Air Pollution Control Measures Research Articles

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.

Long term variation of microphysical properties of black carbon in Beijing derived from observation and machine learning

Long term variation of microphysical properties of black carbon in Beijing derived from observation and machine learning

Accountability analysis of health benefits related to National Action Plan on Air Pollution Prevention and Control in China.

China is one of the largest producers and consumers of coal in the world. The National Action Plan on Air Pollution Prevention and Control in China (2013-2017) particularly aimed to reduce emissions from coal combustion. Here, we show whether the acute health effects of PM2.5 changed from 2013 to 2018 and factors that might account for any observed changes in the Beijing-Tianjin-Hebei (BTH) and the surrounding areas where there were major reductions in PM2.5 concentrations. We used a two-stage analysis strategy, with a quasi-Poisson regression model and a random effects meta-analysis, to assess the effects of PM2.5 on mortality in the 47 counties of BTH. We found that the mean daily PM2.5 levels and the SO42- component ratio dramatically decreased in the study period, which was likely related to the control of coal emissions. Subsequently, the acute effects of PM2.5 were significantly decreased for total and circulatory mortality. A 10 μg/m3 increase in PM2.5 concentrations was associated with a 0.16% (95% CI: 0.08, 0.24%) and 0.02% (95% CI: -0.09, 0.13%) increase in mortality from 2013 to 2015 and from 2016 to 2018, respectively. The changes in air pollution sources or PM2.5 components appeared to have played a core role in reducing the health effects. The air pollution control measures implemented recently targeting coal emissions taken in China may have resulted in significant health benefits.

Modeling assessment of air pollution control measures and COVID-19 pandemic on air quality improvements over Greater Bay Area of China

A remarkable progress has been made toward the air quality improvements over the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China from 2017 to 2020. In this study, for the first time, the emission reductions of regional control measures together with the COVID-19 pandemic were considered simultaneously into the development of the GBA's emission inventories for the years of 2017 and 2020. Based on these collective emission inventories, the impacts of control measures, meteorological variations together with temporary COVID-19 lockdowns on the five major air quality index pollutants (SO2, NO2, PM2.5, PM10, and O3, excluding CO) were evaluated using the WRF-CMAQ and SMAT-CE model attainment assessment tool over the GBA region. Our results revealed that control measures in the Pearl River Delta (PRD) region affected significantly the GBA, resulting in pollutant reductions ranging from 48 % to 64 %. In contrast, control measures in Hong Kong and Macao contributed to pollutant reductions up to 10 %. In PRD emission sectors, stationary combustion, on-road, industrial processes and dust sectors stand out as the primary contributors to overall air quality improvements. Moreover, the COVID-19 pandemic during period I (Jan 23-Feb 23) led to a reduction of NO2 concentration by 7.4 %, resulting in a negative contribution (disbenefit) for O3 with an increase by 2.4 %. Our findings highlight the significance of PRD control measures for the air quality improvements over the GBA, emphasizing the necessity of implementing more refined and feasible manageable joint prevention and control policies.

Spatial-temporal distribution and emission of urban scale air pollutants in Hefei based on Mobile-DOAS

As a significant city in the Yangtze River Delta regions, Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion. However, there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants. To address this, this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022. The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data. Temporally, there were pronounced seasonal variations in air pollutants. Spatially, high concentration of HCHO and NO2 were closely associated with traffic congestion on roadways, while heightened SO2 levels were attributed to winter heating and industrial emissions. The study also revealed that with the implementation of road policies, the average vehicle speed increased by 95.4%, while the NO concentration decreased by 54.4%. In the estimation of urban NOx emission flux, it was observed that in temporal terms, compared with inventory data, the emissions calculated via mobile measurements exhibited more distinct seasonal patterns, with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer. In spatial terms, the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city's primary NOx emission sources in the area between these two rings. This study offers data support for formulating the next phase of air pollution control measures in urban areas.

