Changes In O3 Concentrations Research Articles

Responses of surface ozone under the tropical cyclone circulations: Case studies from Fujian Province, China

The circulation of tropical cyclones (TCs) exerts a multifaceted influence on the spatial and temporal distribution of surface pollutants. This study investigates the response of surface ozone (O3) concentration to the TCs in Fujian Province from June to December 2022 by analyzing the contributions of atmospheric pollutants, meteorological conditions, and dynamical transports. Empirical orthogonal function (EOF) decomposition methods are used to analyze the spatio-temporal distribution patterns of affected O3, and a Gradient Boosting Regression Trees (GBRT) machine learning model is employed to estimate surface O3 concentration, quantifying the influence of each factor. The results indicate an anomaly increase in O3 concentration during this period, with photochemistry-related meteorological conditions being the primary influencer, accounting for 66.9% of O3 variations, elucidating the interpretability of the GBRT model for attributing changes in O3 concentration. Low relative humidity and high temperature conditions have been identified as pivotal factors influencing the rise in O3 concentrations. The presence of TC undermines this predominant influence, amplifying the role of transport factors and other atmospheric pollutants. In the case studies of TC (Muifa and Nanmadol, 2022), the slow or stagnant TCs triggered persistent downdrafts in its periphery and brought favorable meteorological conditions such as clear sky and warm temperature for photochemistry. TCs also enhances the impact of horizontal and vertical dynamic transport on O3 concentrations. This work provides vital insights into the complex interplay between TCs and surface O3 concentrations, highlighting the need for targeted environmental and air quality management strategies in regions frequently impacted by TCs.

Variation Characteristics and Source Analysis of Atmospheric Ozone Pollution in Guanzhong Region

Guanzhong urban agglomeration has a good development foundation and great development potential, and it has a unique strategic position in the national all-round opening up pattern. In recent years, the problem of near-surface ozone （O3） in the Guanzhong Region has become increasingly prominent, which has become a bottleneck affecting the continuous improvement of air quality. In order to effectively prevent and control O3 pollution, this study analyzed the characteristics of annual, monthly, and daily changes in O3 concentration in the Guanzhong Region based on the environmental monitoring data from 2018 to 2021. A geo-detector was used to study the driving factors of the spatial differentiation of O3 concentration, and the sources of O3 were analyzed using a backward trajectory model and emission inventory construction. The results showed that the daily and monthly variation in O3 concentration in the Guanzhong Region were unimodal. The daily maximum value appeared at 15：00, the minimum value appeared at 07：00, the peak value of the monthly average appeared in June, and the valley value appeared in December. The O3 concentration was highest in summer, followed by that in spring, and the lowest in winter. The days of O3 exceeding the standard showed mainly mild pollution, and moderate and above pollution showed a trend of decreasing first and then increasing. The O3 concentration in the Guanzhong Region was mainly closely related to precursors and meteorological factors, and the explanatory power of the interaction of each factor was significantly greater than that of any single factor. The regional transport of O3 concentration in the Guanzhong Region was mainly affected by easterly airflow, followed by the northwest direction, with the potential source areas located mainly in Henan Province and Hubei Province. The main local sources of volatile organic compounds （VOCs） were solvent use sources, process sources, and mobile sources, and the main emission sources of nitrogen oxides （NOx） were mobile sources and industrial production combustion sources. The research results have a guiding significance for O3 joint prevention and control in the Guanzhong Region.

Ozone pollution aggravated by mountain-valley breeze over the western Sichuan Basin, Southwest China

