Aerosol Emissions Research Articles

Global source apportionment of aerosols into major emission regions and sectors over 1850–2017

Abstract. Anthropogenic emissions of aerosols and precursor gases have changed significantly in the past few decades around the world. In this study, the Explicit Aerosol Source Tagging (EAST) system is merged into the Energy Exascale Earth System Model version 1 (E3SMv1) to quantify the variations in anthropogenic aerosol concentrations, source contributions, and their subsequent radiative impact in four major emission regions across the globe during 1850–1980, 1980–2010, and 2010–2017. In North America and Europe, changes in anthropogenic PM2.5 were mainly caused by changes in emissions from local energy and industrial sectors. The local industrial sector caused the largest increase in PM2.5 in East Asia during 1980–2010 and decrease during 2010–2017. In South Asia, the increase in energy-related emissions dominated the rise in PM2.5 levels during 1980–2017. During 1850–1980, the increases in emissions from North America contributed to the increase in the European PM2.5 burden by 1.7 mg m−2 and the sources from the Europe were also responsible for the PM2.5 burden increase in East Asia and South Asia by about 1.0 mg m−2. During 1980–2010, East Asia contributed to an increase of 0.4–0.6 mg m−2 in the PM2.5 burden in North America and Europe, while South Asia contributed about 0.3 mg m−2. During 2010–2017, the contributions from East Asia to the PM2.5 burdens in the North America, Europe, and South Asia declined by 0.3–0.6 mg m−2 due to the clean air actions in China, while the contributions from South Asia still increased due to the continuous increase in emissions in South Asia. The historical changes in aerosols had an impact on effective radiative forcing through aerosol–radiation interactions (ERFari). During 1980–2010, a decline in North American aerosols resulted in a positive ERFari change (warming effect) in Europe and a decline in aerosols in Europe caused a warming effect in Russia and northern China. The changes in ERFari from the increase and decrease in aerosols in China during 1980–2010 and 2010–2017, respectively, are comparable in magnitude. The continuous aerosol increases in South Asia from 1980 to 2017 resulted in negative ERFari (cooling) changes in South Asia, Southeast Asia, and southern China.

175 The characteristic of aerosol emission from motors

175 The characteristic of aerosol emission from motors

Physical Mechanisms of Deep Convective Boundary Layer Leading to Dust Emission in the Taklimakan Desert

AbstractDeserts play an important role in the climate system, which is closely associated with the emission and transport of dust aerosols. Based on the intensive observation experiment in the Taklimakan Desert, the potential physical processes between the deep convective boundary layer (CBL) and dust emission are revealed in this study. Deep CBL enables the formation of clouds in the late afternoon, leading to significant cooling of surface. Large‐scale buoyant coherent structures thereby transform into the mechanical coherent structures confined near the surface. The responses promote the earlier occurrence of low‐level jet (LLJ) than in cloudless conditions, which allows the downward transport of LLJ momentum and substantially increases surface wind. Therefore, dust emission is initiated by strong wind at dusk and lasts for several hours. The results are useful to predict dust emissions and improve our understanding of distinctive boundary‐layer processes in desert regions.

Brazilian Atmospheric Inventories – BRAIN: a comprehensive database of air quality in Brazil

