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China is set to actively reduce its methane emissions in the coming decade. A comprehensive evaluation of the current situation can provide a reference point for tracking the country's future progress. Here, using satellite and surface observations, we quantify China's methane emissions during 2010-2017. Including newly available data from a surface network across China greatly improves our ability to constrain emissions at subnational and sectoral levels. Our results show that recent changes in China's methane emissions are linked to energy, agricultural, and environmental policies. We find contrasting methane emission trends in different regions attributed to coal mining, reflecting region-dependent responses to China's energy policy of closing small coal mines (decreases in Southwest) and consolidating large coal mines (increases in North). Coordinated production of coalbed methane and coal in southern Shanxi effectively decreases methane emissions, despite increased coal production there. We also detect unexpected increases from rice cultivation over East and Central China, which is contributed by enhanced rates of crop-residue application, a factor not accounted for in current inventories. Our work identifies policy drivers of recent changes in China's methane emissions, providing input to formulating methane policy toward its climate goal.
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Carbón Mineral , Metano , Agricultura , China , Metano/análisis , PolíticasRESUMEN
Nitrogen dioxide (NO2) hydrolysis in deliquesced aerosol particles forms nitrous acid and nitrate and thus impacts air quality, climate, and the nitrogen cycle. Traditionally, it is considered to proceed far too slowly in the atmosphere. However, the significance of this process is highly uncertain because kinetic studies have only been made in dilute aqueous solutions but not under high ionic strength conditions of the aerosol particles. Here, we use laboratory experiments, air quality models, and field measurements to examine the effect of the ionic strength on the reaction kinetics of NO2 hydrolysis. We find that high ionic strengths (I) enhance the reaction rate constants (kI) by more than an order of magnitude compared to that at infinite dilution (kI=0), yielding log10(kI/kI=0) = 0.04I or rate enhancement factor = 100.04I. A state-of-the-art air quality model shows that the enhanced NO2 hydrolysis reduces the negative bias in the simulated concentrations of nitrous acid by 28% on average when compared to field observations over the North China Plain. Rapid NO2 hydrolysis also enhances the levels of nitrous acid in other polluted regions such as North India and further promotes atmospheric oxidation capacity. This study highlights the need to evaluate various reaction kinetics of atmospheric aerosols with high ionic strengths.
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Aerosoles , Aerosoles/química , Hidrólisis , Concentración Osmolar , Dióxido de Nitrógeno/química , Cinética , Atmósfera/química , Contaminantes Atmosféricos/químicaRESUMEN
Hydroxymethanesulfonate (HMS) has been found to be an abundant organosulfur aerosol compound in the Beijing-Tianjin-Hebei (BTH) region with a measured maximum daily mean concentration of up to 10 µg per cubic meter in winter. However, the production medium of HMS in aerosols is controversial, and it is unknown whether chemical transport models are able to capture the variations of HMS during individual haze events. In this work, we modify the parametrization of HMS chemistry in the nested-grid GEOS-Chem chemical transport model, whose simulations provide a good account of the field measurements during winter haze episodes. We find the contribution of the aqueous aerosol pathway to total HMS is about 36% in winter in Beijing, due primarily to the enhancement effect of the ionic strength on the rate constants of the reaction between dissolved formaldehyde and sulfite. Our simulations suggest that the HMS-to-inorganic sulfate ratio will increase from the baseline of 7% to 13% in the near future, given the ambitious clean air and climate mitigation policies for the BTH region. The more rapid reductions in emissions of SO2 and NOx compared to NH3 alter the atmospheric acidity, which is a critical factor leading to the rising importance of HMS in particulate sulfur species.
