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.

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.

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.

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%.

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.

The COVID-19 lockdown: a unique perspective into heterogeneous impacts of transboundary pollution on snow and ice darkening across the Himalayas.

The Tibetan Plateau holds the largest mass of snow and ice outside of the polar regions. The deposition of light-absorbing particles (LAPs) including mineral dust, black carbon and organic carbon and the resulting positive radiative forcing on snow (RFSLAPs) substantially contributes to glacier retreat. Yet how anthropogenic pollutant emissions affect Himalayan RFSLAPs through transboundary transport is currently not well known. The COVID-19 lockdown, resulting in a dramatic decline in human activities, offers a unique test to understand the transboundary mechanisms of RFSLAPs. This study employs multiple satellite data from the moderate resolution imaging spectroradiometer and ozone monitoring instrument, as well as a coupled atmosphere-chemistry-snow model, to reveal the high spatial heterogeneities in anthropogenic emissions-induced RFSLAPs across the Himalaya during the Indian lockdown in 2020. Our results show that the reduced anthropogenic pollutant emissions during the Indian lockdown were responsible for 71.6% of the reduction in RFSLAPs on the Himalaya in April 2020 compared to the same period in 2019. The contributions of the Indian lockdown-induced human emission reduction to the RFSLAPs decrease in the western, central, and eastern Himalayas were 46.8%, 81.1%, and 110.5%, respectively. The reduced RFSLAPs might have led to 27 Mt reduction in ice and snow melt over the Himalaya in April 2020. Our findings allude to the potential for mitigating rapid glacial threats by reducing anthropogenic pollutant emissions from economic activities.

Mortality burden due to ambient nitrogen dioxide pollution in China: Application of high-resolution models.

BACKGROUND: A large gap exists between the latest Global Air Quality Guidelines (AQG 2021) and Chinese air quality standards for NO2. Assessing whether and to what extent air quality standards for NO2 should be tightened in China requires a comprehensive understanding of the spatiotemporal characteristics of population exposure to ambient NO2 and related health risks, which have not been studied to date. OBJECTIVE: We predicted ground NO2 concentrations with high resolution in mainland China, explored exposure characteristics to NO2 pollution, and assessed the mortality burden attributable to NO2 exposure. METHODS: Daily NO2 concentrations in 2019 were predicted at 1-km spatial resolution in mainland China using random forest models incorporating multiple predictors. From these high-resolution predictions, we explored the spatiotemporal distribution of NO2, population and area percentages with NO2 exposure exceeding criterion levels, and premature deaths attributable to long- and short-term NO2 exposure in China. RESULTS: The cross-validation R2and root mean squared error of the NO2 predicting model were 0.80 and 7.78 µg/m3, respectively,at the daily level in 2019.The percentage of people (population number) with annual NO2 exposure over 40 µg/m3 in mainland China in 2019 was 10.40 % (145,605,200), and it reached 99.68 % (1,395,569,840) with the AQG guideline value of 10 µg/m3. NO2 levels and population exposure risk were elevated in urban areas than in rural. Long- and short-term exposures to NO2 were associated with 285,036 and 121,263 non-accidental deaths, respectively, in China in 2019. Tightening standards in steps gradually would increase the potential health benefit. CONCLUSION: In China, NO2 pollution is associated with significant mortality burden. Spatial disparities exist in NO2 pollution and exposure risks. China's current air quality standards may no longer objectively reflect the severity of NO2 pollution and exposure risk. Tightening the national standards for NO2 is needed and will lead to significant health benefits.

Inter-regional environmental inequality under lasting pandemic exacerbated by residential response.

Pandemics greatly affect transportation, economic and household activities and their associated air pollutant emissions. In less affluent regions, household energy use is often the dominant pollution source and is sensitive to the affluence change caused by a persisting pandemic. Air quality studies on COVID-19 have shown declines in pollution levels over industrialized regions as an immediate response to pandemic-caused lockdown and weakened economy. Yet few have considered the response of residential emissions to altered household affluence and energy choice supplemented by social distancing. Here we quantify the potential effects of long-term pandemics on ambient fine particulate matter pollution (PM2.5) and resulting premature mortality worldwide, by comprehensively considering the changes in transportation, economic production and household energy use. We find that a persisting COVID-like pandemic would reduce the global gross domestic product by 10.9 % and premature mortality related to black carbon, primary organic aerosols and secondary inorganic aerosols by 9.5 %. The global mortality decline would reach 13.0 % had the response of residential emissions been excluded. Among the 13 aggregated regions worldwide, the least affluent regions exhibit the greatest fractional economic losses with no comparable magnitudes of mortality reduction. This is because their weakened affluence would cause switch to more polluting household energy types on top of longer stay-at-home time, largely offsetting the effect of reduced transportation and economic production. International financial, technological and vaccine aids could reduce such environmental inequality.

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.

Inequality in historical transboundary anthropogenic PM2.5 health impacts.

