Soil Emissions of Reactive Nitrogen Accelerate Summertime Surface Ozone Increases in the North China Plain.

Summertime surface ozone in China has been increasing since 2013 despite the policy-driven reduction in fuel combustion emissions of nitrogen oxides (NOx). Here we examine the role of soil reactive nitrogen (Nr, including NOx and nitrous acid (HONO)) emissions in the 2013-2019 ozone increase over the North China Plain (NCP), using GEOS-Chem chemical transport model simulations. We update soil NOx emissions and add soil HONO emissions in GEOS-Chem based on observation-constrained parametrization schemes. The model estimates significant daily maximum 8 h average (MDA8) ozone enhancement from soil Nr emissions of 8.0 ppbv over the NCP and 5.5 ppbv over China in June-July 2019. We identify a strong competing effect between combustion and soil Nr sources on ozone production in the NCP region. We find that soil Nr emissions accelerate the 2013-2019 June-July ozone increase over the NCP by 3.0 ppbv. The increase in soil Nr ozone contribution, however, is not primarily driven by weather-induced increases in soil Nr emissions, but by the concurrent decreases in fuel combustion NOx emissions, which enhance ozone production efficiency from soil by pushing ozone production toward a more NOx-sensitive regime. Our results reveal an important indirect effect from fuel combustion NOx emission reduction on ozone trends by increasing ozone production from soil Nr emissions, highlighting the necessity to consider the interaction between anthropogenic and biogenic sources in ozone mitigation in the North China Plain.

Transboundary health impacts of transported global air pollution and international trade.

Millions of people die every year from diseases caused by exposure to outdoor air pollution. Some studies have estimated premature mortality related to local sources of air pollution, but local air quality can also be affected by atmospheric transport of pollution from distant sources. International trade is contributing to the globalization of emission and pollution as a result of the production of goods (and their associated emissions) in one region for consumption in another region. The effects of international trade on air pollutant emissions, air quality and health have been investigated regionally, but a combined, global assessment of the health impacts related to international trade and the transport of atmospheric air pollution is lacking. Here we combine four global models to estimate premature mortality caused by fine particulate matter (PM2.5) pollution as a result of atmospheric transport and the production and consumption of goods and services in different world regions. We find that, of the 3.45 million premature deaths related to PM2.5 pollution in 2007 worldwide, about 12 per cent (411,100 deaths) were related to air pollutants emitted in a region of the world other than that in which the death occurred, and about 22 per cent (762,400 deaths) were associated with goods and services produced in one region for consumption in another. For example, PM2.5 pollution produced in China in 2007 is linked to more than 64,800 premature deaths in regions other than China, including more than 3,100 premature deaths in western Europe and the USA; on the other hand, consumption in western Europe and the USA is linked to more than 108,600 premature deaths in China. Our results reveal that the transboundary health impacts of PM2.5 pollution associated with international trade are greater than those associated with long-distance atmospheric pollutant transport.

Recognizing the Importance of Fast Nonisothermal Crystallization for High-Performance Two-Dimensional Dion-Jacobson Perovskite Solar Cells with High Fill Factors: A Comprehensive Mechanistic Study.

Two-dimensional (2D) Dion-Jacobson (DJ) perovskite solar cells (PSCs), despite their advantage in versatility of n-layer variation, are subject to poor photovoltaic efficiency, particularly in the fill factor (FF), compared to their three-dimensional counterparts. To enhance the performance of DJ PSCs, the process of growing crystals and hence the corresponding morphology of DJ perovskites are of prime importance. Herein, we report the fast nonisothermal (NIT) crystallization protocol that is previously unrecognized for 2D perovskites to significantly improve the morphology, orientation, and charge transport of the DJ perovskite films. Comprehensive mechanistic studies reveal that the NIT effect leads to the secondary crystallization stage, forming network-like channels that play a vital role in the FF's leap-forward improvement and hence the DJ PSC's performance. As a whole, the NIT crystallized PSCs demonstrate a high power conversion efficiency and an FF of up to 19.87 and 86.16%, respectively. This research thus provides new perspectives to achieve highly efficient DJ PSCs.

Considerable Unaccounted Local Sources of NOx Emissions in China Revealed from Satellite.