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Contaminantes Atmosféricos , Contaminación del Aire , Beijing , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Material Particulado/análisis , Monitoreo del Ambiente , China , Aerosoles/análisis , AguaRESUMEN
Surface ozone is a severe air pollution problem in the North China Plain, which is home to 300 million people. Ozone concentrations are highest in summer, driven by fast photochemical production of hydrogen oxide radicals (HOx) that can overcome the radical titration caused by high emissions of nitrogen oxides (NOx) from fuel combustion. Ozone has been very low during winter haze (particulate) pollution episodes. However, the abrupt decrease of NOx emissions following the COVID-19 lockdown in January 2020 reveals a switch to fast ozone production during winter haze episodes with maximum daily 8-h average (MDA8) ozone concentrations of 60 to 70 parts per billion. We reproduce this switch with the GEOS-Chem model, where the fast production of ozone is driven by HOx radicals from photolysis of formaldehyde, overcoming radical titration from the decreased NOx emissions. Formaldehyde is produced by oxidation of reactive volatile organic compounds (VOCs), which have very high emissions in the North China Plain. This remarkable switch to an ozone-producing regime in January-February following the lockdown illustrates a more general tendency from 2013 to 2019 of increasing winter-spring ozone in the North China Plain and increasing association of high ozone with winter haze events, as pollution control efforts have targeted NOx emissions (30% decrease) while VOC emissions have remained constant. Decreasing VOC emissions would avoid further spreading of severe ozone pollution events into the winter-spring season.
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Contaminación del Aire/análisis , Ozono/análisis , Material Particulado/análisis , Estaciones del Año , Compuestos Orgánicos Volátiles , COVID-19 , China , Productos Agrícolas , Monitoreo del Ambiente , Contaminación Ambiental , Humanos , Óxidos de Nitrógeno/química , Pandemias , Salud PúblicaRESUMEN
The eating and cooking quality (ECQ) directly affects the taste of rice, being closely related to factors such as gelatinization temperature (GT), gel consistency (GC) and amylose content (AC). Mining the quantitative trait loci (QTLs), and gene loci controlling ECQ-related traits is vital. A genome-wide association study on ECQ-related traits was conducted, combining 1.2 million single nucleotide polymorphisms (SNPs) with the phenotypic data of 173 rice accessions. Two QTLs for GT, one for GC and five for AC were identified, of which two were found in previously reported genes, and six were newly found. There were 28 positional candidate genes in the region of qAC11. Based on a linkage disequilibrium (LD) analysis, three candidate genes were screened within the LD region associated with AC. There were significant differences between the haplotypes of LOC_Os11g10170, but no significant differences were found for the other two genes. The qRT-PCR results showed that the gene expression levels in the accessions with high ACs were significantly larger than those in the accessions with low ACs at 35d and 42d after flowering. Hap 2 and Hap 3 of LOC_Os11g10170 reduced the AC by 13.09% and 10.77%, respectively. These results provide a theoretical and material basis for improving the ECQ of rice.
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Oryza , Sitios de Carácter Cuantitativo , Oryza/genética , Estudio de Asociación del Genoma Completo , Amilosa , CulinariaRESUMEN
During the COVID-19 lockdown in early 2020, observations in Beijing indicate that secondary organic aerosol (SOA) concentrations increased despite substantial emission reduction, but the reasons are not fully explained. Here, we integrate the two-dimensional volatility basis set into a state-of-the-art chemical transport model, which unprecedentedly reproduces organic aerosol (OA) components resolved by the positive matrix factorization based on aerosol mass spectrometer observations. The model shows that, for Beijing, the emission reduction during the lockdown lowered primary organic aerosol (POA)/SOA concentrations by 50%/18%, while deteriorated meteorological conditions increased them by 30%/119%, resulting in a net decrease in the POA concentration and a net increase in the SOA concentration. Emission reduction and meteorological changes both led to an increased OH concentration, which accounts for their distinct effects on POA and SOA. SOA from anthropogenic volatile organic compounds and organics with lower volatility contributed 28 and 62%, respectively, to the net SOA increase. Different from Beijing, the SOA concentration decreased in southern Hebei during the lockdown because of more favorable meteorology. Our findings confirm the effectiveness of organic emission reductions and meanwhile reveal the challenge in controlling SOA pollution that calls for large organic precursor emission reductions to rival the adverse impact of OH increase.