Atmospheric transport of fine particulate matter (PM2.5), the leading environmental risk factor for public health, is estimated to exert substantial transboundary effects at present. During the past several decades, human-produced pollutant emissions have undergone drastic and regionally distinctive changes, yet it remains unclear about the resulting global transboundary health impacts. Here we show that between 1950 and 2014, global anthropogenic PM2.5 has led to 185.7 million premature deaths cumulatively, including about 14% from transboundary pollution. Among four country groups at different affluence levels, on a basis of per capita contribution to transboundary mortality, a richer region tends to exert severer cumulative health externality, with the poorest bearing the worst net externality after contrasting import and export of pollution mortality. The temporal changes in transboundary mortality and cross-regional inequality are substantial. Effort to reduce PM2.5-related transboundary mortality should seek international collaborative strategies that account for historical responsibility and inequality.

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.

Contrasting suitability and ambition in regional carbon mitigation.

Substantially enhancing carbon mitigation ambition is a crucial step towards achieving the Paris climate goal. Yet this attempt is hampered by poor knowledge on the potential cost and benefit of emission mitigation for each emitter. Here we use a global economic model to assess the mitigation costs for 27 major emitting countries and regions, and further contrast the costs against the potential benefits of mitigation valued as avoided social cost of carbon and the mitigation ambition of each region. We find a strong negative spatial correlation between cost and benefit of mitigating each ton of carbon dioxide. Meanwhile, the relative suitability of carbon mitigation, defined as the ratio of normalized benefit to normalized cost, also shows a considerable geographical mismatch with the mitigation ambition of emitters indicated in their first submitted nationally determined contributions. Our work provides important information to improve concerted climate action and formulate more efficient carbon mitigation strategies.

Modulation of Perovskite Grain Boundaries by Electron Donor-Acceptor Zwitterions R,R-Diphenylamino-phenyl-pyridinium-(CH2) n -sulfonates: All-Round Improvement on the Solar Cell Performance.

Inverted perovskite solar cells (PSCs) have attracted intense attention because of their insignificant hysteresis and low-temperature fabrication process. However, the efficiencies of inverted PSCs are still inferior to those of commercialized silicon solar cells. Also, the poor stability of PSCs is one of the major impedances to commercialization. Herein, we rationally designed and synthesized a new series of electron donor (R,R-diphenylamino) and acceptor (pyridimium-(CH2) n -sulfonates) zwitterions as a boundary modulator and systematically investigated their associated interface properties. Comprehensive physical and optoelectronic studies verify that these zwitterions provide a four-in-one functionality: balancing charge carrier transport, suppressing less-coordinated Pb2+ defects, enhancing moisture resistance, and reducing ion migration. Although each functionality may have been reported by specific passivating molecules, a strategy that simultaneously regulates the charge-transfer balance and three other functionalities has not yet been developed. The results are to make an omnidirectional improvement of PSCs. Among all zwitterions, 4-(4-(4-(di-(4-methoxylphenyl)amino)phenyl)propane-1-ium-1-yl)butane-1-sulfonate (OMeZC3) optimizes the balance hole/electron mobility ratio of perovskite to 0.91, and the corresponding PSCs demonstrate a high power conversion efficiency (PCE) of up to 23.15% free from hysteresis, standing out as one of the champion PSCs with an inverted structure. Importantly, the OMeZC3-modified PSC exhibits excellent long-term stability, maintaining almost its initial PCE after being stored at 80% relative humidity for 35 days.

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.

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.

The underappreciated role of agricultural soil nitrogen oxide emissions in ozone pollution regulation in North China.

Intensive agricultural activities in the North China Plain (NCP) lead to substantial emissions of nitrogen oxides (NOx) from soil, while the role of this source on local severe ozone pollution is unknown. Here we use a mechanistic parameterization of soil NOx emissions combined with two atmospheric chemistry models to investigate the issue. We find that the presence of soil NOx emissions in the NCP significantly reduces the sensitivity of ozone to anthropogenic emissions. The maximum ozone air quality improvements in July 2017, as can be achieved by controlling all domestic anthropogenic emissions of air pollutants, decrease by 30% due to the presence of soil NOx. This effect causes an emission control penalty such that large additional emission reductions are required to achieve ozone regulation targets. As NOx emissions from fuel combustion are being controlled, the soil emission penalty would become increasingly prominent and shall be considered in emission control strategies.

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 .

Source sector and fuel contributions to ambient PM2.5 and attributable mortality across multiple spatial scales.

Ambient fine particulate matter (PM2.5) is the world's leading environmental health risk factor. Reducing the PM2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. We provide a contemporary and comprehensive evaluation of sector- and fuel-specific contributions to this disease burden across 21 regions, 204 countries, and 200 sub-national areas by integrating 24 global atmospheric chemistry-transport model sensitivity simulations, high-resolution satellite-derived PM2.5 exposure estimates, and disease-specific concentration response relationships. Globally, 1.05 (95% Confidence Interval: 0.74-1.36) million deaths were avoidable in 2017 by eliminating fossil-fuel combustion (27.3% of the total PM2.5 burden), with coal contributing to over half. Other dominant global sources included residential (0.74 [0.52-0.95] million deaths; 19.2%), industrial (0.45 [0.32-0.58] million deaths; 11.7%), and energy (0.39 [0.28-0.51] million deaths; 10.2%) sectors. Our results show that regions with large anthropogenic contributions generally had the highest attributable deaths, suggesting substantial health benefits from replacing traditional energy sources.