Numerical simulations for the sources apportionment and control strategies of PM2.5 over Pearl River Delta, China, part I: Inventory and PM2.5 sources apportionment

Exploring efficient strategies for air quality improvement in China based on its regional characteristics and interannual evolution of PM2.5 pollution

Fine particulate matter (PM2.5) harms human health and hinders normal human life. Considering the serious complexity and obvious regional characteristics of PM2.5 pollution, it is urgent to fill in the comprehensive overview of regional characteristics and interannual evolution of PM2.5. This review studied the PM2.5 pollution in six typical areas between 2014 and 2022 based on the data published by the Chinese government and nearly 120 relevant literature. We analyzed and compared the characteristics of interannual and quarterly changes of PM2.5 concentration. The Beijing-Tianjin-Hebei region (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) made remarkable progress in improving PM2.5 pollution, while Fenwei Plain (FWP), Sichuan Basin (SCB) and Northeast Plain (NEP) were slightly inferior mainly due to the relatively lower level of economic development. It was found that the annual average PM2.5 concentration change versus year curves in the three areas with better pollution control conditions can be merged into a smooth curve. Importantly, this can be fitted for the accurate evaluation of each area and provide reliable prediction of its future evolution. In addition, we analyzed the factors affecting the PM2.5 in each area and summarize the causes of air pollution in China. They included primary emission, secondary generation, regional transmission, as well as unfavorable air dispersion conditions. We also suggested that the PM2.5 pollution control should target specific industries and periods, and further research need to be carried out on the process of secondary production. The results provided useful assistance such as effect prediction and strategy guidance for PM2.5 pollution control in Chinese backward areas.

The role of NOx in Co-occurrence of O3 and PM2.5 pollution driven by wintertime east Asian monsoon in Hainan

Clarifying the driving forces of O3 and fine particulate matter (PM2.5) co-pollution is important to perform their synergistic control. This work investigated the co-pollution of O3 and PM2.5 in Hainan Province using an observation-based model and explainable machine learning. The O3 and PM2.5 pollution that occurs in winter is affected by the wintertime East Asian Monsoon. The O3 formation shifts from a NOx-limited regime with a low O3 production rate (PO3) in the non-pollution season to a transition regime with a high PO3 in the pollution season due to an increase in NOx concentrations. Increased O3 and atmospheric oxidation capacity promote the conversion from gas-phase precursors to aerosols. Meanwhile, the high concentration of particulate nitrate favors HONO formation via photolysis, in turn facilitating O3 production. Machine learning reveals that NOx promotes O3 and PM2.5 co-pollution during the pollution period. The PO3 shows an upward trend at the observation site from 2018 to 2022 due to the inappropriate reduction of volatile organic compounds (VOCs) and NOx in the upwind areas. Our results suggest that a deep reduction of NOx should benefit both O3 and PM2.5 pollution control in Hainan and bring new insights into improving air quality in other regions of China in the future.

Contribution of local and surrounding anthropogenic emissions to a particulate matter pollution episode in Zhengzhou, Henan, China

In this study, we simulated the spatial and temporal processes of a particulate matter (PM) pollution episode from December 10-29, 2019, in Zhengzhou, the provincial capital of Henan, China, which has a large population and severe PM pollution. As winter is the high incidence period of particulate pollution, winter statistical data were selected from the pollutant observation stations in the study area. During this period, the highest concentrations of PM_2.5 (atmospheric PM with a diameter of less than 2.5 µm) and PM₁₀ (atmospheric PM with a diameter of less than 10 µm) peaked at 283 μg m^-3 and 316 μg m^-3, respectively. The contribution rates of local and surrounding regional emissions within Henan (emissions from the regions to the south, northwest, and northeast of Zhengzhou) to PM concentrations in Zhengzhou were quantitatively analyzed based on the regional Weather Research and Forecasting model coupled with Chemistry (WRF/Chem). Model evaluation showed that the WRF/Chem can accurately simulate the spatial and temporal variations in the PM concentrations in Zhengzhou. We found that the anthropogenic emissions south of Zhengzhou were the main causes of high PM concentrations during the studied episode, with contribution rates of 14.39% and 16.34% to PM_2.5 and PM₁₀, respectively. The contributions of anthropogenic emissions from Zhengzhou to the PM_2.5 and PM₁₀ concentrations in Zhengzhou were 7.94% and 7.29%, respectively. The contributions of anthropogenic emissions from the area northeast of Zhengzhou to the PM_2.5 and PM₁₀ concentrations in Zhengzhou were 7.42% and 7.18%, respectively. These two areas had similar contributions to PM pollution in Zhengzhou. The area northeast of Zhengzhou had the lowest contributions to the PM_2.5 and PM₁₀ concentrations in Zhengzhou (5.96% and 5.40%, respectively).

