Changes In Anthropogenic Emissions Research Articles

A comparison of meteorological normalization of PM2.5 by multiple linear regression, general additive model, and random forest methods

PM2.5 is still one of the major atmospheric pollutants worldwide. Extracting contributions of anthropogenic emission control from the observed PM2.5 variations (PM2.5_anth), which are also strongly affected by meteorological changes, is critical for effective pollution control. Statistical and machine learning methods are usually used for such purpose, but the effectiveness of these methods is hard to evaluate due to the lack of observed anthropogenic contributions. In this study, we use the chemical transport model GEOS-Chem standard simulation to mimic PM2.5 variability in the real atmosphere, and use the model simulation with fixed meteorological fields as the “true value” for PM2.5_anth. We evaluate the effectiveness of three methods in meteorological normalization of PM2.5 on decadal (2006–2017) and synoptic (one month) scale: multiple linear regression (MLR), general additive model (GAM), and random forest (RF) algorithm. For meteorological normalization of PM2.5 on decadal scale, 67–72% of the MLR simulations show positive biases and 56–75% of the RF simulations show negative biases. The “true value” of PM2.5_anth falls within the range of meteorological normalization results of the three methods in most cases, but consistent positive/negative biases are observed in ∼30% of the cases, when meteorological changes dominate PM2.5 variability. In addition, the biases are correlated to the contribution of meteorological changes. As such, multiple statistical or machine learning methods are recommended to quantify the uncertainties associated with method choice in cases anthropogenic emission changes dominate PM2.5 variability. On synoptic scale, RF performs better in reproducing the daily variations of the PM2.5_anth differences than MLR (GAM) in all (83% of) the cases, and is recommended for meteorological normalization of PM2.5 in short-term in eastern China.

Estimating future climate change impacts on human mortality and crop yields via air pollution

Future climate change may bring local benefits or penalties to surface air pollution, resulting from changing temperature, precipitation, and transport patterns, as well as changes in climate-sensitive natural precursor emissions. Here, we estimate the climate penalties and benefits at the end of this century with regard to surface ozone and fine particulate matter (PM[Formula: see text]; excluding dust and smoke) using a one-way offline coupling between a general circulation model and a global 3-D chemical-transport model. We archive meteorology for the present day (2005 to 2014) and end of this century (2090 to 2099) for seven future scenarios developed for Phase 6 of the Coupled Model Intercomparison Project. The model isolates the impact of forecasted anthropogenic precursor emission changes versus that of climate-only driven changes on surface ozone and PM[Formula: see text] for scenarios ranging from extreme mitigation to extreme warming. We then relate these changes to impacts on human mortality and crop production. We find ozone penalties over nearly all land areas with increasing warming. We find net benefits due to climate-driven changes in PM[Formula: see text] in the Northern Extratropics, but net penalties in the Tropics and Southern Hemisphere, where most population growth is forecast for the coming century.

Detecting changes in anthropogenic light emissions: Limits due to atmospheric variability

Monitoring the evolution of the anthropogenic light emissions is a priority task in light pollution research. Among the complementary approaches that can be adopted to achieve this goal stand out those based on measuring the direct radiance of the sources at ground level or from low Earth orbit satellites, and on measuring the scattered radiance (known as artificial night sky brightness or skyglow) using networks of ground-based sensors. The terrestrial atmosphere is a variable medium interposed between the sources and the measuring instruments, and the fluctuation of its optical parameters sets a lower limit for the actual source emission changes that can be confidently detected. In this paper we analyze the effect of the fluctuations of the molecular and aerosol optical depths. It is shown that for reliably detecting changes in the anthropogenic light emissions of order ∼1 % per year, the inter-annual variability of the annual means of these atmospheric parameters in the measurement datasets must be carefully controlled or efficiently corrected for.

Anthropogenic Fingerprint Detectable in Upper Tropospheric Ozone Trends Retrieved from Satellite.