Abstract. Developing air quality management systems to control the impacts of air pollution requires reliable data. However, current initiatives do not provide datasets with large spatial and temporal resolutions for developing air pollution policies in Brazil. Here, we introduce the Brazilian Atmospheric Inventories (BRAIN), the first comprehensive database of air quality and its drivers in Brazil. BRAIN encompasses hourly datasets of meteorology, emissions, and air quality. The emissions dataset includes vehicular emissions derived from the Brazilian Vehicular Emissions Inventory Software (BRAVES), industrial emissions produced with local data from the Brazilian environmental agencies, biomass burning emissions from FINN – Fire INventory from the National Center for Atmospheric Research (NCAR), and biogenic emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN) (https://doi.org/10.57760/sciencedb.09858, Hoinaski et al., 2023a; https://doi.org/10.57760/sciencedb.09886, Hoinaski et al., 2023b). The meteorology dataset has been derived from the Weather Research and Forecasting Model (WRF) (https://doi.org/10.57760/sciencedb.09857, Hoinaski and Will, 2023a; https://doi.org/10.57760/sciencedb.09885, Hoinaski and Will, 2023c). The air quality dataset contains the surface concentration of 216 air pollutants produced from coupling meteorological and emissions datasets with the Community Multiscale Air Quality Modeling System (CMAQ) (https://doi.org/10.57760/sciencedb.09859, Hoinaski and Will, 2023b; https://doi.org/10.57760/sciencedb.09884, Hoinaski and Will, 2023d). We provide gridded data in two domains, one covering the Brazilian territory with 20×20 km spatial resolution and another covering southern Brazil with 4×4 km spatial resolution. This paper describes how the datasets were produced, their limitations, and their spatiotemporal features. To evaluate the quality of the database, we compare the air quality dataset with 244 air quality monitoring stations, providing the model's performance for each pollutant measured by the monitoring stations. We present a sample of the spatial variability of emissions, meteorology, and air quality in Brazil from 2019, revealing the hotspots of emissions and air pollution issues. By making BRAIN publicly available, we aim to provide the required data for developing air quality policies on municipal and state scales, especially for under-developed and data-scarce municipalities. We also envision that BRAIN has the potential to create new insights into and opportunities for air pollution research in Brazil.​​​​​​​

New insights into black carbon light absorption enhancement: A comprehensive analysis of two differential behaviors

High uncertainty in optical properties of black carbon (BC) involving heterogeneous chemistry has recently attracted increasing attention in the field of atmospheric climatology. To fill the gap in BC optical knowledge so as to estimate more accurate climate effects and serve the response to global warming, it is beneficial to conduct site-level studies on BC light absorption enhancement (Eabs) characteristics. Real-time surface gas and particulate pollutant observations during the summer and winter over Wuhan were utilized for the analysis of Eabs simulated by minimum R squared (MRS), considering two distinct atmospheric conditions (2015 and 2017). In general, differences in aerosol emissions led to Eabs differential behaviors. The summer average of Eabs (1.92 ± 0.55) in 2015 was higher than the winter average (1.27 ± 0.42), while the average (1.11 ± 0.20) in 2017 summer was lower than that (1.67 ± 0.69) in winter. Eabs and RBC (representing the mass ratio of non-refractory constituents to elemental carbon) constraints suggest that Eabs increased with the increase in RBC under the ambient condition enriched by secondary inorganic aerosol (SIA), with a maximum growth rate of 70.6% in 2015 summer. However, Eabs demonstrated a negative trend against RBC in 2017 winter due to the more complicated mixing state. The result arose from the opposite impact of hygroscopic SIA and absorbing OC/irregular distributed coatings on amplifying the light absorbency of BC. Furthermore, sensitivity analysis revealed a robust positive correlation (R > 0.9) between aerosol chemical compositions (including sulfate, nitrate, ammonium and secondary organic carbon), which could be significantly perturbed by only a small fraction of absorbing materials or restructuring BC through gaps filling. The above findings not only deepen the understanding of BC, but also provide useful information for the scientific decision-making in government to mitigate particulate pollution and obtain more precise BC radiative forcing.