Understanding the inter-city causality and regional transport of atmospheric PM2.5 pollution in winter in the Harbin-Changchun megalopolis in China: A perspective from local and regional

Harbin-Changchun megalopolis (HCM) is the typical cold urban agglomeration in China, where PM_2.5 pollution is still serious in winter against the backdrop of continuous improvement in annual air quality in China. To further understand interactions of atmospheric pollution among HCM cities, inter-city causality and regional transport of PM_2.5 in the winter in the HCM were comprehensively investigated by using convergent cross mapping (CCM) and CMAQ-BFM methods. CCM analysis results suggest strong bidirectional causal relationships between cities in the HCM, and the causality during polluted episodes were significantly larger than that during clean period. In addition, the influence on local PM_2.5 from the HCM western cities were larger than that from cities in the southeast. Inter-city and regional transport contributions results demonstrated that although local emission were the largest contributors among 14 sub-regions for most HCM cities, interactions among cities were strong. Regional transport (42.8%-77.4%) largely contributes to HCM cities' PM_2.5 concentrations. Among three regions outside the HCM, NMG (including part of inner Mongolia and Baicheng city in Jilin, 9.1%) was the largest contributor to the PM_2.5 concentration in the whole HCM, followed by JLS (including Liaoning Province, Tonghua and Baishan cities in Jilin province, 5.1%) and HLJ (including cities of Heihe, Yichun, Jiamusi, Hegang, Shuangyashan, Jixi, Qitaihe in the Heilongjiang province, 3.8%). Regional transport contribution to the most HCM cities increased significantly from excellent to heavily polluted days. Furthermore, close relationships between transport paths/intensity and wind direction/speed in studied region suggests that we can quantitatively guide the regional joint emergency prevention and control before and during heavily polluted events based on regional weather forecasts in the future.

Source contribution analysis of PM2.5 using Response Surface Model and Particulate Source Apportionment Technology over the PRD region, China

Identifying the emission source contributions to PM_2.5 is essential for a sound PM_2.5 pollution control policy. In this study, we conduct a comparative analysis of PM_2.5 source contributions over the Pearl River Delta (PRD) region of China using two advanced source contribution modeling techniques: Response Surface Model (RSM) and Particulate Source Apportionment Technology (PSAT). Our comparative analyses show that RSM and PSAT can both reasonably predict the contribution of primary PM_2.5 emission sources to PM_2.5 formation due to its linear nature. For the secondary PM_2.5 formed by the nonlinear reactions among PM_2.5 precursors, however, our study shows that PSAT appears to have limitations in quantifying the nonlinear contribution of PM_2.5 precursors to emission reductions, while RSM seems to better address the nonlinear relationship among PM_2.5 precursors (e.g., PM_2.5 disbenefits due to local NO_x emission reductions in major cities with high NO_x emissions). The pilot study case results show that for the ambient PM_2.5 in the central cities (Guangzhou, Shenzhen, Foshan, Dongguan, and Zhongshan) of the PRD, the regional source emissions contribute the most by 42-66%; the dust emissions are the top contribution sources (29-34% by RSM and 27-31% by PSAT), and the mobile sources are listed as the secondary contributors accounting for 16-25% by RSM and 19-30% by PSAT among the anthropogenic emission sources. The city-scale cooperation on emission reductions and the enhancement of dust and mobile emission control are recommended to effectively reduce the ambient PM_2.5 concentration in the PRD.

What Are the Sectors Contributing to the Exceedance of European Air Quality Standards over the Iberian Peninsula? A Source Contribution Analysis

The Iberian Peninsula, located in southwestern Europe, is exposed to frequent exceedances of different threshold and limit values of air pollution, mainly related to particulate matter, ozone, and nitrous oxide. Source apportionment modeling represents a useful modeling tool for evaluating the contribution of different emission sources or sectors and for designing useful mitigation strategies. In this sense, this work assesses the impact of various emission sectors on air pollution levels over the Iberian Peninsula using a source contribution analysis (zero-out method). The methodology includes the use of the regional WRF + CHIMERE modeling system (coupled to EMEP emissions). In order to represent the sensitivity of the chemistry and transport of gas-phase pollutants and aerosols, several emission sectors have been zeroed-out to quantify the influence of different sources in the area, such as on-road traffic or other mobile sources, combustion in energy generation, industrial emissions or agriculture, among others. The sensitivity analysis indicates that large reductions of precursor emissions (coming mainly from energy generation, road traffic, and maritime-harbor emissions) are needed for improving air quality and attaining the thresholds set in the European Directive 2008/50/EC over the Iberian Peninsula.