Tropospheric ozone (O3) is a strong greenhouse gas, particularly in the upper troposphere (UT). Limited observations point to a continuous increase in UT O3 in recent decades, but the attribution of UT O3 changes is complicated by large internal climate variability. We show that the anthropogenic signal ("fingerprint") in the patterns of UT O3 increases is distinguishable from the background noise of internal variability. The time-invariant fingerprint of human-caused UT O3 changes is derived from a 16-member initial-condition ensemble performed with a chemistry-climate model (CESM2-WACCM6). The fingerprint is largest between 30°S and 40°N, especially near 30°N. In contrast, the noise pattern in UT O3 is mainly associated with the El Niño-Southern Oscillation (ENSO). The UT O3 fingerprint pattern can be discerned with high confidence within only 13 years of the 2005 start of the OMI/MLS satellite record. Unlike the UT O3 fingerprint, the lower tropospheric (LT) O3 fingerprint varies significantly over time and space in response to large-scale changes in anthropogenic precursor emissions, with the highest signal-to-noise ratios near 40°N in Asia and Europe. Our analysis reveals a significant human effect on Earth's atmospheric chemistry in the UT and indicates promise for identifying fingerprints of specific sources of ozone precursors.

Responses of fine particulate matter (PM2.5) air quality to future climate, land use, and emission changes: Insights from modeling across shared socioeconomic pathways

Air pollution induced by fine particulate matter with diameter ≤ 2.5 μm (PM2.5) poses a significant challenge for global air quality management. Understanding how factors such as climate change, land use and land cover change (LULCC), and changing emissions interact to impact PM2.5 remains limited. To address this gap, we employed the Community Earth System Model and examined both the individual and combined effects of these factors on global surface PM2.5 in 2010 and projected scenarios for 2050 under different Shared Socioeconomic Pathways (SSPs). Our results reveal biomass-burning and anthropogenic emissions as the primary drivers of surface PM2.5 across all SSPs. Less polluted regions like the US and Europe are expected to experience substantial PM2.5 reduction in all future scenarios, reaching up to ~5 μg m−3 (70 %) in SSP1. However, heavily polluted regions like India and China may experience varied outcomes, with a potential decrease in SSP1 and increase under SSP3. Eastern China witness ~20 % rise in PM2.5 under SSP3, while northern India may experience ~70 % increase under same scenario. Depending on the region, climate change alone is expected to change PM2.5 up to ±5 μg m−3, while the influence of LULCC appears even weaker. The modest changes in PM2.5 attributable to LULCC and climate change are associated with aerosol chemistry and meteorological effects, including biogenic volatile organic compound emissions, SO2 oxidation, and NH4NO3 formation. Despite their comparatively minor role, LULCC and climate change can still significantly shape future air quality in specific regions, potentially counteracting the benefits of emission control initiatives. This study underscores the pivotal role of changes in anthropogenic emissions in shaping future PM2.5 across all SSP scenarios. Thus, addressing all contributing factors, with a primary focus on reducing anthropogenic emissions, is crucial for achieving sustainable reduction in surface PM2.5 levels and meeting sustainable pollution mitigation goals.

Characterization of winter PM2.5 source contributions and impacts of meteorological conditions and anthropogenic emission changes in the Sichuan Basin, 2002–2020