AeroSense: Sensing Aerosol Emissions from Indoor Human Activities

The types of human activities occupants are engaged in within indoor spaces significantly contribute to the spread of airborne diseases through emitting aerosol particles. Today, ubiquitous computing technologies can inform users of common atmosphere pollutants for indoor air quality. However, they remain uninformed of the rate of aerosol generated directly from human respiratory activities, a fundamental parameter impacting the risk of airborne transmission. In this paper, we present AeroSense, a novel privacy-preserving approach using audio sensing to accurately predict the rate of aerosol generated from detecting the kinds of human respiratory activities and determining the loudness of these activities. Our system adopts a privacy-first as a key design choice; thus, it only extracts audio features that cannot be reconstructed into human audible signals using two omnidirectional microphone arrays. We employ a combination of binary classifiers using the Random Forest algorithm to detect simultaneous occurrences of activities with an average recall of 85%. It determines the level of all detected activities by estimating the distance between the microphone and the activity source. This level estimation technique yields an average of 7.74% error. Additionally, we developed a lightweight mask detection classifier to detect mask-wearing, which yields a recall score of 75%. These intermediary outputs are critical predictors needed for AeroSense to estimate the amounts of aerosol generated from an active human source. Our model to predict aerosol is a Random Forest regression model, which yields 2.34 MSE and 0.73 r2 value. We demonstrate the accuracy of AeroSense by validating our results in a cleanroom setup and using advanced microbiological technology. We present results on the efficacy of AeroSense in natural settings through controlled and in-the-wild experiments. The ability to estimate aerosol emissions from detected human activities is part of a more extensive indoor air system integration, which can capture the rate of aerosol dissipation and inform users of airborne transmission risks in real time.

Historical association between respiratory diseases hospitalizations and fire occurrence in the Pantanal wetland, Brazil

The occurrence of fires in the Pantanal wetland increases during drought conditions, resulting in higher aerosol emissions and deterioration of air quality. For the first time, a comprehensive assessment of the climatic effects on monthly Respiratory Disease Hospitalizations (RDH) was conducted in the Pantanal region. We investigated correlations among climatic variables and health indicators, focusing on three groups: RDH5 (<5 years old), RDH60 (≥60 years old), and RDH (total records) between 2003 and 2019 in all 17 municipalities of the region. We reported a 26–34% increase in RDH during drought years, as represented by the negative relationship between RDH and precipitation. Precipitation and humidity exert a primary control on fire occurrence and, hence, on respiratory illnesses in the Pantanal. Particulate material emissions are strongly related to increased fires and temperature across the region. Incidence rates among children and the elderly were four and three times higher, respectively, than general population, confirming the higher vulnerability of these groups. To effectively mitigate the risks and vulnerabilities associated with droughts, policies and action plans should prioritize vulnerable populations and implement targeted measures to reduce their exposure.

Comprehensive Analysis of Heavy Metal Aerosol Emissions and Health Risk from the Electrical Discharge Machining Process: A Control and Mitigation Approach for Green Manufacturing

Comprehensive Analysis of Heavy Metal Aerosol Emissions and Health Risk from the Electrical Discharge Machining Process: A Control and Mitigation Approach for Green Manufacturing

Atmosphere teleconnections from abatement of China aerosol emissions exacerbate Northeast Pacific warm blob events

During 2010 to 2020, Northeast Pacific (NEP) sea surface temperature (SST) experienced the warmest decade ever recorded, manifested in several extreme marine heatwaves, referred to as "warm blob" events, which severely affect marine ecosystems and extreme weather along the west coast of North America. While year-to-year internal climate variability has been suggested as a cause of individual events, the causes of the continuous dramatic NEP SST warming remain elusive. Here, we show that other than the greenhouse gas (GHG) forcing, rapid aerosol abatement in China over the period likely plays an important role. Anomalous tropospheric warming induced by declining aerosols in China generated atmospheric teleconnections from East Asia to the NEP, featuring an intensified and southward-shifted Aleutian Low. The associated atmospheric circulation anomaly weakens the climatological westerlies in the NEP and warms the SST there by suppressing the evaporative cooling. The aerosol-induced mean warming of the NEP SST, along with internal climate variability and the GHG-induced warming, made the warm blob events more frequent and intense during 2010 to 2020. As anthropogenic aerosol emissions continue to decrease, there is likely to be an increase in NEP warm blob events, disproportionately large beyond the direct radiative effects.

