Multiple Impacts of Aerosols on O3 Production Are Largely Compensated: A Case Study Shenzhen, China

The Impact of Indoor Environments on the Abundance of Urban Outdoor VOCs

With the upcoming transition to clean electric vehicles, the sources of volatile organic compounds (VOCs) in the ambient environment are rapidly changing and highly uncertain. Here, through systematic characterization of emissions from a typical apartment in a Chinese megacity (Shenzhen), we show that indoor environments contribute significantly to the levels of ambient (i.e., outdoor) VOCs. In particular, we observe that the majority of indoor VOCs originate from unoccupied spaces, demonstrating temperature-dependent release from indoor surface reservoirs. The total indoor-to-outdoor VOC emission rates varied from 53 to 2300 mg day-1 (median 230 mg day-1) during unoccupied periods, influenced by both the air exchange rate and indoor temperature. Reanalysis of literature data from various building studies worldwide corroborates our findings and reveals that indoor-to-outdoor emissions scale with room volume, with an average emission rate of 0.33 ± 0.03 mg h-1 m-3. Our study implies that indoor-to-outdoor emissions significantly contribute to urban VOC levels, rivaling traditional urban sources, e.g., power generation and biomass burning. This is particularly true for oxygenated VOCs, such as methanol, amounting to ∼60% of transportation emissions. The findings change our understanding of the role of indoor VOC contributions to outdoor air quality, whose importance will increase as controls on industrial and transportation emissions intensify.

Evidence for Coordinated Control of PM2.5 and O3: Long-Term Observational Study in a Typical City of Central Plains Urban Agglomeration

Fine particulate matter (PM2.5) and Ozone (O3) pollution have emerged as the primary environmental challenges in China in recent years. Following the implementation of the Air Pollution Prevention and Control Action Plan, a substantial decline in PM2.5 concentrations was observed, while O3 concentrations exhibited an increasing trend across the country. Here, we investigated the long-term trend of O3 from 2015 to 2022 in Xinxiang City, a typical city within the Central Plains urban agglomeration. Our findings indicate that the hourly average O3 increased by 3.41 μg m-3 yr-1, with the trend characterized by two distinct phases (Phase I, 2015-2018; Phase II, 2019-2022). Interestingly, the increasing rate of O3 concentration in Phase I (7.89 μg m-3) was notably higher than that in Phase II (2.89 μg m-3). The Random Forest (RF) model was employed to identify the key factors influencing O3 concentrations during the two phases. The significant dropping of PM2.5 in Phase I could be responsible for the O3 increase. In Phase II, the reductions in nitrogen dioxide (NO2) and unfavorable meteorological conditions were the major drivers of the continued increase in O3. The Observation-Based Model (OBM) was developed to further explore the role of PM2.5 in O3 formation. Our results suggest that PM2.5 can influence O3 concentrations and the chemical sensitivity regime through heterogeneous reactions and changes in photolysis rates. In addition, the relatively high concentration of PM2.5 in Xinxiang City in recent years underscores its significant role in O3 formation. Future efforts should focus on the joint control of PM2.5 and O3 to improve air quality in the Central Plains urban agglomeration.

Causal-inference machine learning reveals the drivers of China's 2022 ozone rebound

Ground-level ozone concentrations rebounded significantly across China in 2022, challenging air quality management and public health. Identifying the drivers of this rebound is crucial for designing effective mitigation strategies. Commonly used methods, such as chemical transport models and machine learning, provide valuable insights but face limitations-chemical transport models are computationally intensive, while machine learning often fails to address confounding factors or establish causality. Here we show that elevated temperatures and increased solar radiation, as primary meteorological drivers, collectively account for 57 % of the total ozone increase, based on an integrated analysis of ground-based monitoring data, satellite observations, and meteorological reanalysis information using explainable machine learning and causal inference techniques. Compared to the year 2021, 90 % of the stations reported an increase in the Formaldehyde to Nitrogen ratio, implying a growing sensitivity of ozone formation to nitrogen oxide levels. These findings highlight the significant causal role of meteorological changes in the ozone rebound, urging the adoption of targeted ozone mitigation strategies under climate warming, particularly through varied regional strategies that consider existing anthropogenic emission levels and the prospective increase in biogenic volatile organic compounds. This identification of causal relationships in air pollution dynamics can support data-driven and accurate decision-making.