The impact of thermally driven mountain-valley breezes (MVB) on the atmospheric environment remains poorly understood, especially in ozone (O3)-polluted regions with complex underlying topography. To address this knowledge gap, we focused on the western Sichuan Basin (SCB), situated immediately east of the Tibetan Plateau (TP), which is considered susceptible to MVB coupled with severe O3 pollution in southwest China. We revealed the MVB driving diurnal O3 variations and meteorological mechanisms using surface observations and ERA5 reanalysis data. Local MVB days accounted for up to 47% of cases in the summers of 2015–2022. Driven by the MVB, the near-surface O3 concentrations increased by 8.8%, with 12.7% and 50.0% deterioration in the O3 light and moderate exceedance rates, respectively, on the western SCB edge. The daytime upslope valley breeze with 20% higher wind speed drove the westward transport of rich O3 and precursors from the upwind-polluted inner SCB towards its western edge, and the O3 photochemical production, followed by intensifying solar radiation and air temperature, gave rise to 14.8% of surface O3 concentrations over the western SCB edge. The nighttime downward mountain breeze with a 20% increase in wind speed could transport the rich O3 in the mountainous area to the basin edge, causing O3 levels to increase by 2.8%. In summary, we quantitatively assessed the impacts of MVB on changes in O3 concentrations and air quality along with its meteorological mechanisms, facilitating a comprehensive understanding of meteorological drivers in the atmospheric environment.

Simple model of vertical dispersion of O3 in Bangkok, Thailand using regression method

Bangkok, the capital city of Thailand, has experienced a degradation in air quality. In particular, ozone (O3) concentrations frequently exceed Thailand’s National Ambient Air Quality standards. Various policies have been developed to manage air quality at near-surface levels; however, the assessment of air quality above these levels has been neglected. Analysis of O3 concentrations and its precursors measured at various altitudes revealed that the vertical structures of the pollutants in Bangkok were stratified. While NOx concentrations decreased with height, O3 concentrations increased. These results emphasize the importance of air quality management above ground level, particularly in megacities with high-rise buildings, such as Bangkok. Assuming that the O3 formation regime over Bangkok is VOC-limited, a simple model was developed based on a linear regression method to estimate the changes in O3 concentrations with height. We found that the simple model was able to capture the variation in O3 concentrations at 30, 75, and 110 m above ground level, with an R2 of 0.48–0.65. Although the simple model had some difficulty estimating the magnitude of O3 concentrations, the estimated O3 values from the model were reasonable for capturing vertical O3 trends. Using this approach, policymakers can visualize the vertical distribution of pollutants, which will be useful in designing air quality management plans.

Wheat yield response to elevated O3 concentrations differs between the world's major producing regions

Ground-level ozone (O3) concentration is rising in Asia, which accommodates the world's top-two wheat producers (China and India). Because wheat is among the species of high O3 sensitivity, yield loss due to rising O3 in Asia is a major threat to global wheat supply. We estimated the relationships between O3 dose on AOT40 (accumulated daytime O3 concentrations above 40 ppb for 90 days) and relative wheat yield for four wheat producing regions: China, India, Europe and North America using results of O3 elevation experiments conducted therein. When compared on the same AOT40, the estimated yield loss was greatest in China followed by India, Europe, and North America in this order. In China, Europe and North America, the yield loss was primarily due to the reduction of single grain weight, whereas in India reduction of the number of grains contributed more to the yield loss than single grain weight. The greater response of the number of grains to O3 in India can be explained by the earlier start of O3 elevation, but the seasonal change in O3 concentrations cannot explain the lower yield loss in North America than China and India. Referring to the past reports of lower yield sensitivity to O3 in older cultivars, we compared the year of release of cultivars between the regions. In North America, they used cultivars released in 1980s or earlier, whereas in China they used cultivars released in 2000s. In Europe and India, most cultivars were released between those in North America and China. The difference in cultivars could therefore be a cause the differential yield response among the regions. We argue that the O3-induced yield loss should be quantified using the dose-response relationships for each region accounting for the effects of seasonal change in O3 concentrations, cultivars and climate on the yield response.