Air Quality in the Harbin-Changchun Metropolitan Area in Northeast China: Unique Episodes and New Trends

Because of the unique geographical, climate, and anthropogenic emission characteristics, it is meaningful to explore the air pollution in the Harbin-Changchun (HC) metropolitan area. In this study, the Air Quality Index (AQI) and the corresponding major pollutant were investigated for the HC cities, based on the air quality data derived from the China National Environmental Monitoring Center. The number of days with the air quality level of "good" gradually increased during recent years, pointing to an improvement of the air quality in HC. It was also found that ozone, a typical secondary pollutant, exhibited stronger inter-city correlations compared to typical primary pollutants such as carbon monoxide and nitrogen dioxide. In addition, for nearly all the HC cities, the concentrations of fine particulate matter (PM2.5) decreased substantially in 2020 compared to 2015. However, this was not the case for ozone, with the most significant increase of ozone observed for HC's central city, Harbin. This study highlights the importance of ozone reduction for further improving HC's air quality, and the importance of agricultural fire control for eliminating heavily-polluted and even off-the-charts PM2.5 episodes.

A comparative study of EOF and NMF analysis on downward trend of AOD over China from 2011 to 2019

In recent decades China has experienced high-level PM_2.5 pollution and then visible air quality improvement. To understand the air quality change from the perspective of aerosol optical depth (AOD), we adopted two statistical methods of Empirical Orthogonal Functions (EOF) and Non-negative Matrix Factorization (NMF) to AOD retrieved by MODIS over China and surrounding areas. Results showed that EOF and NMF identified the important factors influencing AOD over China from different angles: natural dusts controlled the seasonal variation with contribution of 42.4%, and anthropogenic emissions have larger contribution to AOD magnitude. To better observe the interannual variation of different sources, we removed seasonal cycles from original data and conducted EOF analysis on AOD monthly anomalies. Results showed that aerosols from anthropogenic sources had the greatest contribution (27%) to AOD anomaly variation and took an obvious downward trend, and natural dust was the second largest contributor with contribution of 17%. In the areas surrounding China, the eastward aerosol transport due to prevailing westerlies in spring significantly influenced the AOD variation over West Pacific with the largest contribution of 21%, whereas the aerosol transport from BTH region in winter had relative greater impact on the AOD magnitude. After removing seasonal cycles, biomass burning in South Asia became the most important influencing factor on AOD anomalies with contribution of 10%, as its interannual variability was largely affected by El Niño. Aerosol transport from BTH was the second largest contributor with contribution of 8% and showed a decreasing trend. This study showed that the downward trend of AOD over China since 2011 was dominated by aerosols from anthropogenic sources, which in a way confirmed the effectiveness of air pollution control policies.

Insights into the source-specific health risk of ambient particle-bound metals in the Pearl River Delta region, China

Quantification of source-specific health risks of PM2.5 plays an essential role in health-oriented air pollution control. However, there is limited evidence supporting the source-based risk apportionment of particle-bound metals. In this study, source-specific cancer and non-cancer risk characterization of 12 particle-bound metals was performed in the Pearl River Delta (PRD) region, China. A combination of health risk assessment model and receptor-based source apportionment modeling with positive matrix factorization (PMF) was applied for characterizing the spatial-temporal patterns for inhalation health risks of particle-bound metals in three main city clusters, inland area and coastal area in the region from December 2014 through July 2016. Results showed that the carcinogenic risk of particle-bound metals for adults (4.13 × 10-5) was higher than that for children (9.53 × 10-6) in the PRD region. The highest and significant non-carcinogenic risk was found in the northwest city cluster. Industrial emission (63.3%) were the dominant contributors to the cancer risk, while the main contributors to the non-cancer risk were the vehicle emission source (33.2%) in the dry season and industrial emission (30.8%) in the wet season. Our results provide important evidence for spatial source-specific health risks with temporal characteristics of particle-bound metals in most densely populated areas in the southern China, and suggest that reduction of industrial and vehicle emissions could facilitate more cost-effective PM2.5 control measures to improve human health.

Ingestion of GNSS-Derived ZTD and PWV for Spatial Interpolation of PM2.5 Concentration in Central and Southern China