Discrepant Global Surface Ozone Responses to Emission- and Heatwave-Induced Regime Shifts

Heatwaves have substantial but poorly quantified impacts on surface ozone photochemical regimes. As heatwaves of increasing severity occur, communities face more serious exposure to ozone, necessitating a more comprehensive understanding of the impact of heatwaves on the nonlinear response of ozone to its precursors for guiding policies in emission reductions. Here we estimate the spatiotemporal evolution of global ozone chemistry based on machine learning and in situ observations and show that emission changes and heatwaves alter ozone photochemical regimes, leading to diverse ozone changes across regions. Sustained emission reductions in East Asia decreased the ozone formation sensitivity to formaldehyde (HCHO) and fine particulate matter (PM2.5), counteracting the adverse high-temperature effect. Quantified results reveal that heatwaves increased the sensitivity of ozone to HCHO and PM2.5, enhancing their positive contributions and causing increased ozone trends across most regions, with a global average anomaly of 9.4 μg/m3. Meanwhile, heatwave-induced PM2.5 anomalies concentrated in wildfire-risk zones, coupled with increased HCHO, elevated downwind ozone levels. Specifically, the effects in wildfire-endangered western Canada and heatwave-exposed southeastern United States contributed to a chemically driven ozone increase of 0.18 μg/m3/month in Northern America. Our results demonstrate that more targeted and substantial regulation of volatile organic compounds will be beneficial in mitigating future intensifying climate penalty effects.

Long-term evolution of carbonaceous aerosols in PM2.5 during over a decade of atmospheric pollution outbreaks and control in polluted central China

Against the backdrop of an uncertain evolution of carbonaceous aerosols in polluted areas over the long term amid air pollution control measures, this 11-year study (2011-2021) investigated fine particulate matter (PM2.5) and carbonaceous components in polluted central China. Organic carbon (OC) and elemental carbon (EC) averaged 16.5 and 3.4 μg/m3, constituting 16 and 3 % of PM2.5 mass. Carbonaceous aerosols dominated PM2.5 (35 and 27 %) during periods of excellent and good air quality, while polluted days witnessed other components as dominants, with a significant decrease in primary organic aerosols and increased secondary pollution. From 2011 to 2021, OC and EC decreased by 53 and 76 %, displaying a high-value oscillation phase (2011-2015) and a low-value fluctuation phase (post-2016). A substantial reduction in high OC and EC concentrations in 2016 marked a milestone in significant air quality improvement attributed to effective control measures, especially targeting OC and EC, evident from their decreased proportion in PM2.5. Primary OC (POC) in winter exhibited the most pronounced reduction (8 % per year), and the seasonal disparities in PM2.5 and carbonaceous components were reduced, showcasing the effectiveness of control measures. Contrary to the more pronounced reduction of EC, which decreased in proportion to PM2.5, secondary OC (SOC) in PM2.5 exhibited an increasing trend. Along with rising OC/EC, SOC/OC, and SOC/EC ratios, this indicates a growing prominence of secondary pollution compared to the decrease in primary pollution. SOC shows an increasing trend with NO2 rise (r = 0.53), without O3 promoting SOC. Positive correlations of SOC with SO2, CO (r = 0.41, 0.59), also highlight their influence on atmospheric conditions, oxidative capacity, and chemical reactions, indirectly impacting SOC formation. The implementation of precise precursor emission reduction measures holds the key to future efforts in mitigating SOC pollution and reducing PM2.5 concentrations, thereby contributing to improved air quality.