Ozone and its precursors at an urban site in the Yangtze River Delta since clean air action plan phase II in China

In response to regional ozone (O3) pollution, Chinese government has implemented air pollution control measures in recent years. Here, a case study was performed at an O3-polluted city, Wuhu, in Yangtze River Delta region of China to investigate O3 variation trend and the relationship to its precursors after implementation of Clean Air Action Plan Phase II, which aims to reduce O3 pollution. The results showed that peak O3 concentration was effectively reduced since Clean Air Action Plan Phase II. Due to significant NOx reduction, O3 formation tended to shift from volatile organic compound (VOC)-limited regimes to NOx-limited regimes during 2018–2022. VOC/NOx ratios measured in 2022 revealed that peak O3 concentration tended to respond positively to NOx. Apart from high-O3 period, Wuhu was still in a VOC-limited regime. The relationship of maximum daily 8-h ozone average and NO2 followed a lognormal distribution with an inflection point at 20 μg m−3 of NO2, suggesting that Wuhu should conduct joint control of VOC and NOx with a focus on VOC reduction before the inflection point. Alkenes and aromatics were suggested to be preferentially controlled due to their higher ozone formation potentials. Using random forest meteorological normalization method, meteorology had a positive effect on O3 concentration in 2018, 2019 and 2022, but a negative effect in 2020 and 2021. The meteorology could explain 44.0 ± 19.1% of the O3 variation during 2018–2022. High temperature favors O3 production and O3 pollution occurred more easily when temperature was over 25 °C, while high relative humidity inhibits O3 generation and no O3 pollution was found at relative humidity above 70%. This study unveils some new insights into the trend of urban O3 pollution in Yangtze River Delta region since Clean Air Action Plan Phase II and the findings provide important references for formulating control strategies against O3 pollution.

CO2 synergistic emission reduction and health benefits of PM2.5 reaching WHO-III level in Pearl River Delta

Protecting human health is one of the fundamental goals of continuous air quality improvement. Considering the same sources of CO2 and air pollutants emissions, their emission control measures often have a certain degree of synergistic emission reduction effects To balance the costs and policy efficiency, policy makers should assess the synergistic benefits of CO2 emission reduction when formulating air quality improvement strategies. Aimed at the air quality improvement strategy targeting WHO-III level (i.e. 15 μg/m3) for PM2.5 in the Pearl River Delta (PRD) region, this study evaluates the synergistic CO2 reduction effects and the associated health benefits from this strategy which includes a range of air pollution prevention and control measures. The results of the study show that promoting the attainment of WHO-III for PM2.5 in the PRD region can bring about 74 Mt of synergistic CO2 emission reduction, resulting in an 18% reduction of CO2 emissions in the PRD compared to 2017. Among various measures considered, industrial restructuring, power supply transition and industrial energy consumption transformation exhibit the most pronounced synergistic effects. Therefore, these measures are recommended to be prioritized and promoted in the next stage of air pollution prevention and CO2 emission reduction. Furthermore, when the PM2.5 concentration in the PRD region reaches the WHO-III level, the number of PM2.5-related deaths will be estimated to reduce approximately 5.5 thousand compared to that in the current policy scenario. Through continuous structural transformation and emission reduction efforts, it not only facilitates the decline in regional PM2.5 concentration but also helps more regional residents to live in an environment with a relatively low PM2.5 concentration. In addition, in order to reduce the health impacts of PM2.5, it is recommended that the government should guide people to change their production and living styles in order to reduce pollutant emissions from anthropogenic activities.

Assessment of CO2 Co-benefits of Air Pollution Control Policies in Taiyuan's 14th Five-Year Plan