In this study, the Weather Research and Forecasting (WRF) model and Community Multiscale Air Quality–Integrated Source Apportionment Method (CMAQ–ISAM) were utilized, which were integrated with the Multiresolution Emission Inventory for China (MEIC) emission inventory, to simulate winter PM2.5 concentrations, regional transport, and changes in emission source contributions in the Sichuan basin (SCB) from 2002 to 2020, considering variations in meteorological conditions and anthropogenic emissions. The results indicated a gradual decrease in the basin's winter average PM2.5 concentration from 300 μg/m3 to 120 μg/m3, with the most significant decrease occurring after 2014, reflecting the actual impact of China's air pollution control measures. Spatially, the main pollution area shifted from Chongqing to Chengdu and the western basin. The sources of PM2.5 at the eastern and western margins of the basin have remained stable and have been dominated by local emissions for many years, while the sources of PM2.5 in the central part of the basin have evolved from a multiregional co-influenced source during the early period to a high proportion of local emissions; except for boundary condition sources, residential sources were the main PM2.5 sources in the basin (approximately 29.70 %), followed by industrial sources (approximately 14.11 %). Industrial sources exhibited higher contributions in Chengdu and Chongqing and gradually stabilized with residential sources over the years, while residential sources dominated in the eastern and western parts of the basin and exhibited a declining trend. Meteorological conditions exacerbated pollution in the whole basin from 2008 to 2014, especially in the west (21–40 μg/m3). The eastern basin and Chongqing exhibited more years with alleviated meteorological pollution, including a 40+ μg/m3 decrease in Chongqing from 2002 to 2005. Reduced anthropogenic emissions alleviated annual pollution levels, with a greater reduction (> −20 μg/m3) after 2011 due to pollution control measures.

Prediction of changes in war-induced population and CO2 emissions in Ukraine using social media

Monitoring the changes in population and anthropogenic CO2 emissions caused by geopolitical conflicts is significant for humanitarian assistance and also for revealing the CO2 emission patterns of human activities. However, the changes in population and anthropogenic CO2 emissions are highly dynamic, and representative survey data are generally unavailable. We monitor the near-real-time and fine-grained changes in war-induced population and anthropogenic CO2 emissions in Ukraine through social media data. One year after the invasion, over 11 million Ukrainians are displaced from the baseline 0.1∘*0.1∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${0.1}^{\\circ}\\,*\\,{0.1}^{\\circ}$$\\end{document} gridded regions. There is a significant correlation between the estimated changes and the reference changes for each month in all CO2 emission sectors, with R2 respectively ranging from 0.57 to 0.93, 0.41 to 0.9, 0.74 to 0.99 for residential consumption, ground transport, and industry sectors. Overall, the proposed method provides a new perspective to monitor Ukrainian refugee crisis and measure the spatio-temporal response of anthropogenic CO2 emissions.

Ozone Pollution in the North China Plain during the 2016 Air Chemistry Research in Asia (ARIAs) Campaign: Observations and a Modeling Study

To study air pollution in the North China Plain (NCP), the Air Chemistry Research in Asia (ARIAs) campaign conducted airborne measurements of air pollutants in spring 2016. High pollutant concentrations, with O3 > 100 ppbv, CO > 500 ppbv, and NO2 > 10 ppbv, were observed. CMAQ simulations with the 2010 EDGAR emissions capture the spatial and temporal variations in ozone and its major precursors such as NO2 and VOCs, with significant underestimation. Differences between CMAQ simulations and satellite observations reflect changes in anthropogenic emissions, decreased NOx emissions in megacities such as Beijing, but slight increases in other cities and rural areas. CMAQ also underestimates HCHO and CO, suggesting adjustments of the 2010 EDGAR emissions are necessary. HCHO/NO2 column ratios derived from OMI measurements and CMAQ simulations show that VOC-sensitive chemistry dominates the ozone photochemical production in eastern China, suggesting the importance of tightening regulations on anthropogenic VOC emissions. After adjusting emissions based on satellite observations, better model performance was achieved. Because of the VOC-sensitive environment in ozone chemistry over the NCP, the underestimation of anthropogenic emissions could be important for CMAQ simulations, while future study and regulations should focus on VOC emissions with continuous controls on NOx emissions in China.