대도시 지역의 배출량 저감에 따른 O3 농도 변화 분석: 부산광역시 2019년 여름 사례

대도시 지역의 배출량 저감에 따른 O3 농도 변화 분석: 부산광역시 2019년 여름 사례

Responses of ozone concentrations to the synergistic control of NOx and VOCs emissions in the Chengdu metropolitan area

Simulations of 108 emission reduction scenarios for NOx and VOCs using Comprehensive Air Quality Model with Extensions (CAMx) were conducted for eight cities in the Chengdu metropolitan area (CMA). The isopleth diagrams were drawn to explore the responses and differences of ozone (O3) concentrations to NOx and VOCs emission changes under Chengdu, CMA and Sichuan Province emission reduction scenarios. The results show that the O3-sensitive regimes of eight cities may change under different emission reduction scenarios. Under Chengdu emission reduction scenario, the Chengdu city is in the transition regime and O3 formation will shift from transition to VOC-limited when the VOCs emissions decreased by 50%, and the decreases in O3 concentrations caused by VOCs emission reductions are small. For the CMA and Sichuan Province emission reduction scenarios, all cities are NOx-limited in the baseline cases and with at least a 66% and a 77% reduction in NOx emissions, respectively, the daily maximum 8-h average O3 (MDA8) can attain the O3 standard (160 μg m−3). Although reductions in VOCs emissions can also lessen the O3 concentration, the effectiveness is relatively small. The changes in O3 concentrations under different VOCs to NOx emission reduction ratios indicate that all cities achieve a relatively high O3 concentration decrement with low VOCs to NOx emission reduction ratios and that the decreasing O3 concentrations caused by non-local emission reductions are much higher than those achieved by local emission reductions. In addition, the decreases in O3 concentrations in Chengdu are quite close when the total NOx and VOCs emissions reduction percentages are less than 30% under the CMA and Sichuan emission reduction scenarios.

A Numerical Analysis of the Changes in O3 Concentration in a Wildfire Plume

This study analyzed the characteristics of changes in O3 concentration in a plume induced by a wildfire in Andong, South Korea, from 24 to 26 April 2020, using the Community Multi-scale Air Quality (CMAQ) model. Fire INventory from National Center for Atmospheric Research (FINN) emissions data were used for the wildfire emissions. The increases in the concentrations of primary pollutants (CO, NOx, and volatile organic compounds (VOCs)) due to the wildfire peaked near the source at 09 LST and, as the plume was transported, the reduction in the supply of pollutants from wildfire, as well as chemical reactions, advection and diffusion, and deposition, caused the concentrations to continuously decrease. In contrast, O3 concentration showed a sustained increase during transport due to photochemical reactions caused by precursors (e.g., NOx, VOCs) emitted during the wildfire, peaking (1.40 ppb) at approximately 1 km at 13 LST over 60 km from the source. To analyze these results, a process analysis was conducted. Integrated process rate (IPR) analysis results showed that the production rate of O3 and loss rates of NOx and VOCs peaked at 09 LST due to the photochemical reactions of NOx and VOCs emitted due to wildfire. Then, as the plume was transported, the loss rates of NOx and VOCs that contributed to O3 production continued to decrease at 11 LST. The O3 production rate also decreased at 11 LST but increased at 13 LST due to increasing solar radiation. This indicates that the O3 concentration is complexly determined by O3 precursors and solar radiation. Additionally, IRR analysis revealed that NO and NO2 emitted during wildfire and solar radiation contributed to the production and loss processes of O3; the production reactions of O3 were predominant, and O3 was accumulated and transported in the plume, leading to the peak O3 concentration at 13 LST.

Quantifying changes in ambient NOx, O3 and PM10 concentrations in Austria during the COVID-19 related lockdown in spring 2020

During spring 2020, unprecedented changes in local and regional emissions have occurred around the globe due to governmental restrictions associated with COVID-19. Many European countries including Austria issued partial curfews or stay-at-home order policies, which have impacted ambient air quality through reductions in non-essential transportation and energy consumption of industrial sites and work places. Here, we analyse the effect of these measures on ambient concentrations of nitrogen oxides (NOx), ozone (O3) and particulate matter (PM10) during the first nationwide lockdown in Austria (16.03.2020 to 14.04.2020). To ensure a robust analysis, the Austrian domain is divided into four individual subsectors contingent on regional climate. For air quality analysis a novel method is applied for filtering days with comparable weather conditions during the 2020 lockdown and spring 2017 to 2019. In general, our analysis shows decreasing pollutant concentrations, although in magnitude dependent on pollutant and regional subdomain. Largest reductions are found for NOx reaching up to −68% at traffic sites reflecting the substantial decrease in non-essential transport. Changes in the O3 concentrations at background sites show a rather weak response to NOx declines varying between roughly −18 to +8% for both the median and the upper tail of the distribution. Occasional site level increases in O3 concentrations can be attributed to comparably weak titration during night-time. PM10 concentrations show the smallest response among air pollutants, attributable to manifold precursor sources not affected by the lockdown measures. However, our analysis indicates also a shift of PM10 distributions at traffic sites closer to distributions observed at background sites.