Increased summertime wildfire as a major driver of the clear-sky dimming in the Siberian Arctic from 2000 to 2020

A warming Arctic is expected to exacerbate wildfires in Siberia, potentially creating a critical feedback to the Arctic climate change. However, our understanding of these fire-climate interactions remains limited. This study investigated changes in East Siberian wildfires and their influence on fire emissions, aerosol optical depth (AOD), and the surface clear-sky insolation across the Siberian Arctic from 2000 to 2020 using satellite observations. Our analysis reveals a substantial increase in wildfires, with fire counts doubling (a 114% increase) and fire radiative power surging by 8.4 × 106 MW compared to the early 21st century. Over 93% of this increase occurred during the boreal summer months. These intensified wildfires led to a significant rise in aerosol emission (organic carbon, PM2.5, and black carbon) exceeding 75% in East Siberia. Consequently, fire-season AOD in the Siberian Arctic increased by 33% (6.0 × 10−2), with 85% (5.1 × 10−2) attributable to wildfire changes. The wildfire-associated increase in AOD resulted in enhanced clear-sky dimming of 4.1 ± 3.2 W m−2 across the Siberian Arctic from 2000 to 2020. These findings suggest a critical feedback mechanism: a warming Arctic drives increased wildfires in Siberia, which in turn significantly impact the Arctic surface radiative budget through enhanced clear-sky dimming. Future simulations and projections for the Arctic should prioritize incorporating the feedback effects of intensifying wildfires.

Global Climatology of Low‐Level‐Jets: Occurrence, Characteristics, and Meteorological Drivers

AbstractLow‐level jets (LLJs), vertical profiles with a wind speed maxima in the lowest hundred meters of the troposphere, have multiple impacts in the Earth system, but a global present‐day climatology based on contemporary data does not exist. We use the spatially and temporally complete data set from ERA5 reanalysis to compile a global climatology of LLJs for studying the formation mechanisms, characteristics, and trends during the period of 1992–2021. In the global mean, LLJs are detected 21% of the time with more cases over land (32%) than over the ocean (15%). We classified the LLJs into three categories: non‐polar land (LLLJ), polar land (PLLJ), and coastal (CLLJ) LLJs. For LLLJ, the averaged frequency of occurrence is 20% and 75% of them are associated with a near‐surface temperature inversion as a prerequisite for an inertial oscillation. PLLJs are also associated with a temperature inversion and occur even more frequently with 59% of the time. These are also the lowest and the strongest LLJs among the three categories. CLLJs are particularly frequent in some marine hotspots, situated along the west coast of continents, with neutral to unstable stratification close to the surfaces and a stably stratified layer aloft. We found distinct regional trends in both the frequency and intensity of LLJs over the past decades, which can have implications for the emission and transport of aerosols, and the transport of atmospheric moisture. Future studies could address changes in LLJs and the associated implications in more detail, based on the here released ERA5‐based LLJ data.

Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model

Abstract. Emissions of anthropogenic aerosol and their precursors are often prescribed in global aerosol models. Most of these emissions are spatially heterogeneous at model grid scales. When remapped from low-resolution data, the spatial heterogeneity in emissions can be lost, leading to large errors in the simulation. It can also cause the conservation problem if non-conservative remapping is used. The default anthropogenic emission treatment in the Energy Exascale Earth System Model (E3SM) is subject to both problems. In this study, we introduce a revised emission treatment for the E3SM Atmosphere Model (EAM) that ensures conservation of mass fluxes and preserves the original emission heterogeneity at the model-resolved grid scale. We assess the error estimates associated with the default emission treatment and the impact of improved heterogeneity and mass conservation in both globally uniform standard-resolution (∼ 165 km) and regionally refined high-resolution (∼ 42 km) simulations. The default treatment incurs significant errors near the surface, particularly over sharp emission gradient zones. Much larger errors are observed in high-resolution simulations. It substantially underestimates the aerosol burden, surface concentration, and aerosol sources over highly polluted regions, while it overestimates these quantities over less-polluted adjacent areas. Large errors can persist at higher elevation for daily mean estimates, which can affect aerosol extinction profiles and aerosol optical depth (AOD). We find that the revised treatment significantly improves the accuracy of the aerosol emissions from surface and elevated sources near sharp spatial gradient regions, with significant improvement in the spatial heterogeneity and variability of simulated surface concentration in high-resolution simulations. In the next-generation E3SM running at convection-permitting scales where the resolved spatial heterogeneity is significantly increased, the revised emission treatment is expected to better represent the aerosol emissions as well as their lifecycle and impacts on climate.