Human-induced intensified seasonal cycle of sea surface temperature

Changes in the seasonal cycle of sea surface temperature (SST) have far-reaching ecological and societal implications. Previous studies have found an intensified SST seasonal cycle under global warming, but whether such changes have emerged in historical records remains largely unknown. Here, we reveal that the SST seasonal cycle globally has intensified by 3.9 ± 1.6% in recent four decades (1983–2022), with hotspot regions such as the northern subpolar gyres experiencing an intensification of up to 10%. Increased greenhouse gases are the primary driver of this intensification, and decreased anthropogenic aerosols also contribute. These changes in anthropogenic emissions lead to shallower mixed layer depths, reducing the thermal inertia of upper ocean and enhancing the seasonality of SST. In addition, the direct impacts of increased ocean heat uptake and suppressed seasonal amplitude of surface heat flux also contribute in the North Pacific and North Atlantic. The temperature seasonal cycle is intensified not only at the ocean surface, but throughout the mixed layer. The ramifications of this intensified SST seasonal cycle extend to the seasonal variation in upper-ocean oxygenation, a critical factor for most ocean ecosystems.

Long-term trends and response of wet ammonia deposition to changes in anthropogenic emissions in the Pearl River delta of China

The Pearl River Delta (PRD) region has been identified as a significant hotspot of wet ammonium deposition. However, the absence of long-term monitoring data in the area hinders the comprehension of the historical trends and changes in wet NH4+-N deposition in response to emissions, which interferes with the ability to make effective decisions. This study has analyzed the long-term trends of wet NH4+-N deposition flux and has quantified the effect of anthropogenic emissions and meteorological factors at a typical urban site and a typical forest site in the PRD region from 2009 to 2020. It revealed a significant decreasing trend in wet NH4+-N flux in both the typical urban and forest areas of the PRD region, at -6.2%/year (p < 0.001) and -3.3%/year (p < 0.001), respectively. Anthropogenic emissions are thought to have contributed 47%–57% of the wet NH4+-N deposition trend over the past 12 years compared to meteorological factors. Meteorological conditions dominated the inter-annual fluctuations in wet NH4+-N deposition with an absolute contribution of 46%–52%, while anthropogenic emissions change alone explained 10%–31%. NH3 emissions have the greatest impact on the urban area among anthropogenic emission factors, while SO2 emissions have the greatest impact on the forest area. Additionally, precipitation was identified as the primary meteorological driver for both sites. Our findings also imply that the benefits of NH3 emissions reductions might not immediately emerge due to interference from weather-related factors.

Co-occurrence of ozone and PM2.5 pollution in urban/non-urban areas in eastern China from 2013 to 2020: Roles of meteorology and anthropogenic emissions

We applied a three-dimensional (3-D) global chemical transport model (GEOS-Chem) to evaluate the influences of meteorology and anthropogenic emissions on the co-occurrence of ozone (O3) and fine particulate matter (PM2.5) pollution day (O3-PM2.5PD) in urban and non-urban areas of the Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) regions during the warm season (April–October) from 2013 to 2020. The model captured the observed O3-PM2.5PD trends and spatial distributions well. From 2013 to 2020, with changes in both anthropogenic emissions and meteorology, the simulated values of O3-PM2.5PD in the urban (non-urban) areas of the BTH and YRD regions were 424.8 (330.1) and 309.3 (286.9) days, respectively, suggesting that pollution in non-urban areas also warrants attention. The trends in the simulated values of O3-PM2.5PD were −0.14 and −0.15 (+1.18 and +0.81) days yr−1 in the BTH (YRD) urban and non-urban areas, respectively. Sensitivity simulations revealed that changes in anthropogenic emissions decreased the occurrence of O3-PM2.5PD, with trends of −0.99 and −1.23 (−1.47 and −1.92) days yr−1 in the BTH (YRD) urban and non-urban areas, respectively. Conversely, meteorological conditions could exacerbate the frequency of O3-PM2.5PD, especially in the urban YRD areas, but less notably in the urban BTH areas, with trends of +2.11 and +0.30 days yr−1, respectively, owing to changes in meteorology only. The increases in T2m_max and T2m were the main meteorological factors affecting O3-PM2.5PD in most BTH and YRD areas. Furthermore, by conducting sensitivity experiments with different levels of pollutant precursor reductions in 2020, we found that volatile organic compound (VOC) reductions primarily benefited O3-PM2.5PD decreases in urban areas and that NOx reductions more notably influenced those in non-urban areas, especially in the YRD region. Simultaneously, reducing VOC and NOx emissions by 50 % resulted in considerable O3-PM2.5PD decreases (58.8–72.6 %) in the urban and non-urban areas of the BTH and YRD regions. The results of this study have important implications for the control of O3-PM2.5PD in the urban and non-urban areas of the BTH and YRD regions.