To quantitatively evaluate the co-benefits of air pollution reduction and carbon dioxide reduction of Taiyuan's 14th Five-Year Plan air pollution prevention and control policies, this study used the Beijing-Tianjin-Hebei Greenhouse Gas-Air Pollution Interaction and Synergy Model (GAINS-JJJ) to simulate and evaluate the emission reduction potential and CO2 co-benefit of 13 air pollution control measures. The emission reductions of PM2.5, PM10, SO2, NOx, VOCs, and NH3 in 2025 were 1.8 (5%, compared with that in the baseline scenario), 2.5 (2%), 3.7 (16%), 20.0 (27%), 13.6 (15%), and 0.0 kt (0%), respectively. The reduction in CO2 emissions was 9.0 Mt (13%), whereas CH4 emissions increased by 203.3 kt (25% increase relative to that in the baseline scenario). SO2, NOx, and VOCs emission reductions derived from the power, industrial combustion, and solvent use sectors. CO2 reduction occurred mainly in the industrial combustion sector, and CH4 emission increased mainly due to the increase in coal mining activity. The highest synergistic CO2 reductions were achieved by restricting energy consumption in the high energy-consuming and high-emitting sectors; prohibiting new capacity in the steel, coke, cement, and flat glass industries; and replacing coal-fired power generation with renewable energy. Furthermore, the CO2 reduction co-benefit was highest for VOCs. In addition, this study suggests that promoting the policy of terminal electrification and simultaneously increasing the share of clean energy and the ability to consume renewable energy generation in the power sector are the keys to decreasing the emissions in Taiyuan.

Source differences in the components and cytotoxicity of PM2.5 from automobile exhaust, coal combustion, and biomass burning contributing to urban aerosol toxicity

Abstract. Although air quality guidelines generally use the atmospheric concentration of fine particulate matter (PM2.5) as a metric for air pollution evaluation and management, the fact cannot be ignored that different particle toxicities are unequal and significantly related to their sources and chemical compositions. Therefore, judging the most harmful source and identifying the toxic component would be helpful for optimizing air quality standards and prioritizing targeted PM2.5 control strategies to protect public health more effectively. Since the combustions of fuels, including oil, coal, and biomass, are the main anthropogenic sources of environmental PM2.5, their discrepant contributions to health risks of mixed ambient aerosol pollution dominated by the respective emission intensity and unequal toxicity of chemical components need to be identified. In order to quantify the differences between these combustion primary emissions, 10 types of PM2.5 from each typical source group, i.e., vehicle exhaust, coal combustion, and plant biomass (domestic biofuel) burning, were collected for comparative study with toxicological mechanisms. In total, 30 types of individual combustion samples were intercompared with representative urban ambient air PM2.5 samples, whose chemical characteristics and biological effects were investigated by component analysis (carbon, metals, soluble ions) and in vitro toxicity assays (cell viability, oxidative stress, inflammatory response) of human lung adenocarcinoma epithelial cells (A549). Carbonaceous fractions were plenteous in automobile exhaust and biomass burning, while heavy metals were more plentiful in PM2.5 from coal combustion and automobile exhaust. The overall ranking of mass-normalized cytotoxicity for source-specific PM2.5 was automobile exhaust > coal combustion > domestic plant biomass burning > ambient urban air, possibly with differential toxicity triggers, and showed that the carbonaceous fractions (organic carbon, OC; elemental carbon, EC) and redox-active transition metals (V, Ni, Cr) assisted by water-soluble ions (Ca2+, Mg2+, F−, Cl−) might play important roles in inducing cellular reactive organic species (ROS) production, causing oxidative stress and inflammation, resulting in cell injury and apoptosis, and thus damaging human health. Coupled with the source apportionment results of typical urban ambient air PM2.5 in eastern China, reducing toxic PM2.5 from these anthropogenic combustions will be greatly beneficial to public health. In addition to the air pollution control measures that have been implemented, like strengthening the vehicle emission standards, switching energy from coal to gas and electricity, and controlling the open incineration of agricultural straws, further methods could be considered, especially by preferentially reducing the diesel exhaust, lessening the coal combustion by replacement with low-ash clean coals, and depressing the rural crop straw biomass burning emissions.

Deep learning-based air pollution analysis on carbon monoxide in Taiwan

Global air pollution poses a threat to humanity. Specifically, CO directly affects cardiovascular and other organ tissues and leads to numerous chronic diseases and major public health problems. The effective implementation of a deep learning model for predicting variations in CO levels would enable the early formulation of policies for controlling air pollution. In this study, a seasonal gated recurrent unit (SGRU) model, which is a deep learning time-series prediction model, was developed to predict the levels of CO in Taiwan. Atmospheric CO measurements from 2005 to 2021 were collected from the Environmental Protection Administration of Taiwan and preprocessed using the Kalman filter to achieve accurate forecasting. The performance of the proposed SGRU model was compared with that of the autoregressive integrated moving average (ARIMA), seasonal ARIMA, exponential smoothing (ETS), Holt–Winters ETS, support vector regression, and seasonal long short-term memory models in terms of mean absolute percentage error (MAPE) and root mean square error. The SGRU model achieved the lowest MAPE value of 0.94, which demonstrated its superior performance. The construction of an accurate air pollution prediction model can assist government entities in formulating health and social care strategies and in planning future air pollution control measures.