Monitoring of enteropathogenic Gram-negative bacteria in wastewater treatment plants: a multimethod approach

The wastewater treatment processes are associated with the emission of microbial aerosols, including enteropathogenic bacteria. Their presence in this work environment poses a real threat to the health of employees, both through the possibility of direct inhalation of the contaminated air and indirectly through the pollution of all types of surfaces with such bioaerosol particles. This study aimed to investigate the prevalence of enteropathogenic bacteria in the air, on surfaces, and in wastewater samples collected in four wastewater treatment plants (WWTPs). The effectiveness of conventional culture-biochemical, as well as spectrometric and molecular methods for the rapid detection of enteropathogenic bacteria at workstations related to particular stages of wastewater processing, was also evaluated. Bioaerosol, surface swab, and influent and effluent samples were collected from wastewater plants employing mechanical–biological treatment technologies. The air samples were collected using MAS-100 NT impactor placed at a height of 1.5 m above the floor or ground, simulating aspiration from the human breathing zone. Surface samples were collected with sterile swabs from different surfaces (valves, handles, handrails, and coveyor belts) at workplaces. The raw influent and treated effluent wastewater samples were aseptically collected using sterile bottles. The identification of bacterial entheropathogens was simultaneously conducted using a culture-based method supplemented with biochemical (API) tests, mass-spectrometry (MALDI TOF MS), and molecular (multiplex real-time PCR) methods. This study confirmed the common presence of bacterial pathogens (including enteropathogenic and enterotoxigenic Escherichia coli, Salmonella spp., Campylobacter spp., and Yersinia enterocolitica) in all air, surface, and wastewater samples at studied workplaces. Higher concentrations of enteropathogenic bacteria were observed in the air and on surfaces at workplaces where treatment processes were not hermetized. The results of this study underline that identification of enteropathogenic bacteria in WWTPs is of great importance for the correct risk assessment at workplaces. From the analytical point of view, the control of enteropathogenic bacterial air and surface pollution using rapid multiplex-PCR method should be routinely performed as a part of hygienic quality assessment in WWTPs.

An uncertain future change in aridity over the tropics

An ensemble of climate models from phase six of the Coupled Model Intercomparison Project shows that temperature and potential evapotranspiration (PET) are projected to increase globally towards the end of the 21st century. However, climate models show a spatially heterogeneous change in precipitation over the tropics. Consequently, future changes in aridity (a measure of water availability) are complex and location-dependent. We assess future changes in aridity using three climate models and several single-forcing experiments. Near-term (2021–2040) changes in aridity are small, and we focus instead on its long-term (2081–2100) changes. We show that the increase in greenhouse gases (GHG) primarily explains the spatial pattern, magnitude and ensemble spread of the long-term future changes in aridity. On this timescale, the effects of changes in emissions of anthropogenic aerosols are moderate compared to the effects of increases in atmospheric GHG concentrations. Model diversity in the responses to GHG concentration is large over northern Africa and North and South America. We suggest the large uncertainty is due to differences between models in simulating the effects of an increase in GHG concentrations on surface air temperature over the North Atlantic Ocean, on the interhemispheric temperature gradient, and on PET over North and South America.