CARACTERÍSTICAS DE LA EVOLUCIÓN Y FACTORES DE INFLUENCIA DE LA CONTAMINACIÓN POR OZONO DURANTE EVENTOS A GRAN ESCALA

The impact of temporary control measures on regional air quality during large-scale events is the focus of current research. Most of them focus on the discussion of environmental particulate matter concentration, while the changes in O3 concentration during such periods have not been explored. To reveal the variation characteristics of environmental O3 concentration during large-scale events, the ozone pollution control during the 2019 National Games in Zhengzhou, China was considered as an example and the six pollution parameters of state-controlled stations, meteorological parameters, and online volatile organic compound (VOC) component data was used. The evolution law of O3 pollution in Zhengzhou before and after the implementation of control measures was discussed, and the changes in NOx and the components of VOCs in different control stages were compared. The positive matrix factorization model was used to analyze the contribution of different types of pollution sources to the O3 mass concentration in Zhengzhou during the observation period. Results show that during the National Games, the concentration of O3 decreased by 45.2% and 29.3% compared with that before control and during Stage-I of control, respectively. The concentration of alkanes, olefins, and alkynes decreased significantly during the National Games, whereas the concentration of aromatic hydrocarbons increased by 6.5%. The pollution sources with the highest contribution of VOCs in Zhengzhou were as follows: motor vehicle tail gas source (the average contribution was 32.8%), natural gas/oil source (26.3%), solvent use source (20.4%), industrial process source (13.9%), and natural plant source (6.7%). The research conclusion revealed the evolution characteristics of O3 concentration and the causes of pollution during large-scale activities. Key Words: O3 pollution, VOCs, Control measures, the National Games, PMF source apportionment

Sources and Formation of Atmospheric Nitrate Over China–Indochina Peninsula in Spring: A Perspective From Oxygen and Nitrogen Isotopic Compositions Based on Passive Air Samplers

The formation processes and potential sources of particulate nitrate can be revealed by nitrogen (δ15N-NO3−) and oxygen (δ18O-NO3−) isotopes; however, the linkage and comparative information over a large scale is limited. In this work, the feasibility of using quartz wool disk passive air samplers (Pas-QW) to identify and quantify the nitrate concentrations and their isotopic compositions was demonstrated. The results of a simultaneous sampling campaign from March to June showed that the NO3− concentration was largely attributed to the development of the regional economies. The regional distribution of δ15N-NO3− values was due to the source changes. The decreasing trend of δ18O-NO3− values with latitude from south to north was mainly a combination of oxygen isotopic fractionation of the oxidant induced by natural factors and anthropogenic changes in O3 concentrations. Coal combustion (CC) and mobile sources (MS) have a significant contribution to NOx in the typical urban agglomerations, while the high contribution from biomass burning (BB) and biogenic soil emission (BS) was mainly in areas with high natural productivity and intensive agricultural activities. By allowing simultaneous monitoring at multiple sites and over extended periods, passive sampling complements existing techniques for studying nitrate aerosol, and the results can provide a reference for the spatial distribution of its sources and formation in the China–Indochina Peninsula (CICP).