Atmospheric Oxidation Capacity Elevated during 2020 Spring Lockdown in Chengdu, China: Lessons for Future Secondary Pollution Control

This study presents the measurement of photochemical precursors during the lockdown period from January 23, 2020, to March 14, 2020, in Chengdu in response to the coronavirus (COVID-19) pandemic. To derive the lockdown impact on air quality, the observations are compared to the equivalent periods in the last 2 years. An observation-based model is used to investigate the atmospheric oxidation capacity change during lockdown. OH, HO2, and RO2 concentrations are simulated, which are elevated by 42, 220, and 277%, respectively, during the lockdown period, mainly due to the reduction in nitrogen oxides (NOx). However, the radical turnover rates, i.e., OH oxidation rate L(OH) and local ozone production rate P(O3), which determine the secondary intermediates formation and O3 formation, only increase by 24 and 48%, respectively. Therefore, the oxidation capacity increases slightly during lockdown, which is partly attributed to unchanged alkene concentrations. During the lockdown, alkene ozonolysis seems to be a significant radical primary source due to the elevated O3 concentrations. This unique data set during the lockdown period highlights the importance of controlling alkene emission to mitigate secondary pollution formation in Chengdu and may also be applicable in other regions of China given an expected NOx reduction due to the rapid transformation to electrified fleets in the future.

Dissecting Drivers of Ozone Pollution during the 2022 Multicity Lockdowns in China Sheds Light on Future Control Direction

In 2022, many Chinese cities experienced lockdowns and heatwaves. We analyzed ground and satellite data using machine learning to elucidate chemical and meteorological drivers of changes in O3 pollution in 27 major Chinese cities during lockdowns. We found that there was an increase in O3 concentrations in 23 out of 27 cities compared with the corresponding period in 2021. Random forest modeling indicates that emission reductions in transportation and other sectors, as well as the changes in meteorology, increased the level of O3 in most cities. In cities with over 80% transportation reductions and temperature fluctuations within -2 to 2 °C, the increases in O3 concentrations were mainly attributable to reductions in nitrogen oxide (NOx) emissions. In cities that experienced heatwaves and droughts, increases in the O3 concentrations were primarily driven by increases in temperature and volatile organic compound (VOC) emissions, and reductions in NOx concentrations from ground transport were offset by increases in emissions from coal-fired power generation. Despite 3-99% reduction in passenger volume, most cities remained VOC-limited during lockdowns. These findings demonstrate that to alleviate urban O3 pollution, it will be necessary to further reduce industrial emissions along with transportation sources and to take into account the climate penalty and the impact of heatwaves on O3 pollution.

Investigation on the budget of peroxyacetyl nitrate (PAN) in the Yangtze River Delta: Unravelling local photochemistry and regional impact

Peroxyacetyl nitrate (PAN) is a significant indicator of atmospheric photochemical pollution, which can influence the regional distribution of ozone (O3) and hydroxyl radical (OH) through long-range transport. However, investigations of PAN incorporating comprehensive measurement and explicit modeling analysis are limited, hindering complete understandings of its temporal behavior, sources, and impacts on photochemistry. Here we conducted a 1-year continuous observation of PAN and relative atmospheric species in Nanjing located in Yangtze River Delta (YRD). The annual mean concentration of PAN was 0.62 ± 0.49 ppbv and showed a bimodal monthly variation, peaking in April-June and November-January, respectively. This pattern is different from the typical pattern of photochemistry, suggesting important contributions of other non-photochemical processes. We further analyzed the PAN budget using an observation-based model, by which, PAN from local photochemical production and regional source could be decoupled. Our results revealed that local photochemical production of PAN is the sole contributor to PAN in summer, whereas about half of the total PAN concentration is attributed to regional source in winter. Although the formation of PAN can suppress the atmospheric oxidation capacity by consuming the peroxyacetyl radical and nitrogen dioxide (NO2), our analyses suggested this effect is minor at our station (-3.2 ± 1.1 % in summer and - 7.2 ± 2.8 % in winter for O3 formation). However, it has the potential to enhance O3 and OH formation by 14.16 % and 5.93 %, if transported to cleaner environments with air pollutants halved. Overall, our study highlights the importance of both local photochemistry and regional process in PAN budget and provides a useful evaluation on the impact of PAN on atmospheric oxidation capacity.