High-resolution (e.g., 5 km) emission data of nitrogen oxides (NOx = NO + NO2) provide localized knowledge of pollution sources for targeted regulations, yet such data are lacking or inaccurate over most regions at present. Here we improve our PHLET-based inversion method to derive NOx emissions in China at a 5-km resolution in summer 2019, based on the TROPOMI-POMINO satellite product of nitrogen dioxide (NO2) columns. With low computational costs, our inversion explicitly accounts for the effects of horizontal transport and nonlinear chemistry. We find numerous small-to-medium sources related to minor roads and small human settlements at relatively low affluence levels, in addition to clear emission signals along major transportation lines, consistent with road line density and Tencent location data. Many small-to-medium sources and transportation emissions are unclear or missing in the spatial distributions of four widely used emission inventories. Our emissions offer a unique reference for targeted emission control.

Ground-Level NO2 Surveillance from Space Across China for High Resolution Using Interpretable Spatiotemporally Weighted Artificial Intelligence.

Nitrogen dioxide (NO2) at the ground level poses a serious threat to environmental quality and public health. This study developed a novel, artificial intelligence approach by integrating spatiotemporally weighted information into the missing extra-trees and deep forest models to first fill the satellite data gaps and increase data availability by 49% and then derive daily 1 km surface NO2 concentrations over mainland China with full spatial coverage (100%) for the period 2019-2020 by combining surface NO2 measurements, satellite tropospheric NO2 columns derived from TROPOMI and OMI, atmospheric reanalysis, and model simulations. Our daily surface NO2 estimates have an average out-of-sample (out-of-city) cross-validation coefficient of determination of 0.93 (0.71) and root-mean-square error of 4.89 (9.95) µg/m3. The daily seamless high-resolution and high-quality dataset "ChinaHighNO2" allows us to examine spatial patterns at fine scales such as the urban-rural contrast. We observed systematic large differences between urban and rural areas (28% on average) in surface NO2, especially in provincial capitals. Strong holiday effects were found, with average declines of 22 and 14% during the Spring Festival and the National Day in China, respectively. Unlike North America and Europe, there is little difference between weekdays and weekends (within ±1 µg/m3). During the COVID-19 pandemic, surface NO2 concentrations decreased considerably and then gradually returned to normal levels around the 72nd day after the Lunar New Year in China, which is about 3 weeks longer than the tropospheric NO2 column, implying that the former can better represent the changes in NOx emissions.

Reduced carbon emission estimates from fossil fuel combustion and cement production in China.

Nearly three-quarters of the growth in global carbon emissions from the burning of fossil fuels and cement production between 2010 and 2012 occurred in China. Yet estimates of Chinese emissions remain subject to large uncertainty; inventories of China's total fossil fuel carbon emissions in 2008 differ by 0.3 gigatonnes of carbon, or 15 per cent. The primary sources of this uncertainty are conflicting estimates of energy consumption and emission factors, the latter being uncertain because of very few actual measurements representative of the mix of Chinese fuels. Here we re-evaluate China's carbon emissions using updated and harmonized energy consumption and clinker production data and two new and comprehensive sets of measured emission factors for Chinese coal. We find that total energy consumption in China was 10 per cent higher in 2000-2012 than the value reported by China's national statistics, that emission factors for Chinese coal are on average 40 per cent lower than the default values recommended by the Intergovernmental Panel on Climate Change, and that emissions from China's cement production are 45 per cent less than recent estimates. Altogether, our revised estimate of China's CO2 emissions from fossil fuel combustion and cement production is 2.49 gigatonnes of carbon (2 standard deviations = ±7.3 per cent) in 2013, which is 14 per cent lower than the emissions reported by other prominent inventories. Over the full period 2000 to 2013, our revised estimates are 2.9 gigatonnes of carbon less than previous estimates of China's cumulative carbon emissions. Our findings suggest that overestimation of China's emissions in 2000-2013 may be larger than China's estimated total forest sink in 1990-2007 (2.66 gigatonnes of carbon) or China's land carbon sink in 2000-2009 (2.6 gigatonnes of carbon).

A Universal Approach for Controllable Synthesis of n-Specific Layered 2D Perovskite Nanoplates.