The Burden of Cardiovascular Disease from Air Pollution in Rwanda.

Rwanda, like many countries in sub-Saharan Africa, is still relatively early in development. Industrialization and urbanization are major drivers of the county's economic growth. Rwanda is also undergoing an epidemiological transition, from a pattern of morbidity and mortality dominated by infectious diseases to a pattern shaped by non-communicable diseases (NCDs). The rise in NCDs is due, in part, to increasing exposures to environmental hazards. These include emissions from the growing number of motor vehicles and toxic occupational exposures. Cardiovascular disease (CVD) is now an increasingly important cause of death in Rwanda, and ambient air pollution is a CVD risk factor of growing importance. To quantify the burden of CVD attributable to air pollution in Rwanda and identify opportunities for prevention and control of air pollution and pollution-related disease. We relied on the 2019 Global Burden of Disease (GBD) study for information on levels, sources, and trends in household and ambient air pollution and the burden of pollution-related disease in Rwanda. Information on pollution sources was obtained from the Health Effects Institute State of Global Air 2019 report. An estimated 3,477 deaths (95% Uncertainty Interval [UI]: 2,500-4,600) in Rwanda in 2019 were attributable to air pollution-related CVD. Of these, 689 (UI: 283-1,300) deaths were from ambient air pollution-related CVD, while 2,788 (UI: 1,800-3,800) deaths were from household air pollution-related CVD. Rwanda is experiencing increased rates of disease and premature death from NCDs, including CVD, as the country grows economically. While household air pollution is still the top pollution-related cause of disease and premature death, rising levels of ambient air pollution are an increasingly important CVD risk factor. Actions taken now to curb rising levels of ambient air pollution will improve health, reduce CVD, increase longevity, and produce great economic benefit for Rwanda. The single most effective intervention against air pollution will be a rapid nationwide transition to renewable energy. We recommend additionally that Rwanda prioritize air pollution prevention and control, establish a robust, nationwide air monitoring network, support research on the health effects of air pollutants, and build national research capacity. The allocation of increased resources for rural and urban public health and health care will complement air pollution control measures and further reduce CVD. To incentivize a rapid transition to renewable energy in Rwanda and other nations, we recommend the creation of a new Global Green Development Fund.

An advection-diffusion equation-based approach to discern the meteorological factor effects on particle concentrations

The evaluation of the impact of meteorological conditions and anthropogenic emissions to PM2.5 concentrations is a subject of ongoing debetate, which holds significant importance in guiding the formulation and implementation of emission reduction policies. A new method, based on advection dispersion theory, has been developed to assess the impact of emission control measures and meteorological effects on the reduction of pollutant concentrations. This method involves classifying meteorological factors and utilizing the emission source intensity, which is characterized under various meteorological factors, to quantify the effects of meteorological factors and emission reduction on pollutant concentrations. Wind speed (WS), wind direction (WD), atmospheric stability (determined by cloud volume, solar radiation levels, surface wind speed) and mixed height are chosen as the key meteorological factors. Baoding City, situated within the Beijing-Tianjin-Hebei (BTH) region, is taken as an example in this study and is characterized by severe particle pollution. Due to the implementation of air pollution control measures from 2016 to 2020, the particulate pollution in this city has significantly reduced. The result of our method showed that despite the unfavorable conditions for pollutant dispersion during 2018 and 2021, the aggressive policies were estimated to have contributed to reductions in PM2.5 concentration. Specifically, there were reductions of 35.7, 19.6, 28.6, and 107.9 μg/m3 in spring, summer, autumn, and winter, respectively, from 2015 to 2018. Additionally, reductions of 8.2, 14.9, 30.0, and 50.7 μg/m3 were observed in the corresponding seasons from 2018 to 2021.