Impact of Meteorological Conditions and Human Activities on Air Quality During the COVID-19 Lockdown in Northeast China

During the lockdown implemented to curb the spread of COVID-19, human activities have drastically reduced, providing a valuable opportunity to study and compare the impact of meteorological conditions and human activities on air quality. In this study, large-scale weather circulation, local meteorological conditions, and the impact of human activities are comprehensively considered, and changes in the concentration of major air pollutants in the northeast during this period are systematically studied. The large-scale weather circulation patterns that mainly affect the northeast region are divided into nine types by using the T-mode Principal components analysis objective circulation classification method. It is found that the northeast region is located at the edge of weak high pressure (Types 1, 2, and 7) and at the rear of high pressure (Type 4) and has higher concentrations of PM2.5, NO2, SO2, and CO; in cyclonic weather systems, low vortices (Types 3 and 5) and under the influence of the updraft (Type 6) in front of the trough, the ozone concentration is higher. The changes in the concentrations of PM2.5, NO2, CO, SO2, and O3 in the three cities, namely Shenyang, Changchun, and Harbin, during the lockdown period are compared, and it is found that the concentrations of PM2.5, NO2, CO, and SO2 have a tendency to first decrease and then increase, while the changes of O3 concentration are cyclical and increased significantly during this period. This demonstrates that pollutants such as PM2.5, NO2, CO, and SO2 are more susceptible to human activities and local meteorological conditions, and changes in O3 concentration are more closely related to changes in weather circulation types. Finally, the FLEXPART-WRF model is used to simulate the pollution process of nine circulation types, which confirms that particulate pollution in the northeast is mainly affected by local emissions and local westward sinking airflow.

Sensitivity modeling of ozone and its precursors over the Chengdu metropolitan area

The comprehensive air quality model with extensions (CAMx)–high-order decoupled direct method (HDDM) was used to simulate ozone (O3)-NOx-VOCs sensitivity from June 1 to September 30 in 2019 over the Chengdu metropolitan area. In terms of the diurnal variations of O3 sensitivities to NOx and VOCs emissions, most cities in the Chengdu metropolitan area, except Ya'an, Suining and Ziyang, show a shift in O3 sensitivity from NOx-limited to VOC-limited from daytime to nighttime, when 8:00 and 19:00 were the cut-off points for the switch in O3-sensitive regimes. The average daily maximum 8-h O3 sensitivity to regional NOx and VOCs emissions show that the Chengdu metropolitan area is mainly NOx-limited. The O3 sensitivity to local emissions in urban areas of each city is VOC-limited or in a transition regime, while O3 sensitivities to overall regional emissions are prone to NOx-limited. Therefore, when proposing O3 control strategies, it is necessary to consider the different measures for the local and regional emissions. First-order sensitivity coefficients combined with the path integral method (PIM) are used to calculate the contributions of precursors' emissions to O3 concentrations in different sectors, revealing that mobile source accounted for 31.1–36.9%, followed by industrial source, with contribution of 22.2–30.5% to O3 concentrations. Finally, five emission reduction scenarios were designed with different NOx/VOC reduction ratios, and O3 concentration changes with different NOx/VOC reduction ratios were calculated based on O3 sensitivity coefficients. The results show that the influence of local emission reductions on the changes in O3 concentrations varies significantly among cities. The decrease in O3 concentrations reach maximum when the NOx/VOC reduction ratio is 3:1 in most of the cities, except Chengdu and Mianyang, with the highest O3 decrement occurs at the NOx/VOC reduction ratio of 1:3.

Modeling the impacts of land use/land cover change on meteorology and air quality during 2000–2018 in the Yangtze River Delta region, China