Anthropogenic Influence on Tropospheric Reactive Bromine Since the Pre‐industrial: Implications for Arctic Ice‐Core Bromine Trends

AbstractTropospheric reactive bromine (Bry) influences the oxidation capacity of the atmosphere by acting as a sink for ozone and nitrogen oxides. Aerosol acidity plays a crucial role in Bry abundances through acid‐catalyzed debromination from sea‐salt‐aerosol, the largest global source. Bromine concentrations in a Russian Arctic ice‐core, Akademii Nauk, show a 3.5‐fold increase from pre‐industrial (PI) to the 1970s (peak acidity, PA), and decreased by half to 1999 (present day, PD). Ice‐core acidity mirrors this trend, showing robust correlation with bromine, especially after 1940 (r = 0.9). Model simulations considering anthropogenic emission changes alone show that atmospheric acidity is the main driver of Bry changes, consistent with the observed relationship between acidity and bromine. The influence of atmospheric acidity on Bry should be considered in interpretation of ice‐core bromine trends.

Bias correction of OMI HCHO columns based on FTIR and aircraft measurements and impact on top-down emission estimates

Abstract. Spaceborne formaldehyde (HCHO) measurements constitute an excellent proxy for the sources of non-methane volatile organic compounds (NMVOCs). Past studies suggested substantial overestimations of NMVOC emissions in state-of-the-art inventories over major source regions. Here, the QA4ECV (Quality Assurance for Essential Climate Variables) retrieval of HCHO columns from OMI (Ozone Monitoring Instrument) is evaluated against (1) FTIR (Fourier-transform infrared) column observations at 26 stations worldwide and (2) aircraft in situ HCHO concentration measurements from campaigns conducted over the USA during 2012–2013. Both validation exercises show that OMI underestimates high columns and overestimates low columns. The linear regression of OMI and aircraft-based columns gives ΩOMI=0.651Ωairc+2.95×1015 molec.cm-2, with ΩOMI and Ωairc the OMI and aircraft-derived vertical columns, whereas the regression of OMI and FTIR data gives ΩOMI=0.659ΩFTIR+2.02×1015 molec.cm-2. Inverse modelling of NMVOC emissions with a global model based on OMI columns corrected for biases based on those relationships leads to much-improved agreement against FTIR data and HCHO concentrations from 11 aircraft campaigns. The optimized global isoprene emissions (∼445Tgyr-1) are 25 % higher than those obtained without bias correction. The optimized isoprene emissions bear both striking similarities and differences with recently published emissions based on spaceborne isoprene columns from the CrIS (Cross-track Infrared Sounder) sensor. Although the interannual variability of OMI HCHO columns is well understood over regions where biogenic emissions are dominant, and the HCHO trends over China and India clearly reflect anthropogenic emission changes, the observed HCHO decline over the southeastern USA remains imperfectly elucidated.

Differential response of various pollutant-meteorology factors on O3 in key regions of China: Based on multiple methods and datasets