Long-term PM2.5 exposure and early-onset diabetes: Does BMI link this risk?

ObjectiveLimited studies investigated the association between high-level fine particulate matter (PM2.5) pollution and early-onset diabetes, leaving the possible metabolic mechanisms unclear. We assessed the association of cumulative PM2.5 exposure with diabetes, including early-onset, in high-pollution areas of China and explored whether metabolic factors mediated this association. Methods124,204 participants (≥18 years) from 121 counties in Hunan province, China, were enrolled between 2005 and 2020, with follow-up until 2021. The ground-level air pollution concentrations at each participant's residence were calculated using a high-quality dataset in China. The independent association of PM2.5 with incident diabetes and early-onset diabetes was assessed by Cox proportional hazards models. Restricted cubic splines were utilized to establish the exposure-response relationships. The role of metabolism-related mediators was estimated by mediation analysis. ResultsDuring a median follow-up of 8.47 (IQR, 6.65–9.82) years, there were 3650 patients with new-onset diabetes. Each 1 μg/m3 increase in the level of cumulative PM2.5 exposure was positively related to an increased incidence of diabetes (HR 1.177, 95 % CI 1.172–1.181) among individuals in the PM2.5 > 50 μg/m3 group after adjusting for multiple variables. The relationship of the PM2.5 dose-response curve for diabetes was non-linear. Significant associations between PM2.5 exposure and early-onset diabetes risk were observed, with this risk showing an increase with the earlier age of early diabetes onset. Males, young individuals (≤45 years), and those with a lower body mass index (BMI <24 kg/m2) appeared to be more susceptible to diabetes. Moreover, change in BMI significantly mediated 31.06 % of the PM2.5-diabetes relationship. ConclusionsLong-term cumulative PM2.5 exposure increased the risk of early-onset diabetes, which is partially mediated by BMI. Sustained air pollution control measures, priority protection of vulnerable individuals, and effective management of BMI should be taken to reduce the burden of diabetes.

Assessing the disease burden of air pollution on children and adolescents in China from 1990 to 2019

&lt;p&gt;Air pollution is a pressing concern in China, particularly its adverse effects on vulnerable populations such as children and adolescents. This study aimed to elucidate the disease burden in children and adolescents attributable to air pollution in geographical areas across China from 1990 to 2019. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 methodology to estimate disease burden attributable to air pollution in 33 areas of China, including provinces, autonomous regions, municipalities, and special administrative regions. In 2019, approximately 10,511 childhood deaths and 932,095 disability-adjusted life-years (DALYs) were attributable to air pollution in China. The DALYs was higher for boys and infants &lt;1 year than it was for girls. Lower respiratory infections, neonatal preterm birth, and neonatal encephalopathy caused by birth asphyxia and trauma were the main air pollution-related diseases. The disease burden attributable to air pollution in children and adolescents decreased significantly from 1990 to 2019; with the average annual percent change (AAPC) of ?9.11% ([95%CI, ?9.61% to ?8.60%], P&lt;0.001) for death rate, and ?9.09% ([?9.59% to ?8.58%], P&lt;0.001) for DALYs rate. Disease burden attributable to air pollution in children and adolescents varied across provinces, with DALYs rate per 100,000 population ranged from 16.88 in Hong Kong to 2,152.54 in Tibet, peaking in the health area five. These findings highlight the necessity for province-specific research into the impacts of air pollution on childhood health in China, as well as improved air pollution control measures.&lt;/p&gt;

Effectiveness of public policies related to traffic emissions in improving air quality in Brazil: A causal inference study using Bayesian structural time-series models

Air pollution is a major environmental health risk, particularly in low- and middle-income countries. In Brazil, the government has implemented progressive stages of traffic emission controls since 1986 through a program called “Proconve”. In this study, we evaluated the effectiveness of two of these stages, Proconve stages L-5 and P-7, in reducing air pollution in the 10 most populated cities in Brazil. We used Bayesian structural time-series models to estimate the causal effect of the vehicle emission control measures on the air pollution time series for each city and air pollutant (PM2.5, O3, NO2, and CO), accounting for potential confounding factors such as temperature and humidity. While previous studies have shown positive effects of control measures on air quality, our study suggests that the effects may not always be statistically significant, which has implications for the design and interpretation of future studies. Our study provides valuable information for policymakers in Brazil and adds to the international literature on the effectiveness of air pollution control measures. Despite the lack of statistically significant results, our study highlights the importance of considering statistical power and unmeasured confounding factors when evaluating the effectiveness of air pollution control measures.