The land use/land cover (LULC) change in the fast-developing city clusters of China exhibits impacts on both the meteorology and air quality. However, this effect, especially in the Yangtze River Delta (YRD), has not been well quantified. In this study, the LULC data are extracted from Landsat satellite imageries for year 2000 and 2018 for the YRD region. The Weather Research and Forecasting with Chemistry (WRF/Chem) model is applied to investigate the impact of historical LULC change on regional meteorology and air pollution over the YRD region during the past two decades. Two simulation scenarios are performed with two sets of LULC data to represent the pre-urbanization (LULC of year 2000) and the most recent urban pattern (LULC of year 2018). Results indicate that rapid urbanization leads to an increase of monthly mean 2-m temperature by 0.4–2.1 °C but decrease of the 10-m wind speed by 0.5–1.3 m/s in urban areas; the maximum increase of daytime planetary boundary layer height (PBLH) in July and November is 289 and 132 m, respectively. Affected by favorable changes in the meteorological conditions due to LULC change, the PM2.5 concentrations in most urban areas show a decreasing trend, especially during the nighttime in summer. On the contrary, surface ozone (O3) concentration in urban areas has increased by 7.2–9.8 ppb in summer and 1.9–2.1 ppb in winter. Changes in O3 concentration are inversely proportional to changes in NOx and the spatial distribution of PM2.5. Areas with higher O3 concentration are consistent with areas of higher temperature and lower wind speed. Our findings reveal that LULC changes during the past years bring observable changes in air pollutant concentrations, which should not be neglected in the YRD region regarding air quality trends as well as policy evaluations under the warming threat.

Temporal and Spatial Variation in O3 Concentration Near the Surface of Shandong Peninsula and Analysis of Potential Source Areas

The purpose of this study was to explore the temporal and spatial distribution characteristics and potential sources of ozone (O3) in the Shandong Peninsula over a long period of time based on the analysis of the temporal and spatial changes in O3 concentration in Shandong Peninsula from 2005 to 2020. We used wavelet analysis, the entropy weight method, and correlation analysis to discuss O3 and its influencing factors and researched the potential sources of O3 in Shandong Peninsula. The results showed that:① in terms of the time pattern, the near-surface O3 in Shandong Peninsula showed a "triple peak" trend from 2005 to 2020, reaching the maximum value of[(40.48±7.64) μg·m-3] in 2010 and a minimum value of[(36.63±5.61) μg·m-3] in 2013. The season was expressed as:summer[(42.49±1.7) μg·m-3]>spring[(40.65±0.6) μg·m-3]>autumn[(36.47±0.7) μg·m-3]>winter[(36.46±0.3) μg·m-3]. ② In terms of the spatial pattern, the O3 concentration of Shandong Peninsula gradually increased with the increase in latitude from 2005 to 2020, showing the characteristics of high concentrations in the east and west and low in the middle region. During the 16-year evolution of the O3 concentration, there was a 1.5 a main oscillation period. ③The analysis of meteorological conditions revealed that O3 concentration was positively correlated with temperature, precipitation, relative humidity, and sunshine hours, whereas pressure and wind speed were negatively correlated. In the analysis of social factors, soot (dust) emissions were the most obvious factor affecting the third indicator, with a weight of 0.25. ④ Through simulating the trajectory of airflow from different regions (Ji'nan and Qingdao), it was found that the ocean airflow contributed 10.69% to Jinan and 48.94% to Qingdao. There was 64.04% of the long-distance air mass transmission path coming from the northwest, and 43.69% of the short-distance air mass transmission path was from the Bohai Sea and the Yellow Sea, followed by Shandong Province with 21.01%. ⑤ The analysis of potential sources of O3 showed that the potential sources of Ji'nan were mainly distributed in Jinzhou, Liaoning Province, northern Jiangsu Province, Hubei Province, and Anhui Province, with a WPSCF value >0.6, and Qingdao's WPSCF value of >0.6 was mainly distributed in the Yellow Sea area. The O3 contribution of Jining City, Linyi City, Xuzhou City, Huaibei City, and Lianyungang City was >40 μg·m-3. The area with >45 μg·m-3 in Qingdao was mainly in the Yellow Sea. Through the analysis of potential sources in the Shandong Peninsula, particular attention should be paid to the supply of industrial sources in the surrounding areas and the marine sources provided by marine air pollution.