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Contaminantes Atmosféricos , COVID-19 , Humanos , Contaminantes Atmosféricos/análisis , Control de Enfermedades Transmisibles , Aerosoles y Gotitas Respiratorias , ChinaRESUMEN
Air quality in Beijing has been improved significantly in recent years; however, our knowledge of the vertically resolved aerosol chemistry in summer remains poor. Here, we carried out comprehensive measurements of aerosol composition, gaseous species, and aerosol optical properties on a meteorological tower in Beijing in summer and compared with those measured in winter. Our results showed that aerosol liquid water (ALW) contributing approximately 50% of the total mass with higher values aloft played a crucial role in aerosol formation. Particularly, the higher nitrate concentration in city aloft than at the ground level during daytime was mainly due to the enhanced gas-particle partitioning driven by ALW and particle acidity. The vertical profiles of organic aerosol (OA) factors varied more differently in the urban boundary layer. Although the ubiquitous decreases in primary OA with the increase in height were mainly due to the influences of local emissions and vertical convection, the vertical differences in oxygenated OA between summer and winter may be related to the photochemical processing of different biogenic and anthropogenic volatile organic compounds. The single-scattering albedo, brown carbon, and absorption Ångstrom exponent of aerosol particles also presented different vertical profiles between day and night due to the vertical changes in aerosol chemistry.
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Contaminantes Atmosféricos , Compuestos Orgánicos Volátiles , Aerosoles/química , Contaminantes Atmosféricos/análisis , Beijing , Monitoreo del Ambiente , Gases , Material Particulado/análisis , Estaciones del AñoRESUMEN
The interaction between water vapor and atmospheric aerosol leads to enhancement in aerosol water content, which facilitates haze development, but its concentrations, sources, and impacts remain largely unknown in polluted urban environments. Here, we show that the Indian capital, Delhi, which tops the list of polluted capital cities, also experiences the highest aerosol water yet reported worldwide. This high aerosol water promotes secondary formation of aerosols and worsens air pollution. We report that severe pollution events are commonly associated with high aerosol water which enhances light scattering and reduces visibility by 70%. Strong light scattering also suppresses the boundary layer height on winter mornings in Delhi, inhibiting dispersal of pollutants and further exacerbating morning pollution peaks. We provide evidence that ammonium chloride is the largest contributor to aerosol water in Delhi, making up 40% on average, and we highlight that regulation of chlorine-containing precursors should be considered in mitigation strategies.
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Contaminantes Atmosféricos , Contaminación del Aire , Aerosoles/análisis , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Cloruro de Amonio , China , Monitoreo del Ambiente , India , Material Particulado/análisis , Estaciones del AñoRESUMEN
Hydroxymethanesulfonate (HMS), a key marker species of aqueous-phase processing, plays a significant role in sulfur budget in atmosphere. Here we have a comprehensive characterization of HMS at urban and rural sites in North China Plain (NCP) by using the real-time measurements from a high-resolution aerosol mass spectrometer (AMS) and a single-particle AMS together with offline filter analysis. Our results showed much higher winter concentration of HMS at the rural site (average±1σ: 2.58 ± 2.56 µg m-3) than that (1.70 ± 2.68 µg m-3) in Beijing due to the more frequent fog events, low particle acidity and high concentration of precursors. The HMS on average contributed 6.3% and 5.2% to organic aerosol (OA), and 16% and 12% to the total particulate sulfur, at the rural and urban sites, respectively. HMS was highly correlated with aqueous-phase secondary OA and sulfate, and its contribution to the total particulate sulfur increased significantly as a function of relative humidity demonstrating the effective HMS production from aqueous-phase processing. Single-particle analysis showed that HMS-containing particles were mainly mixed with amine-related compounds. In addition, we found that organosulfur compounds (OS) estimated from sulfur-containing fragments of AMS correlated well with HMS at both urban and rural sites. While OS at the rural site was dominated by HMS, other types of OS were also important in urban area. The high HMS also affected the estimation of particle acidity using the AMS measured and predicted ammonium, particularly during severe haze episodes. Overall, our results demonstrated the importance of HMS in winter in NCP, and it could be more important in total particulate sulfur budget as the continuous decrease in sulfate in the future.