Evaluation of isoprene emissions from the coupled model SURFEX–MEGANv2.1

Abstract. Isoprene, a key biogenic volatile organic compound, plays a pivotal role in atmospheric chemistry. Due to its high reactivity, this compound contributes significantly to the production of tropospheric ozone in polluted areas and to the formation of secondary organic aerosols. The assessment of biogenic emissions is of great importance for regional and global air quality evaluation. In this study, we implemented the biogenic emission model MEGANv2.1 (Model of Emissions of Gases and Aerosols from Nature, version 2.1) in the surface model SURFEXv8.1 (SURface EXternalisée in French, version 8.1). This coupling aims to improve the estimation of biogenic emissions using the detailed vegetation-type-dependent treatment included in the SURFEX vegetation ISBA (Interaction between Soil Biosphere and Atmosphere) scheme. This scheme provides vegetation-dependent parameters such as leaf area index and soil moisture to MEGAN. This approach enables a more accurate estimation of biogenic fluxes compared to the stand-alone MEGAN model, which relies on average input values for all vegetation types. The present study focuses on the assessment of the SURFEX–MEGAN model isoprene emissions. An evaluation of the coupled SURFEX–MEGAN model results was carried out by conducting a global isoprene emission simulation in 2019 and by comparing the simulation results with other MEGAN-based isoprene inventories. The coupled model estimates a total global isoprene emission of 443 Tg in 2019. The estimated isoprene is within the range of results obtained with other MEGAN-based isoprene inventories, ranging from 311 to 637 Tg. The spatial distribution of SURFEX–MEGAN isoprene is consistent with other studies, with some differences located in low-isoprene-emission regions. Several sensitivity tests were conducted to quantify the impact of different model inputs and configurations on isoprene emissions. Using different meteorological forcings resulted in a ±5 % change in isoprene emissions using MERRA (Modern-Era Retrospective analysis for Research and Applications) and IFS (Integrated Forecasting System) compared with ERA5. The impact of using different emission factor data was also investigated. The use of PFT (plant functional type) spatial coverage and PFT-dependent emission potential data resulted in a 12 % reduction compared to using the isoprene emission potential gridded map. A significant reduction of around 38 % in global isoprene emissions was observed in the third sensitivity analysis, which applied a parameterization of soil moisture deficit, particularly in certain regions of Australia, Africa, and South America. The significance of coupling the SURFEX and MEGAN models lies particularly in the ability of the coupled model to be forced with meteorological data from any period. This means, for instance, that this system can be used to predict biogenic emissions in the future. This aspect of our work is significant given the changes that biogenic organic compounds are expected to undergo as a result of changes in their climatic factors.

Simple retrieval of the real part of the refractive index for ambient aerosols using extinction coefficient analysis via camera and volume size distribution

This study explored a novel approach for estimating the variations in the refractive index (RI) of aerosols, which is a crucial optical parameter that contains information about particle scattering and absorption. RI is often subject to constraints related to observation time, wavelength selection, and analysis methods. To overcome these limitations, we employed real-time continuous measurements using a camera and optical particle counter (OPC) equipment and applied optimization techniques based on the Mie theory to reverse-calculate changes in the refractive index. Our methodology uses a camera to measure the aerosol extinction coefficients at three different wavelengths within the RGB spectrum (597 nm, 534 nm, and 459 nm), whereas OPC observations provide information on particle size distribution (0.127–17.58 μm as radius). Because the extinction efficiency at known wavelengths varies with the refractive index according to the Mie theory, we retrieved the refractive index, which is an unknown variable, from the extinction coefficient equation. We focused on the real part of the RI because it is challenging to discern the imaginary part of the RI from the visible wavelengths. Our observations were conducted in areas near Busan Harbor and in mixed residential regions. The real part of the RI was determined to be 1.53 ± 0.12. During periods of observed dust events, the refractive index's real part was 1.62 ± 0.05, while during periods anticipated to have emissions of fine aerosols, it was 1.51 ± 0.10. The retrieved RI fell within a range similar to that in other studies, and the changes in the refractive index showed meaningful patterns when analyzed for variations in the particle size distribution and changes in the scattering coefficient. This approach has the potential to advance our understanding of aerosol optical properties and can be applied to real-time analyses with a relatively simple equipment setup, thereby opening new possibilities for its use as a critical variable in optical measurements and environmental models.