Response of Air Quality to COVID-19 Lockdown in Xiamen Bay

Air pollutant concentrations in the Xiamen Bay cities during the period before and after COVID-19 lockdown(from January 11 to February 21, 2020) were studied to determine the influence of human activities on air quality in this region. During the Chinese Spring Festival holiday and the lockdown period, the concentrations of SO2, NO2, CO, PM10, and PM2.5 decreased by 6%-22%, 53%-70%, 34%-48%, 47%-64%, and 53%-60%, respectively. However, the changes in O3 concentrations were not consistent with the variations of human activities. The reduction rates for PM2.5, PM10, CO, and NO2 during the Spring Festival were greater than in previous years(2018 and 2019), but the reduction rates for SO2 were comparable. The concentrations of NO2 increased sharply(38%-138%), and much higher those of SO2(2%-42%), after the resumption of socioeconomic activities, indicating the importance of traffic reductions due to the lockdown measures on NO2. Higher wind speeds and rainfall after the Spring Festival were also favorable for the decline of SO2, NO2, and PM. The spatio-temporal distributions of the six criterial pollutants in the Xiamen Bay city cluster were obtained based on the Inverse Distance Weight method. The variability in regions with high NO2 concentrations was strongly linked to traffic emissions, while spatial patterns for CO and SO2 changed little over the six-week study period. The concentrations of PM2.5 and PM10 increased notably in the region, linked to more construction activity, but changed comparatively little in regions with dense populations and traffic networks. O3 remained relatively stable but low-value regions corresponded to those regions with high NO2 concentrations, indicating the significant titration effect of NO2 on O3. These results provide valuable information that can inform O3 pollution reduction measures.

Rapid Evaluation of the Effects of Policies Corresponding to Air Quality, Carbon Emissions and Energy Consumption: An Example from Shenzhen, China

Efficient environmental policies are necessary in the improvement of air quality and reduction in carbon emissions, and the interactions between policy, activity, emissions, and environment comprise a cycle allowing the evaluation of the effects of implemented policies. Based on the establishment of the connection between environmental parameters and policy context using a quantifiable methodology, in this study, we formulated a rapid and simplified pattern for the evaluation of the effects of policies concerning the atmospheric environment, and applied it to the evaluation and improvement of policies for Carbon dioxide (CO2) reduction and air quality enhancement in the sample city of Shenzhen. The Response Surface Model-Visualization and Analysis Tool (RSM-VAT) in the Air Benefit and Cost and Attainment Assessment System (ABaCAS) was applied as the core tool. The required reductions in Fine particulate matter (PM2.5) and Sulfur dioxide (SO2) emissions for 2014–2019 are expected to be achieved; however, the expected reductions in Nitrogen oxides (NOx) emissions (mainly from road mobile sources) and Volatile organic compounds (VOCs) emissions (mainly from secondary industry and road mobile sources) are less certain. According to the simulated concentration of PM2.5 in 2019, it is necessary to reduce the concentrations of air pollutants, both within and outside Shenzhen. The background weather conditions may be the main reason for the increased concentrations of Ozone (O3) in October compared to those in July. Reductions in NOx and VOCs tend to be the main factors driving changes in O3 concentrations. Policies have been formulated and implemented in a wide array of areas. According to the quantitative comparative analysis of the policies, and the relevant activities, the greatest challenge in reducing NOx and VOCs emissions is presented by the oil-powered vehicles in the road mobile sector and organic solvent production in the secondary industry sector. Therefore, in an effort to achieve better air quality and ensure that CO2 emissions reach a peak in Shenzhen by 2025, we propose key improvements in policies based on interdisciplinary cooperation, involving not only atmospheric and environmental science, but also governance and urban planning.

Regional Temperature-Ozone Relationships Across the U.S. Under Multiple Climate and Emissions Scenarios