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Contaminantes Atmosféricos , Material Particulado , Aerosoles/análisis , Contaminantes Atmosféricos/análisis , China , Polvo/análisis , Monitoreo del Ambiente , Material Particulado/análisis , Sulfatos , Azufre/análisis , Agua/análisisRESUMEN
Binary offset carrier (BOC) modulation is a new modulation method that has been gradually applied to the Global Satellite Navigation System (GNSS) in recent years. However, due to the multi-peaks in its auto-correlation function (ACF), it will incur a false lock and generate synchronization ambiguous potentially. In this paper, an unambiguous synchronization method based on a reconstructed correlation function is proposed to solve the ambiguity problem. First, through the shape code vector constructed in this paper, the general cross-correlation function (CCF) expression of the BOC modulated signal will be obtained. Based on the features of the signal correlation function, it is decomposed into a matrix form of trigonometric functions. Then, it generates two local signal waves using a specific method, then the proposed method is implemented to obtain a no-side-peak correlation function by reconstructing the cross-correlation between the received signal and the two local signals. Simulations showed that it fully eliminates the side-peak threat and significantly removes the ambiguity during the synchronization of the BOC signals. This paper also gives the improved structure of acquisition and tracking. The detailed theoretical deduction of detection probability and code tracking error is demonstrated, and the corresponding phase discrimination function is given. In terms of de-blurring ability and detection probability performance, the proposed method outperformed other conventional approaches. The tracking performance was superior to the comparison methods and the phase discrimination curve only had a zero-crossing, which successfully removed the false lock points. In addition, in multipath mitigation, it outperformed the ACF of the BOC signal, and performs as well as the autocorrelation side-peak cancellation technique (ASPeCT) for BOC(kn,n) signals.
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Ammonium is one of the dominant inorganic water-soluble ions in fine particulate matter (PM2.5). In this study, source apportionment and thermodynamic equilibrium models were used to analyze the relationship between pH and the partitioning of ammonium (ε(NH4+)) using hourly ambient samples collected from Tianjin, China. We found a "Reversed-S curve" between pH and ε(NH4+) from the ambient hourly aerosol dataset when the theoretical ε(NO3-)* (an index identified in this work) was within specific ranges. A Boltzmann function was then used to fit the Reversed-S curve. For the summer data set, when ε(NO3-)* was between 0.7 and 0.8, the fitted R2 was 0.88. Through thermodynamic analysis, we found that the values of k[H+]2 (k = 3.08 × 104 L2 mol-2) and ε(NO3-)* can influence the pH-ε(NH4+) curve. Under certain situations, the values of k[H+]2 and ε(NO3-)* are similar to each other, and ε(NH4+) is sensitive to pH, suggesting that ε(NO3-)* plays an important role in affecting the ε(NH4+). During summer, winter, and spring seasons, when the relative humidity was greater than 0.36 and ε(NO3-)* was between 0.8 and 0.95, there was an obvious Reversed-S curve, with R2 = 0.60. The theoretical k[H+]2 and ε(NO3-)* developed in this work can be used to analyze the gas-particle partitioning of ammonia-ammonium and nitrate-nitric acid in the ambient atmosphere. Also, it is the first time that we created the joint source-NH3/HNO3 maps to integrate sources, aerosol pH and liquid water content, and ions (altogether in one map), which can provide useful information for designing effective strategies to control particulate matter pollution.