2D perovskites with chemical formula A'2 An-1 Bn X3n+1 have recently attracted considerable attention due to their tunable optical and electronic properties, which can be attained by varying the chemical composition. While high color-purity emitting perovskite nanomaterials have been accomplished through changing the halide composition, the preparation of single-phase, specific n-layer 2D perovskite nanomaterials is still pending because of the fast nucleation process of nanoparticles. We demonstrate a facile, rational and efficacious approach to synthesizing single-phase 2D perovskite nanoplates with a designated n number for both lead- and tin-based perovskites through kinetic control. Casting carboxylic acid additives in the reaction medium promotes selective formation of the kinetic product-multilayer 2D perovskite-in preference to the single-layer thermodynamic product. For the n-specific layered 2D perovskites, decreasing the number of octahedral layers per inorganic sheet leads to an increase of photoluminescence energy, radiative decay rate, and a significant boost in photostability.

Tuning the Circular Dichroism and Circular Polarized Luminescence Intensities of Chiral 2D Hybrid Organic-Inorganic Perovskites through Halogenation of the Organic Ions.

Through the incorporation of various halogen-substituted chiral organic cations, the effects of chiral molecules on the chiroptical properties of hybrid organic-inorganic perovskites (HOIPs) are investigated. Among them, the HOIP having a Cl-substituted chiral cation exhibits the highest circular dichroism (CD) and circular polarized luminescence (CPL) intensities, indicating the existence of the largest rotatory strength, whereas the F-substituted HIOP shows the weakest intensities. The observed modulation can be correlated to the varied magnetic transition dipole of HOIPs, which is sensitive to the d-spacing between inorganic layers and the halogen-halogen interaction between organic cations and the inorganic sheets. These counteracting effects meet the optimal CD and CPL intensity with chlorine substitution, rendering the rotatory strength of HOIPs arranged in the order of (ClMBA)2 PbI4 >(BrMBA)2 PbI4 >(IMBA)2 PbI4 >(MBA)2 PbI4 >(FMBA)2 PbI4 .

Superior Stability and Emission Quantum Yield (23% ± 3%) of Single-Layer 2D Tin Perovskite TEA2 SnI4 via Thiocyanate Passivation.

Tin-based perovskite, which exhibits narrower bandgap and comparable photophysical properties to its lead analogs, is one of the most forward-looking lead-free semiconductor materials. However, the poor oxidative stability of tin perovskite hinders the development toward practical application. In this work, the effect of pseudohalide anions on the stability and emission properties of single-layer 2D tin perovskite nanoplates with chemical formula TEA2 SnI4 (TEA = 2-thiophene-ethylammonium) is reported. The results reveal that ammonium thiocyanate (NH4 SCN) is the most effective additive in enhancing the stability and photoluminescence quantum yield of 2D TEA2 SnI4 (23 ± 3%). X-Ray photoelectron spectroscopic investigations on the thiocyanate passivated TEA2 SnI4 nanoplate show less than a 1% increase of Sn4+ signal upon 30 min exposure to air under ambient conditions (298 K, humidity ≈70%). Furthermore, no noticeable decrease in emission intensity of the nanoplate is observed after 20 h in air. The SCN- passivation during the growth stage of TEA2 SnI4 is proposed to play a crucial role in preventing the oxidation of Sn2+ and hence boosts both stability and photoluminescence yield of tin perovskite nanoplates.

Harnessing Dielectric Confinement on Tin Perovskites to Achieve Emission Quantum Yield up to 21.

Tin perovskite nanomaterial is one of the promising candidates to replace organic lead halide perovskites in lighting applications. Unfortunately, the performance of tin-based systems is markedly inferior to those featuring toxic Pb salts. In an effort to improve the emission quantum efficiency of nanoscale 2D layered tin iodide perovskites through fine-tuning the electronic property of organic ammonium salts, we came to unveil the relationship between dielectric confinement and the photoluminescent properties of tin iodide perovskite nanodisks. Our results show that increasing the dielectric contrast for organic versus inorganic layers leads to a bathochromic shift in emission peak wavelength, a decrease of exciton recombination time, and importantly a significant boost in the emission efficiency. Under optimized conditions, a leap in emission quantum yield to a record high 21% was accomplished for the nanoscale thienylethylammonium tin iodide perovskite (TEA2SnI4). The as-prepared TEA2SnI4 also possessed superior photostability, showing no sign of degradation under continuous irradiation (10 mW/cm2) over a period of 120 h.

Fugitive Road Dust PM2.5 Emissions and Their Potential Health Impacts.