Changing Responses of PM2.5 and Ozone to Source Emissions in the Yangtze River Delta Using the Adjoint Model

China's industrial restructuring and pollution controls have altered the contributions of individual sources to varying air quality over the past decade. We used the GEOS-Chem adjoint model and investigated the changing sensitivities of PM2.5 and ozone (O3) to multiple species and sources from 2010 to 2020 in the central Yangtze River Delta (YRDC), the largest economic region in China. Controlling primary particles and SO2 from industrial and residential sectors dominated PM2.5 decline, and reducing CO from multiple sources and ≥C3 alkenes from vehicles restrained O3. The chemical regime of O3 formation became less VOC-limited, attributable to continuous NOX abatement for specific sources, including power plants, industrial combustion, cement production, and off-road traffic. Regional transport was found to be increasingly influential on PM2.5. To further improve air quality, management of agricultural activities to reduce NH3 is essential for alleviating PM2.5 pollution, while controlling aromatics, alkenes, and alkanes from industry and gasoline vehicles is effective for O3. Reducing the level of NOX from nearby industrial combustion and transportation is helpful for both species. Our findings reveal the complexity of coordinating control of PM2.5 and O3 pollution in a fast-developing region and support science-based policymaking for other regions with similar air pollution problems.

Integration of Data and Predictive Models for the Evaluation of Air Quality and Noise in Urban Environments

This work addresses assessing air quality and noise in urban environments by integrating predictive models and Internet of Things technologies. For this, a model generated heat maps for PM2.5 and noise levels, incorporating traffic data from open sources for precise contextualization. This approach reveals significant correlations between high pollutant/noise concentrations and their proximity to industrial zones and traffic routes. The predictive models, including convolutional neural networks and decision trees, demonstrated high accuracy in predicting pollution and noise levels, with correlation values such as R2 of 0.93 for PM2.5 and 0.90 for noise. These findings highlight the need to address environmental issues in urban planning comprehensively. Furthermore, the study suggests policies based on the quantitative results, such as implementing low-emission zones and promoting green spaces, to improve urban environmental management. This analysis offers a significant contribution to scientific understanding and practical applicability in the planning and management of urban environments, emphasizing the relevance of an integrated and data-driven approach to inform effective policy decisions in urban environmental management.

Elucidating the mechanisms of rapid O3 increase in North China Plain during COVID-19 lockdown period

Ozone (O3) levels in North China Plain (NCP) suffered from rapid increases during the COVID-19 period. Many previous studies have confirmed more rapid NOx reduction compared with VOCs might be responsible for the O3 increase during this period, while the comprehensive impacts of each VOC species and NOx on ambient O3 and their interactions with meteorology were not revealed clearly. To clarify the detailed reasons for the O3 increase, a continuous campaign was performed in a typical industrial city of NCP. Meanwhile, the machine-learning technique and the box model were employed to reveal the mechanisms of O3 increase from the perspective of meteorology and photochemical process, respectively. The result suggested that the ambient O3 level in Tangshan increased from 18.7 ± 4.63 to 45.6 ± 8.52 μg/m3 (143%) during COVID-19 lockdown, and the emission reduction and meteorology contributed to 54 % and 46 % of this increment, respectively. The lower wind speed (WS) coupled with regional transport played a significant role on O3 increase (30.8 kg/s). The O3 sensitivity verified that O3 production was highly volatile organic compounds (VOC)-sensitive (Relative incremental reactivity (RIR): 0.75), while the NOx showed the negative impact on O3 production in Tangshan (RIR: -0.59). It suggested that the control of VOCs rather than NOx might be more effective in reducing O3 level in Tangshan because it was located on the VOC-limited regime. Besides, both of ozone formation potential (OFP) analysis and observation-based model (OBM) demonstrated that the alkenes (36.3 ppb) and anthropogenic oxygenated volatile organic compounds (OVOCs) (15.2 ppb) showed the higher OFP compared with other species, and their reactions released a large number of HO2 and RO2 radicals. Moreover, the concentrations of these species did not experience marked decreases during COVID-19 lockdown, which were major contributors to O3 increase during this period. This study also underlined the necessity of priority controlling alkenes and OVOCs across the NCP.