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Contaminantes Atmosféricos , Compuestos de Amonio , Aerosoles/análisis , Contaminantes Atmosféricos/análisis , China , Monitoreo del Ambiente , Tamaño de la Partícula , Material Particulado/análisis , Estaciones del AñoRESUMEN
Wild edible mushrooms can accumulate significantly elevated levels of mercury from the surrounding environment, which could be harmful to consumers' health. Speciation analysis of mercury in wild edible mushrooms aids in understanding the human exposure to these toxic compounds. In this study, we developed a high-performance liquid chromatography hyphenated to inductively coupled plasma mass spectrometry (HPLC-ICP-MS) method for the simultaneous determination of inorganic mercury (Hg(II)), methylmercury (MeHg), ethylmercury (EtHg), and phenylmercury (PhHg) in wild edible mushrooms. A rapid separation of four target mercury species was achieved within 11 min by a C8 column without utilizing high proportion of organic phase in HPLC. The parameters affecting the extraction efficiency of mercury in samples have been investigated. The proposed method showed good linearity within 0-50 µg/L with the detection and quantification limits of 0.6-4.5 µg/kg (S/N = 3), and 2.0-15 µg/kg (S/N = 10), respectively. This proposed method was successfully applied to the mercury speciation analysis in 7 varieties (95 samples) of wild edible mushrooms. The results indicated that in most mushroom samples, mercury mainly occurred as inorganic mercury. But there were two Tricholoma matsutakes, one contained 0.14 mg/kg of methylmercury, another contained 1.05 mg/kg of phenylmercury, which were higher than the maximum allowable content of total mercury in edible mushrooms in China. Graphical abstract.
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Agaricales/clasificación , Agaricales/metabolismo , Cromatografía Líquida de Alta Presión/métodos , Espectrometría de Masas/métodos , Mercurio/análisis , China , Humanos , Límite de Detección , Especificidad de la EspecieRESUMEN
Nitrate is one of the most abundant inorganic water-soluble ions in fine particulate matter (PM2.5). However, the formation mechanism of nitrate in the ambient atmosphere, especially the impacts of its semivolatility and the various existing forms of nitrogen, remain under-investigated. In this study, hourly ambient observations of speciated PM2.5 components (NO3-, SO42-, etc.) were collected in Tianjin, China. Source contributions were analyzed by PMF/ME2 (Positive Matrix Factorization using the Multilinear Engine 2) program, and pH were estimated by ISORROPIA-II, to investigate the relationship between pH and nitrate. Five sources (factors) were resolved: secondary sulfate (SS), secondary nitrate (SN), dust, vehicle and coal combustion. SN and pH showed a triangle-shaped relationship. When SS was high, the fraction of nitrate partitioning into the aerosol phase exhibits a characteristic "S-curve" relationship with pH for different seasons. An index ( ITL) is developed and combined with pH to explore the sensitive regions of "S-curve". Controlling the emissions of anions (SO42-, Cl-), cations (Ca2+, Mg2+, etc.) and gases (NO x, NH3, SO2, etc.) will change pH, potentially reducing or increasing SN. The findings of this work provide an effective approach for exploring the formation mechanisms of nitrate under different influencing factors (sources, pH, and IRL).
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Contaminantes Atmosféricos , China , Monitoreo del Ambiente , Gases , Material ParticuladoRESUMEN
Black carbon (BC) emissions from heavy-duty diesel vehicles (HDDVs) are rarely continuously measured using portable emission measurement systems (PEMSs). In this study, we utilize a PEMS to obtain real-world BC emission profiles for 25 HDDVs in China. The average fuel-based BC emissions of HDDVs certified according to Euro II, III, IV, and V standards are 2224 ± 251, 612 ± 740, 453 ± 584, and 152 ± 3 mg kg(-1), respectively. Notably, HDDVs adopting mechanical pump engines had significantly higher BC emissions than those equipped with electronic injection engines. Applying the useful features of PEMSs, we can relate instantaneous BC emissions to driving conditions using an operating mode binning methodology, and the average emission rates for Euro II to Euro IV diesel trucks can be constructed. From a macroscopic perspective, we observe that average speed is a significant factor affecting BC emissions and is well correlated with distance-based emissions (R(2) = 0.71). Therefore, the average fuel-based and distance-based BC emissions on congested roads are 40 and 125% higher than those on freeways. These results should be taken into consideration in future emission inventory studies.