Scientific control is urgently required to address O3 pollution in key regions of China. Therefore, based on air pollutant concentrations and meteorological datasets, the methods including distributed lag nonlinear models, Kolmogorov–Zurbenko filter and stepwise multiple linear regression (SMLR) were applied to analyze and clarify the response of pollution and meteorological factors to O3, as well as the comprehensive impact under different time dimensions in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Chengdu-Chongqing regions (CY). Results indicate O3 concentrations in the study area fluctuated at high pollution levels. The effects of various air pollutants and meteorological factors on O3 varied among cities. Temperature is the dominant driver for O3, followed by solar radiation and relative humidity. The influence of wind vector indicates different transport sources of O3 and its precursors. Direct photochemical process based on SMLR fitting coefficient calculation is the main pathway for O3 generation, with contribution of 68.7%–93.8%. In terms of air-pollutant factors, U-shaped response between PM2.5 and O3 in all cities highlighted the interaction of the two air pollutants. The undeniable impact of NO2 on O3 is reflected in its range of effect. Meteorological adjustments led to −10.4–15.1 μg/m3 variations on O3 during 2014–2021, but performed obvious spatiotemporal differences. The changes in anthropogenic emissions deteriorated O3 pollution from 2014 to 2017, while have fluctuated effect since 2018. From the actual cases in special periods, in order to alleviate O3 pollution, it is necessary to strengthen the understanding of the synergistic contribution of meteorology and anthropogenic emissions.

Ambient volatile organic compounds concentration variation characteristics and source apportionment in Lanzhou, China during the COVID-19 lockdown

During the COVID-19 lockdown, PM2.5, ozone and precursor NOx were widely reported, but changes on volatile organic compounds (VOCs) were scarcely reported. It is important to understand the impact of drastic changes in anthropogenic emissions on the levels of VOCs. In this study, VOCs were collected with Summa tank for monitoring before (Period I), during (Period II) and after (Period III) the COVID-19 lockdown in Lanzhou, Northwest China. During the lockdown, the average concentration of VOCs was 49.01 ± 20.63 ppbv, the total mixing ratio was 39.3 % and 48.5 % lower than Period I and Period III, at the same time alkanes, alkenes, aromatics, halo hydrocarbons decreased by 45.5 % and 46.4 %, 20.2 % and 15.1 %, 21.0 % and 51.4 %, 42.9 % and 61.6 %, respectively. The ratio of benzene/toluene (B/T) increased from 0.85 (Period I) to 1.40 (Period II) and finally to 1.83 (Period III). The trend of isobutane to n-butane （IB/NB）was 0.28 (Period I)-0.75 (Period II)-0.92 (Period III). The above results indicated that traffic source contribute more to VOCs in the Period I, and natural gas, coal and biomass combustion are the main sources during the Period II and III. The xylene/ethylbenzene (X/E) ratio showed a tendence higher in the middle (1.42) and lower on both sides (0.78 and 0.57, respectively), which indicated that the aging of gas masses during the lockdown is lower than Period I and III. Five factors resolved by the positive matrix factorization (PMF) model were Liquefied Petroleum Gas (LPG) and vehicle exhaust emission, biomass/coal burning, industrial coatings/solvents, industrial process and gasoline exhaust. The source apportionment calculation consistent with the ratio of B/T and IB/NB showed that the contribution of biomass/coal burning increased from 13.1 % (Period I) to 21.8 % (Period II), while the contribution of LPG and vehicle exhaust emission decreased from 45.8 % to 31.5 %.

Response of organic aerosol in Beijing to emission reductions during the XXIV Olympic Winter Games

Organic aerosol (OA) serves as a crucial component of fine particulate matter. However, the response of OA to changes in anthropogenic emissions remains unclear due to its complexity. The XXIV Olympic Winter Games (OWG) provided real atmospheric experimental conditions on studying the response of OA to substantial emission reductions in winter. Here, we explored the sources and variations of OA based on the observation of aerosol mass spectrometer (AMS) combined with positive matrix factorization (PMF) analysis in urban Beijing during the 2022 Olympic Winter Games. The influences of meteorological conditions on OA concentrations were corrected by CO and verified by deweathered model. The CO-normalized primary OA (POA) concentrations from traffic, cooking, coal and biomass burning during the OWG decreased by 39.8 %, 23.2 % and 65.0 %, respectively. Measures controlling coal and biomass burning were most effective in reducing POA during the OWG. For the CO-normalized concentration of secondary OA (SOA), aqueous-phase related oxygenated OA decreased by 51.8 % due to the lower relative humidity and emission reduction in precursors, while the less oxidized‑oxygenated OA even slightly increased as the enhanced atmospheric oxidation processes may partially offset the efficacy of emission control. Therefore, more targeted reduction of organic precursors shall be enhanced to lower atmospheric oxidation capacity and mitigate SOA pollution.