Aerosol Effects on Water Cloud Properties in Different Atmospheric Regimes

AbstractAerosol‐cloud interaction remains one of the least understood processes in climate science arena, despite its profound impacts in radiation and water budget perturbations. The aerosol effects on clouds largely depend on aerosol characteristics. Here, we implemented 17‐year (2003–2020) data set of aerosol, cloud, and meteorological factors collected over East Asia—a highly polluted region with recent decreasing trend of air pollution due to control measures—to elucidate atmospheric regime‐dependent aerosol effects on water cloud properties by simultaneously accessing the response of air pollution control measures in cloud field. The study found a very close relationship between aerosol loading and cloud properties modifications in the continental region of East Asia with a significant response of air pollution control measures in the cloud field. The study further revealed that aerosols of the polluted continental atmosphere affected cloud micro‐ and macro‐physics differently than aerosols of the clean maritime atmosphere: in the former, increased aerosol loading increased the stability under cloud base and then enhanced cloud droplet collision‐coalescence process, resulting to increase cloud droplet size by decreasing cloud top height; whereas in the latter, increased aerosol loading decreased cloud droplet size without notable influence in the atmosphere thermodynamics and cloud top height. This study further showed a complex aerosol‐cloud interaction process in the polluted maritime atmosphere due to the mixed effect of polluted continental and clean maritime atmospheres. In all atmospheric regimes, cloud fraction was found to increase with the increase of aerosol loading.

Achievements and challenges in improving air quality in China: Analysis of the long-term trends from 2014 to 2022

Due to the implementation of air pollution control measures in China, air quality has significantly improved, although there are still additional issues to be addressed. This study used the long-term trends of air pollutants to discuss the achievements and challenges in further improving air quality in China. The Kolmogorov-Zurbenko (KZ) filter and multiple-linear regression (MLR) were used to quantify the meteorology-related and emission-related trends of air pollutants from 2014 to 2022 in China. The KZ filter analysis showed that PM2.5 decreased by 7.36 ± 2.92% yr−1, while daily maximum 8-h ozone (MDA8 O3) showed an increasing trend with 3.71 ± 2.89% yr−1 in China. The decrease in PM2.5 and increase in MDA8 O3 were primarily attributed to changes in emission, with the relative contribution of 85.8% and 86.0%, respectively. Meteorology variations, including increased ambient temperature, boundary layer height, and reduced relative humidity, also contributed to the reduction of PM2.5 and the enhancement of MDA8 O3. The emission-related trends of PM2.5 and MDA8 O3 exhibited continuous decrease and increase, respectively, from 2014 to 2022, while the variation rates slowed during 2018–2020 compared to that during 2014–2017, highlighting the challenges in further improving air quality, particularly in simultaneously reducing PM2.5 and O3. This study recommends reducing NH3 emissions from the agriculture sector in rural areas and transport emissions in urban areas to further decrease PM2.5 levels. Addressing O3 pollution requires the reduction of O3 precursor gases based on site-specific atmospheric chemistry considerations.