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Contaminantes Atmosféricos/análisis , Hollín/análisis , Emisiones de Vehículos/análisis , Conducción de Automóvil , China , Ciudades , Monitoreo del Ambiente/métodos , Vehículos a MotorRESUMEN
This study aims to address accuracy challenges in assessing air pollution health impacts using Environmental Benefits Mapping and Analysis Program (BenMap), caused by limited meteorological factor data and missing pollutant data. By employing data increment strategies and multiple machine learning models, this research explores the effects of data volume, time steps, and meteorological factors on model prediction performance using several years of data from Tianjin City as an example. The findings indicate that increasing training data volume enhances the performance of Random Forest Regressor (RF) and Decision Tree Regressor (DT) models, especially for predicting CO, NO2, and PM2.5. The optimal prediction time step varies by pollutant, with the DT model achieving the highest R2 value (0.99) for CO and O3. Combining multiple meteorological factors, such as atmospheric pressure, relative humidity, and dew point temperature, significantly improves model accuracy. When using three meteorological factors, the model achieves an R2 of 0.99 for predicting CO, NO2, PM10, PM2.5, and SO2. Health impact assessments using BenMap demonstrated that the predicted all-cause mortality and specific disease mortalities were highly consistent with actual values, confirming the model's accuracy in assessing health impacts from air pollution. For instance, the predicted and actual all-cause mortality for PM2.5 were both 3120; for cardiovascular disease, both were 1560; and for respiratory disease, both were 780. To validate its generalizability, this method was applied to Chengdu, China, using several years of data for training and prediction of PM2.5, CO, NO2, O3, PM10, and SO2, incorporating atmospheric pressure, relative humidity, and dew point temperature. The model maintained excellent performance, confirming its broad applicability. Overall, we conclude that the machine learning and BenMap-based methods show high accuracy and reliability in predicting air pollutant concentrations and health impacts, providing a valuable reference for air pollution assessment.
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Contaminantes Atmosféricos , Contaminación del Aire , Evaluación del Impacto en la Salud , Aprendizaje Automático , Contaminación del Aire/estadística & datos numéricos , Contaminantes Atmosféricos/análisis , Evaluación del Impacto en la Salud/métodos , China , Humanos , Monitoreo del Ambiente/métodos , Material Particulado/análisis , Conceptos MeteorológicosRESUMEN
Traditional atmospheric chemistry posits that sulfur dioxide (SO2) can be oxidized to sulfate (SO42-) through aqueous-phase reactions in clouds and gas-phase oxidation. Despite adequate knowledge of traditional mechanisms, several studies have highlighted the potential for SO2 oxidation within aerosol water. Given the widespread presence of tropospheric aerosols, SO42- production through aqueous-phase oxidation in aerosol water could have a pervasive global impact. Here, we quantify the potential contributions of aerosol aqueous pathways to global sulfate formation based on the GEOS-Chem simulations and subsequent theoretical calculations. Hydrogen peroxide (H2O2) oxidation significantly influences continental regions both horizontally and vertically. Over the past two decades, shifts in the formation pathways within typical cities reveal an intriguing trend: despite reductions in SO2 emissions, the increased atmospheric oxidation capacities, like rising H2O2 levels, prevent a steady decline in SO42- concentrations. Abating oxidants would facilitate the benefit of SO2 reduction and the positive feedback in sulfate mitigation.
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This study comprehensively investigated the impact of dust storms (DSs) on downstream cities, by selecting representative DS events. In this paper, we discussed the characteristics of meteorological conditions, air pollutants, PM2.5 components, and their influence on sulfate formation mechanisms. During DSs, strong winds, reaching speeds of up to 10 m/s, led to significant increases in PM10 and PM2.5, with maximum concentrations of 2684.5 and 429 µg/m3, respectively. Primary gaseous pollutants experienced substantial reductions, with decline rates of 48.1, 34.9, 36.8, and 9.0 % for SO2, NO2, NH3, and CO, respectively. Despite a notable increase in PM2.5 concentrations, only 7.6 % of the total mass of PM2.5 was attributed to ionic and carbonaceous components, a much lower value than observed before the DSs (77.3 %). Concentrations of Fe, Ti, and Mn exhibited increases by factors of 6.5-14.1, 10.4-17.0, and 1.6-4.7, respectively. In contrast to the significant decrease of >76.2 % in nitrogen oxidation ratio (NOR), sulfur oxidation ratio (SOR) remained at a relatively high level, displaying a strong positive correlation with high concentrations of Fe, Mn, and Ti. Quantitative analysis revealed an average increase of 0.187 and 0.045 µg/m3 in sulfate from natural sources and heterogeneous generation, respectively. The heterogeneous reaction on mineral dust was closely linked to atmospheric humidity, radiation intensity, the form of metal existence, and concentrations of it. High concentrations of titanium dioxide and ironmanganese oxides in mineral dust promoted heterogeneous oxidation of SO2 through photocatalysis during the daytime and metal ion catalysis during the nighttime. This study establishes that the metal components in mineral dust promote heterogeneous sulfate formation, quantifies the yield of sulfate generated as a result, and provides possible mechanisms for heterogeneous sulfate formation.