Possible Interrelations of Space Weather and Seismic Activity: An Implication for Earthquake Forecast

The statistical analysis of the impact of the top 50 X-class solar flares (1997–2024) on global seismic activity as well as on the earthquake preparation zones located in the illuminated part of the globe and in an area of 5000 km around the subsolar point was carried out. It is shown by a method of epoch superposition that for all cases, an increase in seismicity is observed, especially in the region around the subsolar point (up to 33%) during the 10 days after the solar flare in comparison with the preceding 10 days. The case study of the aftershock sequence of a strong Mw = 9.1 earthquake (Sumatra–Andaman Islands, 26 December 2004) after the solar flare of X10.16 class (20 January 2005) demonstrated that the number of aftershocks with a magnitude of Mw ≥ 2.5 increases more than 17 times after the solar flare with a delay of 7–8 days. For the case of the Darfield earthquake (Mw = 7.1, 3 September 2010, New Zealand), it was shown that X-class solar flares and M probably triggered two strong aftershocks (Mw = 6.1 and Mw = 5.9) with the same delay of 6 days on the Port Hills fault, which is the most sensitive to external electromagnetic impact from the point of view of the fault electrical conductivity and orientation. Based on the obtained results, the possible application of natural electromagnetic triggering of earthquakes is discussed for the earthquake forecast using confidently recorded strong external electromagnetic triggering impacts on the specific earthquake preparation zones, as well as ionospheric perturbations due to aerosol emission from the earthquake sources recorded by satellites.

Quantifying the air pollution impacts on solar photovoltaic capacity factors and potential benefits of pollution control for the solar sector in China

Solar photovoltaic (PV) plays a crucial role in China's energy transition. However, air pollution diminishes solar radiation resources, thereby reducing PV power generation efficiency. This study aims to quantify the impacts of air pollution on PV capacity factors in China while emphasizing the geographically specific potential benefits of improved air quality for the future PV sector. Using a PV power generation evaluation model, this study estimated solar PV capacity factors from 1961 to 2016 under both all-sky and clear-sky scenarios. Also, the spatiotemporal patterns of air pollution-induced capacity factor changes were analyzed. The results indicate that the all-sky and clear-sky PV capacity factors showed consistent annual anomalies, suggesting that air pollution due to aerosol emissions drove PV capacity factor temporal evolutions and trends in China. From 1961 to 1990, the national average clear-sky PV capacity factors for fixed modules with optimal tilt angle showed a significant decreasing trend of −0.0053 per decade, whereas from 1990 to 2016, an upward trend of 0.0030 per decade was observed. Compared with fixed modules, tracking systems suffered from greater productivity losses due to air pollution. In comparison to 1961–1965 averages, the provincial PV capacity factors for 2012–2016 decreased by 0.48–13.54%, 1.15–11.40%, 1.06–14.83%, and 1.31–16.51% for fixed modules with optimal tilt angle, horizontal fixed, one-axis horizontal tracking, and two-axis tracking modules, respectively, with decreases of 7–17% in the central and southeast. Furthermore, according to the provincial PV installation targets projected in China's 14th Five-Year Plan, national solar PV power generation was expected to increase by 81.333 TWh to 1069.997 TWh in 2025 with average PV capacity factors for 1961–1965, compared to 2012–2016 averages. In a scenario of keeping grid parity, additional power generation would offer an economic benefit of approximately 30.102 billion CNY.

