijing and Shanghai), where they implemented strict regulations for vehicle emissions years before the national schedule for SCR installations and thus reached their NO2 peak 2–3 years ahead of the deployment of denitration devices for power plants.

This paper, which focuses on emissions from China's coal-fired power plants during 1990-2010, is the second in a series of papers that aims to develop a high-resolution emission inventory for China. This is the first time that emissions from China's coal-fired power plants were estimated at unit level for a 20-year period. This inventory is constructed from a unit-based database compiled in this study, named the China coal-fired Power plant Emissions Database (CPED), which includes detailed information on the technologies, activity data, operation situation, emission factors, and locations of individual units and supplements with aggregated data where unit-based information is not available. Between 1990 and 2010, compared to a 479 % growth in coal consumption, emissions from China's coal-fired power plants increased by 56, 335, and 442 % for SO2, NOx, and CO2, respectively, and decreased by 23 and 27 % for PM2.5 and PM10 respectively. Driven by the accelerated economic growth, large power plants were constructed throughout the country after 2000, resulting in a dramatic growth in emissions. The growth trend of emissions has been effectively curbed since 2005 due to strengthened emission control measures including the installation of flue gas desulfurization (FGD) systems and the optimization of the generation fleet mix by promoting large units and decommissioning small ones. Compared to previous emission inventories, CPED significantly improved the spatial resolution and temporal profile of the power plant emission inventory in China by extensive use of underlying data at unit level. The new inventory developed in this study will enable a close examination of temporal and spatial variations of power plant emissions in China and will help to improve the performances of chemical transport models by providing more accurate emission data.