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Secondary inorganic aerosols play an important role in air pollution and climate change, and their formation modulates the atmospheric deposition of reactive nitrogen (including oxidized and reduced nitrogen), thus impacting the nitrogen cycle. Large-scale and long-term analyses of secondary inorganic aerosol formation based on model simulations have substantial uncertainties. Here we improve constraints on secondary inorganic aerosol formation using decade-long in situ observations of aerosol composition and gaseous precursors from multiple monitoring networks across the United States. We reveal a shift in the secondary inorganic aerosol formation regime in the rural United States between 2011 and 2020, making rural areas less sensitive to changes in ammonia concentrations and shortening the effective atmospheric lifetime of reduced forms of reactive nitrogen. This leads to potential increases in reactive nitrogen deposition near ammonia emission hotspots, with ecosystem impacts warranting further investigation. Ammonia (NH3), a critical but not directly regulated precursor of fine particulate matter in the United States, has been increasingly scrutinized to improve air quality. Our findings, however, show that controlling NH3 became significantly less effective for mitigating fine particulate matter in the rural United States. We highlight the need for more collocated aerosol and precursor observations for better characterization of secondary inorganic aerosols formation in urban areas.
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Ambient volatile organic compounds (VOCs) concentrations are affected by emissions, dispersion, and chemistry. This work developed an initial concentration-dispersion normalized PMF (ICDN-PMF) to reflect the changes in source emissions. The effects of photochemical losses for VOC species were corrected by estimating the initial data, and then applying dispersion normalization to reduce the impacts of atmospheric dispersion. Hourly speciated VOC data measured in Qingdao from March to May 2020 were utilized to test the method and had assessed its effectiveness. Underestimated solvent use and biogenic emissions contributions due to photochemical losses during the O3 pollution (OP) period reached 4.4 and 3.8 times the non-O3 pollution (NOP) period values, respectively. Increased solvent use contribution due to air dispersion during the OP period was 4.6 times the change in the NOP period. The influence of chemical conversion and air dispersion on the gasoline and diesel vehicle emissions was not apparent during either period. The ICDN-PMF results suggested that biogenic emissions (23.1 %), solvent use (23.0 %), motor-vehicle emissions (17.1 %), and natural gas and diesel evaporation (15.8 %) contributed most to ambient VOCs during the OP period. Biogenic emissions and solvent use contributions during the OP period increased by 187 % and 135 % compared with the NOP period, respectively, whereas that of liquefied petroleum gas substantially decreased during the OP period. Controlling solvent use and motor-vehicles could be effective in controlling VOCs in the OP period.
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Estimating health benefits of reducing fossil fuel use from improved air quality provides important rationales for carbon emissions abatement. Simulating pollution concentration is a crucial step of the estimation, but traditional approaches often rely on complicated chemical transport models that require extensive expertise and computational resources. In this study, we develop a machine learning framework that is able to provide precise and robust annual average fine particle (PM2.5) concentration estimations directly from a high-resolution fossil energy use dataset. Applications of the framework with Chinese data reveal highly heterogeneous health benefits of avoiding premature mortality by reducing fossil fuel use in different sectors and regions in China with a mean of $19/tCO2 and a standard deviation of $38/tCO2. Reducing rural and residential coal use offers the highest co-benefits with a mean of $151/tCO2. Our findings prompt careful policy designs to maximize cost-effectiveness in the transition toward a carbon-neutral energy system.