Impact of greening trends on biogenic volatile organic compound emissions in China from 1985 to 2022: Contributions of afforestation projects

The rapid expansion of green areas in China has enhanced carbon sinks, but it also presents challenges regarding increased biogenic volatile organic compound (BVOC) emissions. This study examines the impact of greening trends on BVOC emissions in China from 1985 to 2001 and from 2001 to 2022, focusing on evaluating long-term trends in BVOC emissions within eight afforestation project areas during these two periods. Emission factors for 62 dominant tree species and provincial Plant Functional Types were updated. The BVOC emission inventories were developed for China at a spatial resolution of 27 km × 27 km using the Model of Emissions of Gases and Aerosols from Nature. The national BVOC emissions in 2018 were estimated at 54.24 Tg, with isoprene, monoterpenes, sesquiterpenes, and other BVOC contributing 26.94 Tg, 2.29 Tg, 0.44 Tg, and 24.57 Tg, respectively. Over the past 37 years, BVOC emissions experienced a slow growth rate of 1.7 % (0.79 Tg) during 1985–2001, followed by a significant increase of 12 % (6 Tg) from 2001 to 2022. BVOC emissions in the eight afforestation project areas increased by 2 % and 20 % during the two periods. From 2001 to 2022, at the regional scale, the Shelterbelt program for the middle reaches of the Yellow River area exhibited the largest rate of increase (43 %) in BVOC emissions. The Shelterbelt program for the upper and middle reaches of the Yangtze River made the most largest contribution (45 %) to the national increase in BVOC emissions. Afforestation projects have shifted towards planting more broadleaf trees than needleleaf trees from 2001 to 2022, and there also showed a change from herbaceous plants to broadleaf trees. These trends have led to higher average emission factors for vegetation, resulting in increased BVOC emissions. It underscores the importance of considering BVOC emissions when evaluating afforestation initiatives, emphasizing the need to balancing ecological benefits with potential atmospheric consequences.

Evaluating the potential of iron-based interventions in methane reduction and climate mitigation

Keeping global surface temperatures below international climate targets will require substantial measures to control atmospheric CO2 and CH4 concentrations. Recent studies have focused on interventions to decrease CH4 through enhanced atmospheric oxidation. Here for the first time using a set of models, we evaluate the effect of adding iron aerosols to the atmosphere to enhance molecular chlorine production, and thus enhance the atmospheric oxidation of methane and reduce its concentration. Using different iron emission sensitivity scenarios, we examine the potential role and impact of enhanced iron emissions on direct interactions with solar radiation, and on the chemical and radiative response of methane. Our results show that the impact of iron emissions on CH4 depends sensitively on the location of the iron emissions. In all emission regions there is a threshold in the amount of iron that must be added to remove methane. Below this threshold CH4 increases. Even once that threshold is reached, the iron-aerosol driven chlorine-enhanced impacts on climate are complex. The radiative forcing of both methane and ozone are decreased in the most efficient regions but the direct effect due to the addition of absorbing iron aerosols tends to warm the planet. Adding any anthropogenic aerosol may also cool the planet due to aerosol cloud interactions, although these are very uncertain, and here we focus on the unique properties of adding iron aerosols. If the added emissions have a similar distribution as current shipping emissions, our study shows that the amount of iron aerosols that must be added before methane decreases is 2.5 times the current shipping emissions of iron aerosols, or 6 Tg Fe yr−1 in the most ideal case examined here. Our study suggests that the photoactive fraction of iron aerosols is a key variable controlling the impact of iron additions and poorly understood. More studies of the sensitivity of when, where and how iron aerosols are added should be conducted. Before seriously considering this method, additional impacts on the atmospheric chemistry, climate, environmental impacts and air pollution should be carefully assessed in future studies since they are likely to be important.