Fugitive road dust (FRD) particles emitted by traffic-generated turbulence are an important contributor to urban ambient fine particulate matter (PM2.5). Especially in urban areas of developing countries, FRD PM2.5 emissions are a serious environmental threat to air quality and public health. FRD PM2.5 emissions have been neglected or substantially underestimated in previous study, resulting in the underestimation of modeling PM concentrations and estimating their health impacts. This study constructed the FRD PM2.5 emissions inventory in a major inland city in China (Lanzhou) in 2017 at high-resolution (500 × 500 m2), investigated the spatiotemporal characteristics of the FRD emissions in different urban function zones, and quantified their health impacts. The FRD PM2.5 emission was approximately 1141 ± 71 kg d-1, accounting for 24.6% of total PM2.5 emission in urban Lanzhou. Spatially, high emissions exceeding 3 × 104 µg m-2 d-1 occurred over areas with smaller particle sizes, larger traffic intensities, and more frequent construction activities. The estimated premature mortality burden induced by FRD PM2.5 exposure was 234.5 deaths in Lanzhou in 2017. Reducing FRD emissions are an important step forward to protect public health in many developing urban regions.

Updated Hourly Emissions Factors for Chinese Power Plants Showing the Impact of Widespread Ultralow Emissions Technology Deployment.

Nationwide severe air pollution has prompted China to mandate the adoption of ultralow emissions (ULE) control technologies at all of its coal-fired power plants by 2020. This process has accelerated greatly since 2014 and, combined with operational adjustments related to overcapacity, has reduced the emissions of nitrogen oxides (NO x), sulfur dioxide (SO2), and particulate matter (PM). Yet the quantitative understanding of ULE benefits is poor. Using detailed emissions data from 38 units at 17 power plants, corresponding to 10 combinations of ULE technologies representative of the Chinese power sector, we show that emissions factors for NO x, SO2, and PM are up to 1-2 orders of magnitude lower after ULE retrofitting. The effectiveness in cutting emissions shows a large spread across the various ULE technology combinations, providing an opportunity to choose the most efficient, economically viable technology (or a combination of technologies) in the future. The temporal variations in emissions at hourly resolution reveal the effects of power plant load on emissions, an increasingly important factor given that power plants are not operated at full capacity. These data will be useful in efforts to understand the evolving state of air quality in China and can also provide a basis for benchmarking state-of-the-art air pollution control equipment globally.

China's international trade and air pollution in the United States.

China is the world's largest emitter of anthropogenic air pollutants, and measurable amounts of Chinese pollution are transported via the atmosphere to other countries, including the United States. However, a large fraction of Chinese emissions is due to manufacture of goods for foreign consumption. Here, we analyze the impacts of trade-related Chinese air pollutant emissions on the global atmospheric environment, linking an economic-emission analysis and atmospheric chemical transport modeling. We find that in 2006, 36% of anthropogenic sulfur dioxide, 27% of nitrogen oxides, 22% of carbon monoxide, and 17% of black carbon emitted in China were associated with production of goods for export. For each of these pollutants, about 21% of export-related Chinese emissions were attributed to China-to-US export. Atmospheric modeling shows that transport of the export-related Chinese pollution contributed 3-10% of annual mean surface sulfate concentrations and 0.5-1.5% of ozone over the western United States in 2006. This Chinese pollution also resulted in one extra day or more of noncompliance with the US ozone standard in 2006 over the Los Angeles area and many regions in the eastern United States. On a daily basis, the export-related Chinese pollution contributed, at a maximum, 12-24% of sulfate concentrations over the western United States. As the United States outsourced manufacturing to China, sulfate pollution in 2006 increased in the western United States but decreased in the eastern United States, reflecting the competing effect between enhanced transport of Chinese pollution and reduced US emissions. Our findings are relevant to international efforts to reduce transboundary air pollution.

Revealing the hidden health costs embodied in Chinese exports.

China emits a considerable amount of air pollutants when producing goods for export. Previous efforts have emphasized the magnitude of export-related emissions; however, their health consequences on the Chinese population have not been quantified. Here, we present an interdisciplinary study to estimate the health impact of export-related air pollution. The results show that export-related emissions elevated the annual mean population weighted PM2.5 by 8.3 µg/m(3) (15% of the total) in 2007, causing 157,000 deaths and accounting for 12% of the total mortality attributable to PM2.5-related air pollution. Compared to the eastern coastal provinces, the inner regions experience much larger export-related health losses relative to their economic production gains, owing to huge inter-regional disparities in export structures and technology levels. A shift away from emission-intensive production structure and export patterns, especially in inner regions, could significantly help improve national exports while alleviating the inter-regional cost-benefit inequality. Our results provide the first quantification of health consequences from air pollution related to Chinese exports. The proposed policy recommendations, based on health burden, economic production gains, and emission analysis, would be helpful to develop more sustainable and effective national and regional export strategies.