Strategies for the coordinated control of particulate matter and carbon dioxide under multiple combined pollution conditions

Air pollutants represented by fine particulate matter (PM2.5) and the greenhouse effect caused by carbon dioxide (CO2), are both urgent threats to public health. Tackling the synergistic reduction of PM2.5 and CO2 is critical to achieving improvements in clean air worldwide. A persistent issue is the identification of their common sources and integrated impacts under different environmental conditions. In this study, we investigated the characteristics of the pollution types captured by combined analysis through a comprehensive observational dataset for 2017-2020, and applied machine learning algorithms to quantify the effects of drivers on air pollutants and CO2 formation. More importantly, detailed conclusions were drawn for the joint control of PM2.5-CO2 in multiple pollution types by using ensemble traceability technique. We demonstrated that reducing coal combustion emissions was an effective measure to maximize the benefits of PM2.5-CO2 in weather with low CO2 levels and no PM2.5 pollution. Correspondingly, on days with severe PM2.5 episodes, prioritizing control of vehicle emissions can simultaneously mitigate PM2.5 and CO2. Similar conclusions were found at high CO2 levels, accompanied by a more extensive role of vehicle emissions. Furthermore, a comparison of the differences in source impacts between PM2.5-CO2 and individual species suggests that focusing only on the sources that contribute significantly to one species may result in an underestimation or overestimation of PM2.5-CO2 source impacts. One such implication, as evidenced by our findings, is that synergistic controlling common sources of pollutants should be efficient. Thereby, common source management targeting PM2.5-CO2 under multiple pollution types is a more workable solution to alleviate environmental pollution.

Cost-benefits analysis of ultra-low emissions standard on air quality and health impact in thermal power plants in China

As China's largest energy infrastructure, thermal power plant consumed approximately half of China's coal over the past decade and threatened air quality, human health and socioeconomic development. Thus, a series of control policies have been implemented to alleviate those impacts in China. Particularly, China has witnessed unprecedented declines in air pollutant emissions from thermal power plants since the ultra-low emissions (ULE) standards were implemented. In contrast, the effect of the ULE policy on air quality, health and cost benefits remains poorly understood. Therefore, this study estimates the improved air quality and associated health and economic benefits under the ULE standards in the thermal power sector by using a measure-specific approach, combining a bottom-up emission inventory, an atmospheric model, a health assessment model and a cost analysis model. The results show that all the control measures lead to reduced air pollution, and renovating pre-existing units (RPU) is the most effective. Compared to without implementing the ULE policy, the population-weighted average PM2.5 and O3 concentrations decreased by 1.50 μg/m3 and 0.87 ppm, and 67,831 premature deaths could be avoided nationally. Furthermore, the results also show the net economic benefits of combining health benefits and costs due to control measures are 109.92 billion Yuan (in 2015 value) in China. The comprehensive results reveal that the health benefits outweigh the direct policy. Based on these empirical findings and the specific circumstances of China, we suggest that RPU should be further promoted to the entire of China, and if necessary, establish a long-term compensation mechanism for inter-provincial interests and institute and enforce comprehensive policies that carefully consider the health impacts of policies. This study provides strong arguments for China's policy-making and considering tightening emission standards for thermal power plants worldwide.

Toxicological Effects of Secondary Air Pollutants

Secondary air pollutants, originating from gaseous pollutants and primary particulate matter emitted by natural sources and human activities, undergo complex atmospheric chemical reactions and multiphase processes. Secondary gaseous pollutants represented by ozone and secondary particulate matter, including sulfates, nitrates, ammonium salts, and secondary organic aerosols, are formed in the atmosphere, affecting air quality and human health. This paper summarizes the formation pathways and mechanisms of important atmospheric secondary pollutants. Meanwhile, different secondary pollutants' toxicological effects and corresponding health risks are evaluated. Studies have shown that secondary pollutants are generally more toxic than primary ones. However, due to their diverse source and complex generation mechanism, the study of the toxicological effects of secondary pollutants is still in its early stages. Therefore, this paper first introduces the formation mechanism of secondary gaseous pollutants and focuses mainly on ozone's toxicological effects. In terms of particulate matter, secondary inorganic and organic particulate matters are summarized separately, then the contribution and toxicological effects of secondary components formed from primary carbonaceous aerosols are discussed. Finally, secondary pollutants generated in the indoor environment are briefly introduced. Overall, a comprehensive review of secondary air pollutants may shed light on the future toxicological and health effects research of secondary air pollutants.