Comprehensive evaluation of air pollution emission permit allocation: Effectiveness, efficiency, and equity in China's environmental management framework

Though the emission permit system is a pivotal policy in China's environmental management, there's a lack of comprehensive assessments for air pollutant emission quota allocation. In this study, a comprehensive 3E integrated assessment approach, encompassing the dimensions of Effectiveness, Efficiency, and Equity, was employed to thoroughly evaluate methods for allocating air pollution emission permits. This analysis was based on plant-level data derived from 9181 industrial enterprises situated in seven major cities within the Beijing-Tianjin-Hebei region of China during the year 2017. The Effectiveness assessment encompassed the utilization of the WRF-CMAQ model for simulating air pollution concentrations of PM2.5, SO2, and NO2. The findings underscored the imperative need for intensified efforts to control PM2.5 and NO2 emissions, particularly in achieving compliance with the national annual average level II thresholds. Efficiency assessment navigated the delicate balance between environmental benefits and costs, with a particular emphasis on health benefits and expenses associated with pollution abatement. The results revealed annual net benefits ranging from 8.4 to 19.9 billion yuan, illuminating a highly favorable cost-benefit equilibrium. Equity assessment delved into the examination of the equitable distribution of resources and impacts. Utilizing metrics of Environmental Gini Coefficient (EGC) and Green Contribution Coefficient (GCC), the analysis uncovered disparities in most scenarios and cities, shedding light on areas necessitating targeted policy interventions. Overall, the integrated 3E assessment offers a holistic comprehension of policy impacts. Based on the overall 3E weighted scores, results showed that the allocation method that considered both the emission standard and the pollutant transmission (Scenario S2) outperformed among the three designed allocation methods. In the future, policy efforts should focus on enhancing comprehensive assessments, ensuring the sustainable development and betterment of environmental quality through air pollution control measures.

Air Quality Data Acquisition Through Temporal Data Modeling

The paper presents a novel temporal data model for acquiring air quality data. The proposed model uses the free and open-source Postgres database with tuple time stamping, resulting in rapid and effective data extraction. The conventional relational database SQL server for data extraction is used in this paper as the foundation for an air quality temporal database model. The air quality data set collected for MDU Rohtak (source: Central Control Room for Air Quality Management - All India) is utilized to test and determine the outcomes of the proposed model. Valid time is used as the time dimension for capturing data values, together with tuple timestamping. The Postgres "tsrange" datatype is used to record the timestamp. To eliminate data duplication, the dataset is cleaned up and normalized. Using the air quality temporal data model, AQI data at various time points is effectively extracted. The present model data extraction is compared with the conventional relational data model using SQL Server database. The air quality data extraction process takes a remarkably minimal amount of time, with an average of 23% lesser time than SQL server database. It takes only a few milliseconds to extract the AQI data, and the results of the experiment are ready immediately after that. The suggested model is helpful in decision-making and offers decision-makers useful information and the tool they need to enhance air quality. The results are relevant to the study of the AQI components by different pollution management agencies like central and state pollution control boards, national green tribunal and Ministry of the Environment for efficient air pollution control measures.

Remote Sensing of Planetary Boundary Layer Thermodynamic and Material Structures over a Large Steel Plant, China

Air pollutants emitted by industries can significantly affect local air quality and jeopardize human health, and the study of the boundary layer thermodynamic structure and diffusion capacity over industrial plants can be beneficial for the improvement of corporate air pollution control measures. The continuous high temporal and spatial resolution monitoring of the boundary layer structure (thermal, dynamic, and material) by advanced remote sensing instruments over a single strong industrial source (steel plant) in Shanxi Province, China, from May to June 2021 revealed the boundary layer characteristics under the influence of a single strong local anthropogenic influence. Strong nocturnal temperature inversions and grounded temperature inversions were prone to occur over industrial sources. The local wind field was characterized by significant daily variations, with the whole-layer airflow during the daytime dominated by southwesterly winds. At night, under the influence of radiation, topography, and surface, the airflow was dominated by easterly winds with low speeds (less than 2 m/s) in the low altitude range of 100 m, while the wind direction was still dominated by southwesterly winds with higher speeds in the altitude of 100 m. In addition, the average atmospheric diffusion capacity increased significantly with height in the 500 m altitude range, with an increase in rate of about 2~3 times/50 m, and continued to show a discontinuous increasing trend above 500 m. Combined with the wind direction and wind speed contours, it can be seen that the pollutants can be effectively dispersed at a height of 100 m. The thermal and turbulent boundary layer heights were highly consistent, and the material boundary layer height was significantly higher than the thermal and turbulent boundary layer heights during the daytime when convection was strong.