Machine-learning-based corrections of CMIP6 historical surface ozone in China during 1950-2014.

Due to a lack of long-term observations in China, reports on historical ozone concentration are severely limited. In this study, by combining observation, reanalysis and model simulation data, XGBoost machine learning algorithm is used to correct the surface ozone concentration from CMIP6 climate model, and the long-term and large-scale surface ozone concentration of China during 1950-2014 is obtained. The long-term evolutions and trends of ozone and meteorological effects on interannual ozone variations are further analyzed. The results reveal that CMIP6 historical simulations have a large underestimation in ozone concentrations and their trends. The XGB-derived ozone are closer to observations, with R2 value of 0.66 and 0.74 for daily and monthly retrievals, respectively. Both the concentrations and exceedances of ozone in most parts of China have shown increasing trends from 1950 to 2014. The daily mean ozone concentration without climate change effects is estimated to be 117 ppb in the year 1950 averaged over China. It indicates that the increase in anthropogenic emissions of China has a significant contribution to ozone enhancement between 1950 and 2014. The higher ozone growth rates of XGB retrievals than those from the model indicate a regional surface ozone penalty due to the warming climate. The relatively significant increment in ozone are estimated in the Central and Western China. Seasonally, the ozone enhancement is largest in spring, indicating a shift in seasonal variation of ozone. Given the uncertainty in simulating historical ozone by climate model, we show that machine learning approaches can provide improved assessment of evolution in surface ozone, along with valuable information to guide future model development and formulate future ozone pollution prevention and control policies.

Marine aquaculture can deliver 40% lower carbon footprints than freshwater aquaculture based on feed, energy and biogeochemical cycles.

Freshwater aquaculture is an increasingly important source of blue foods but produces substantial methane and nitrous oxide emissions. Marine aquaculture, also known as mariculture, is a smaller sector with a large growth potential, but its climate impacts are challenging to accurately quantify. Here we assess the greenhouse gas emissions from mariculture's aquatic environment in global potentially suitable areas at 10 km resolution on the basis of marine biogeochemical cycles, greenhouse gas measurements from research cruises and satellite-observed net primary productivity. Mariculture's aquatic emissions intensities are estimated to be 1-6 g CH4 kg-1 carcass weight and 0.05-0.2 g N2O kg-1 carcass weight, >98% and >80% lower than freshwater systems. Using a life-cycle assessment approach, we show that mariculture's carbon footprints are ~40% lower than those of freshwater aquaculture based on feed, energy use and the aquatic environment emissions. Adoption of mariculture alongside freshwater aquaculture production could offer considerable climate benefits to meet future dietary protein and nutritional needs.

Direct and indirect consumption activities drive distinct urban-rural inequalities in air pollution-related mortality in China.

Household consumption in China is associated with substantial PM2.5 pollution, through activities directly (i.e., fuel use) and/or indirectly (i.e., consumption of goods and services) causing pollutant emissions. Urban and rural households exhibit different consumption preferences and living areas, thus their contributions to and suffering from air pollution could differ. Assessing this contrast is crucial for comprehending the environmental impacts of the nation's ongoing urbanization process. Here we quantify Chinese urban and rural households' contributions to ambient PM2.5 pollution and the health risks they suffer from, by integrating economic, atmospheric, and health models and/or datasets. The national premature deaths related to long-term exposure to PM2.5 pollution contributed by total household consumption are estimated to be 1.1 million cases in 2015, among which 56% are urban households and 44% are rural households. For pollution contributed indirectly, urban households, especially in developed provinces, tend to bear lower mortality risks compared with the portions of deaths or pollution they contribute. The opposite results are true for direct pollution. With China's rapid urbanization process, without adequate reduction in emission intensity, the increased indirect pollution-associated premature deaths could largely offset that avoided by reduced direct pollution, and the indirect pollution-associated urban-rural inequalities might become severer. Developing pollution mitigation strategies from both production and consumption sides could help with reducing pollution-related mortality and associated urban-rural inequality.