The potential effects of 21st century climate change on ozone (O3) concentrations in the United States are investigated using global climate simulations to drive higher-resolution regional meteorological and chemical transport models. Community Earth System Model (CESM) and Coupled Model version 3 (CM3) simulations of the Representative Concentration Pathway 8.5 scenario are dynamically downscaled using the Weather Research and Forecasting model, and the resulting meteorological fields are used to drive the Community Multiscale Air Quality model. Air quality is modeled for five 11-year periods using both a 2011 air pollutant emission inventory and a future projection accounting for full implementation of promulgated regulatory controls. Across the U.S., CESM projects daily maximum temperatures during summer to increase 1–4 °C by 2050 and 2–7 °C by 2095, while CM3 projects warming of 2–7 °C by 2050 and 4–11 °C by 2095. The meteorological changes have geographically varying impacts on O3 concentrations. Using the 2011 emissions dataset, O3 increases 1–5 ppb in the central Great Plains and Midwest by 2050 and more than 10 ppb by 2095, but it remains unchanged or even decreases in the Gulf Coast, Maine, and parts of the Southwest. Using the projected emissions, modeled increases are attenuated while decreases are amplified, indicating that planned air pollution control measures ameliorate the ozone climate penalty. The relationships between changes in maximum temperature and changes in O3 concentrations are examined spatially and quantified to explore the potential for developing an efficient approach for estimating air quality impacts of other future climate scenarios. Implications Statement: The effects of climate change on ozone air quality in the United States are investigated using two global climate model simulations of a high warming scenario for five decadal periods in the 21st century. Warming summer temperatures simulated under both models lead to higher ozone concentrations in some regions, with the magnitude of the change increasing with temperature over the century. The magnitude and spatial extent of the increases are attenuated under a future emissions projection that accounts for regulatory controls. Regional linear regression relationships are developed as a first step toward development of a reduced form model for efficient estimation of the health impacts attributable to changes in air quality resulting from a climate change scenario.

Improved estimation of trends in U.S. ozone concentrations adjusted for interannual variability in meteorological conditions

Daily maximum 8-h average (MDA8) ozone (O3) concentrations are well-known to be influenced by local meteorological conditions, which vary across both daily and seasonal temporal scales. Previous studies have adjusted long-term trends in O3 concentrations for meteorological effects using various statistical and mathematical methods in order to get a better estimate of the long-term changes in O3 concentrations due to changes in precursor emissions such as nitrogen oxides (NOX) and volatile organic compounds (VOCs). In this work, the authors present improvements to the current method used by the United States Environmental Protection Agency (US EPA) to adjust O3 trends for meteorological influences by making refinements to the input data sources and by allowing the underlying statistical model to vary locally using a variable selection procedure. The current method is also expanded by using a quantile regression model to adjust trends in the 90th and 98th percentiles of the distribution of MDA8 O3 concentrations, allowing for a better understanding of the effects of local meteorology on peak O3 levels in addition to seasonal average concentrations. The revised method is used to adjust trends in the May to September mean, 90th percentile, and 98th percentile MDA8 O3 concentrations at over 700 monitoring sites in the U.S. for years 2000–2016. The utilization of variable selection and quantile regression allow for a more in-depth understanding of how weather conditions affect O3 levels in the U.S. This represents a fundamental advancement in our ability to understand how interannual variability in weather conditions in the U.S. may impact attainment of the O3 National Ambient Air Quality Standards (NAAQS).

A Machine Learning Approach to Investigate the Surface Ozone Behavior

The concentration of surface ozone (O3) strongly depends on environmental and meteorological variables through a series of complex and non-linear functions. This study aims to explore the performances of an advanced machine learning (ML) method, the boosted regression trees (BRT) technique, in exploring the relationships between surface O3 and its driving factors, and in predicting the levels of O3 concentrations. To this end, a BRT model was trained on hourly data of air pollutants and meteorological parameters, acquired, over the 2016–2018 period, in a rural area affected by an anthropic source of air pollutants. The abilities of the BRT model in ranking, visualizing, and predicting the relationship between ground-level O3 concentrations and its driving factors were analyzed and illustrated. A comparison with a multiple linear regression (MLR) model was performed based on several statistical indicators. The results obtained indicated that the BRT model was able to account for 81% of changes in O3 concentrations; it slightly outperforms the MLR model in terms of the predictions accuracy and allows a better identification of the main factors influencing O3 variability on a local scale. This knowledge is expected to be useful in defining effective measures to prevent and/or mitigate the health damages associated with O3 exposure.