Responses of Ecosystem Productivity to Anthropogenic Ozone and Aerosols at the 2060

AbstractTerrestrial ecosystems help mitigate global warming by sequestering atmospheric carbon dioxide (CO2) through plant photosynthesis, the rate of which is affected by surface ozone (O3) and aerosols under simultaneous impacts of climate change and rising CO2. While the changes in anthropogenic emissions perturb atmospheric components, their consequent impacts on ecosystem productivity in the future climate remain unclear. Here, we apply a fully coupled climate‐chemistry‐vegetation model, ModelE2‐YIBs, to explore the effects of O3 and aerosols from anthropogenic emissions on global gross primary productivity (GPP) under different emission scenarios at 2060. At the present day, anthropogenic air pollutants induce a GPP loss of −1.67 Pg[C] (−4%) in boreal summer with the contributions of −2.18 Pg[C] by O3 and +0.52 Pg[C] by aerosols. At 2060, the detrimental effect of air pollutants on GPP is exacerbated to −1.85 Pg[C] under a high emissions scenario but alleviated to −0.59 Pg[C] under a low emission scenario. The mitigated GPP loss in the latter scenario is owing to the effective control of anthropogenic emissions that on average reduces surface O3 concentrations by 8.14 ppbv globally relative to 2010. Although the CO2 fertilization effect is weaker in the low emission scenario, the strong decline in air pollutants brings additional GPP gains compared to the high scenario. Regionally, such GPP amelioration is close to or even overweighs the CO2 fertilization effect in eastern China and United States, suggesting that the deep cut of anthropogenic emissions can effectively promote future ecosystem productivity over the nowadays polluted regions.

Impacts of anthropogenic emissions and meteorology on spring ozone differences in San Antonio, Texas between 2017 and 2021

San Antonio has been designated as ozone nonattainment under the current National Ambient Air Quality Standards (NAAQS). Ozone events in the city typically occur in two peaks, characterized by a pronounced spring peak followed by a late summer peak. Despite higher ozone levels, the spring peak has received less attention than the summer peak. To address this research gap, we used the Weather Research and Forecasting (WRF)-driven GEOS-Chem (WRF-GC) model to simulate San Antonio's ozone changes in the spring month of May from 2017 to 2021 and quantified the respective contributions from changes in anthropogenic emissions and meteorology. In addition to modeling, observations from the San Antonio Field Studies (SAFS), the Texas Commission on Environmental Quality (TCEQ) Continuous Ambient Monitoring Stations (CAMS), and the spaceborne TROPOspheric Monitoring Instrument (TROPOMI) are used to examine and validate changes in ozone and precursors. Results show that the simulated daytime mean surface ozone in May 2021 is 3.8 ± 0.6 ppbv lower than in May 2017, which is slightly less than the observed average differences of −5.3 ppbv at CAMS sites. The model predicted that the anthropogenic emission-induced changes contribute to a 1.4 ± 0.5 ppbv reduction in daytime ozone levels, while the meteorology-induced changes account for a 2.4 ± 0.6 ppbv reduction over 2017–2021. This suggests that meteorology plays a relatively more important role than anthropogenic emissions in explaining the spring ozone differences between the two years. We additionally identified (1) reduced NO2 and HCHO concentrations as chemical reasons, and (2) lower temperature, higher humidity, increased wind speed, and a stronger Bermuda High as meteorological reasons for lower ozone levels in 2021 compared to 2017. The quantification of the different roles of meteorology and ozone precursor concentrations helps understand the cause and variation of ozone changes in San Antonio over recent years.