Effects of meteorological conditions on the mixing height of Nitrogen dioxide in China using new-generation geostationary satellite measurements and machine learning.

Nitrogen dioxide (NO2) plays a critical role in terms of air quality, human health, ecosystems, and its impact on climate change. While the crucial roles of the vertical structure of NO2 have been acknowledged for some time, there is currently limited knowledge about this aspect in China. The Geostationary Environment Monitoring Spectrometer (GEMS) is the world's first geostationary satellite instrument capable of measuring the hourly columnar amount of NO2. The study presented here introduces the use of mixing height for NO2 in the atmosphere. A thorough examination of spatiotemporal variations in the mixing height of NO2 was conducted using data from both the GEMS and ground-based air quality monitoring networks. A random forest model based on machine learning techniques was utilized to examine how meteorological parameters affect the mixing height of NO2. The results of our study reveal a notable seasonal fluctuation in the mixing height of NO2, with the highest values observed during the summer and the lowest values during the winter. Additionally, there was an increasing diurnal trend from early morning to mid-afternoon. Moreover, the study discovered elevated NO2 mixing heights in the dry regions of northern China. The results also indicated a positive correlation between the mixing height of NO2 and temperature and wind speed, while negative associations were found with relative humidity and air pressure. The machine learning model's predicted NO2 mixing heights were in good agreement with the measurement-based outcomes, as evidenced by a coefficient of determination (R2) value of 0.96 (0.84 for the 10-fold cross-validation). These findings emphasize the noteworthy influence of meteorological variables on the vertical distribution of NO2 in the atmosphere and enhance our comprehension of the three-dimensional variations in NO2.

Influences of El Niño-Southern Oscillation on summertime ozone pollution over central-eastern China during 1950-2014.

Summertime ozone pollution has become increasingly severe over many parts of China in recent years. Due to lack of historical ozone observations, few studies have analyzed the linkage between natural climate variability and ozone levels for a long time series. This study uses the simulation datasets from CMIP6 to explore the effects of El Niño-Southern Oscillation (ENSO) on summertime (June/July/August) surface ozone concentrations in central-eastern China (CEC; 20°N-42°N, 100°E-123°E) during the period of 1950-2014. Our results show that, after excluding the emission-related trend, the detrended summertime daily mean surface ozone concentrations averaged over CEC in El Niño years (30.69 ppb) are higher than those in La Niña events (29.34 ppb). Compared to the summertime mean ozone of 1950-2014 (30.25 ppb), the maximum anomalies in CMIP6 are 2.88 ppb (9.52% higher) and - 5.52 ppb (18.25% lower) in El Niño and La Niña years, respectively. In addition, the summertime MDA8 ozone of CEC is significantly correlated with the central-eastern equatorial Pacific SST (5°N-5°S, 170°W-120°W) (R = 0.29, P-value = 0.02). Such ozone increases/declines in El Niño/La Niña years are also found in satellite observations of OMI ozone. The results show that the ENSO affects the large-scale circulations over central-eastern China, which regulate the regional atmospheric stability and meteorological conditions (including horizontal wind fields, geopotential height, vertical velocity, surface air temperature, and precipitation) to influence the efficiency of ozone photochemical formation and transport. Our study makes better estimation and attribution of future surface ozone pollution in China.

National quantifications of methane emissions from fuel exploitation using high resolution inversions of satellite observations.

Reducing methane emissions from fossil fuel exploitation (oil, gas, coal) is an important target for climate policy, but current national emission inventories submitted to the United Nations Framework Convention on Climate Change (UNFCCC) are highly uncertain. Here we use 22 months (May 2018-Feb 2020) of satellite observations from the TROPOMI instrument to better quantify national emissions worldwide by inverse analysis at up to 50 km resolution. We find global emissions of 62.7 ± 11.5 (2σ) Tg a-1 for oil-gas and 32.7 ± 5.2 Tg a-1 for coal. Oil-gas emissions are 30% higher than the global total from UNFCCC reports, mainly due to under-reporting by the four largest emitters including the US, Russia, Venezuela, and Turkmenistan. Eight countries have methane emission intensities from the oil-gas sector exceeding 5% of their gas production (20% for Venezuela, Iraq, and Angola), and lowering these intensities to the global average level of 2.4% would reduce global oil-gas emissions by 11 Tg a-1 or 18%.