Contribution of anthropogenic emission changes to the evolution of PM2.5 concentrations and composition in the Pearl River Delta during the period of 2006–2020

Over the last decade, the Pearl River Delta (PRD) region has seen substantial improvements in PM2.5 concentrations, which can be attributed to both local emission reductions and nationwide efforts. To formulate effective strategies for long-term PM2.5 mitigation in the PRD, it is essential to understand the benefits derived from emission reductions in various regions. In this study, we employed a simulation-based decomposition analysis to evaluate the impact of national and local emission changes on PM2.5 and its composition in the PRD region from 2006 to 2020. The downturn in annual average PM2.5 concentrations in the PRD region from 2006 to 2020 primarily stems from local emission reductions, constituting 41–55% of the overall improvement, and nationwide emission reductions (excluding those within the PRD), which add another 10–28% to the improvement. The PM2.5 improvement associated with local emission reduction primarily originates from industrial sources, power plants, and vehicles. Both local and nationwide emission reductions significantly curtail sulfate concentrations, but their impact on nitrate concentrations are relatively moderate, impeded by the ozone rebound due to the inappropriate reduction ratio of NOx/VOCs emissions, particularly in regions with VOCs-limited regime. Since 2013, as a result of China's accelerated efforts to reduce air pollution, national emission reductions have played a larger role in reducing PM2.5 concentrations in the PRD region, especially in the autumn and winter seasons when their contributions to PM2.5 decline can reach 44% and 54%, respectively. Therefore, comprehensive ozone control as well as coordinated regional emission reductions will be crucial for the long-term improvement of PM2.5 in the PRD. Furthermore, stricter measures remain imperative to reduce emissions from local sources such as vehicles, agricultural sources, non-road sources, and dust sources.

Predicted and observed changes in summertime biogenic and total organic aerosol in the southeast United States from 2001 to 2010

Biogenic secondary organic aerosol (bSOA) is a major component of atmospheric particulate matter (PM2.5) in the southeast United States especially during the summer, when emissions of biogenic volatile organic compound (VOCs) are high and emissions from anthropogenic sources enhance the formation of secondary particulate matter. In this work we test the hypothesis whether a chemical transport model (PMCAMx) that includes a detailed description of gas-phase chemistry, secondary organic aerosol (SOA) formation based on the volatility basis set (VBS), and interactions among compounds based on partitioning theory can predict organic aerosol (OA) concentrations that are consistent with the observed changes in OA in response to significant changes in anthropogenic emissions during the summers of 2001 and 2010. The model had good performance for OA for both periods and its predictions were consistent with the observed changes in both the urban and rural areas. The fractional error of OA predictions remained practically the same (0.41 and 0.44 at Chemical Speciation Network (CSN) sites and 0.40 to 0.41 at Interagency Monitoring of Protected Visual Environments (IMPROVE) sites in the summers of 2001 and 2010 respectively) in the two examined periods. The fractional bias of OA predictions increased from 0.10 to 0.22 at CSN sites and decreased from 0 to −0.09 at IMPROVE sites between the two periods. Average predicted bSOA concentrations in the southeast US did not change appreciably from the summer of 2001 to the summer of 2010, while the anthropogenic SOA decreased by 45%. As a result, the biogenic fraction of predicted total OA increased from 0.46 in 2001 to 0.63 in 2010. Partitioning effects due to reduced anthropogenic OA from 2001 resulted in 0.4 μg m−3 less biogenic OA on average in the southeast US in the summer of 2010. This was offset by biogenic SOA increases due to higher biogenic vapor emissions in the warmer 2010 summer. Removing the NOx-dependence of SOA formation yields resulted in higher fractional error and fractional bias at both CSN and IMPROVE sites in both summer periods, demonstrating the efficacy of the current formulation of SOA yields. The results of the analysis support the conclusion that a CTM that simulates NOx-dependent SOA chemistry and semivolatile partitioning of SOA material can consistently predict the observed changes in a region rich in biogenic VOCs and SOA.