With the increasing application of global navigation satellite system (GNSS) technology in the field of meteorology, satellite-derived zenith tropospheric delay (ZTD) and precipitable water vapor (PWV) data have been used to explore the spatial coverage pattern of PM_2.5 concentrations. In this study, the PM_2.5 concentration data obtained from 340 PM_2.5 ground stations in south-central China were used to analyze the variation patterns of PM_2.5 in south-central China at different time periods, and six PM_2.5 interpolation models were developed in the region. The spatial and temporal PM_2.5 variation patterns in central and southern China were analyzed from the perspectives of time series variations and spatial distribution characteristics, and six types of interpolation models were established in central and southern China. (1) Through correlation analysis, and exploratory regression and geographical detector methods, the correlation analysis of PM_2.5-related variables showed that the GNSS-derived PWV and ZTD were negatively correlated with PM_2.5, and that their significances and contributions to the spatial analysis were good. (2) Three types of suitable variable combinations were selected for modeling through a collinearity diagnosis, and six types of models (geographically weighted regression (GWR), geographically weighted regression kriging (GWRK), geographically weighted regression—empirical bayesian kriging (GWR-EBK), multiscale geographically weighted regression (MGWR), multiscale geographically weighted regression kriging (MGWRK), and multiscale geographically weighted regression—empirical bayesian kriging (MGWR-EBK)) were constructed. The overall R² of the GWR-EBK model construction was the best (annual: 0.962, winter: 0.966, spring: 0.926, summer: 0.873, and autumn: 0.908), and the interpolation accuracy of the GWR-EBK model constructed by inputting ZTD was the best overall, with an average RMSE of 3.22 μg/m³ recorded, while the GWR-EBK model constructed by inputting PWV had the highest interpolation accuracy in winter, with an RMSE of 4.5 μg/m³ recorded; these values were 2.17% and 4.26% higher than the RMSE values of the other two types of models (ZTD and temperature) in winter, respectively. (3) The introduction of the empirical Bayesian kriging method to interpolate the residuals of the models (GWR and MGWR) and to then correct the original interpolation results of the models was the most effective, and the accuracy improvement percentage was better than that of the ordinary kriging method. The average improvement ratios of the GWRK and GWR-EBK models compared with that of the GWR model were 5.04% and 14.74%, respectively, and the average improvement ratios of the MGWRK and MGWR-EBK models compared with that of the MGWR model were 2.79% and 12.66%, respectively. (4) Elevation intervals and provinces were classified, and the influence of the elevation and the spatial distribution of the plane on the accuracy of the PM_2.5 regional model was discussed. The experiments showed that the accuracy of the constructed regional model decreased as the elevation increased. The accuracies of the models in representing Henan, Hubei and Hunan provinces were lower than those of the models in representing Guangdong and Guangxi provinces.

Two-Tier Synergic Governance of Greenhouse Gas Emissions and Air Pollution in China's Megacity, Shenzhen: Impact Evaluation and Policy Implication

Making a cost-effective governance of greenhouse gas (GHG) emissions and air pollution is of great importance for megacities to pursue a sustainable future. To achieve this, the present study advocates megacities to implement a two-tier synergic governance system consisting of both synergic governance between GHG and air pollutant emission reductions and between megacities and their surrounding regions. Based on the LEAP model and WRF-SMOKE-CMAQ simulation platform, this study found that climate governance of China's megacity, Shenzhen, could synergistically contribute to decreasing urban annual PM_2.5 concentration by 5.6% in 2030. Using synergic governance with surrounding regions could further help cap and then quickly decrease the megacity's GHG emissions and lower its PM_2.5 concentrations by an additional 11.8%. The results demonstrated the substantial effects of transdepartment and transregional synergic governance on Shenzhen's GHG emission reduction and air quality improvement. Furthermore, this study suggested road transportation and power generation and supply as the two priority fields for wide-ranging megacities to promote two-tier synergic governance, highlighting an integration of improved urban electrification with high-efficiency electricity use and a renewable-based power supply.

Air Quality During COVID-19 Lockdown in the Yangtze River Delta and the Pearl River Delta: Two Different Responsive Mechanisms to Emission Reductions in China

Despite the large reduction in anthropogenic activities due to the outbreak of COVID-19, air quality in China has witnessed little improvement and featured great regional disparities. Here, by combining observational data and simulations, this work aims to understand the diverse air quality response in two city clusters, Yangtze River Delta region (YRD) and Pearl River Delta region (PRD), China. Though there was a noticeable drop in primary pollutants in both the regions, differently, the maximum daily 8 h average ozone (O3) soared by 20.6-76.8% in YRD but decreased by 15.5-28.1% in PRD. In YRD, nitrogen oxide (NOx) reductions enhanced O3 accumulation and hence increased secondary aerosol formation. Such an increment in secondary organic and inorganic aerosols under stationary weather reached up to 36.4 and 10.2%, respectively, which was further intensified by regional transport. PRD was quite the opposite. The emission reductions benefited PRD air quality, while regional transport corresponded to an increase of 17.3 and 9.3% in secondary organic and inorganic aerosols, respectively. Apart from meteorology, the discrepancy in O3-VOCs-NOx relationships determined the different O3 responses, indicating that future emission control shall be regionally specific, instead of one-size-fits-all cut. Overall, the importance of regionally coordinated and balanced control strategy for multiple pollutants is highly emphasized.

Importance of regional PM2.5 transport and precipitation washout in heavy air pollution in the Twain-Hu Basin over Central China: Observational analysis and WRF-Chem simulation

With observational analysis and WRF-Chem simulation on a heavy air pollution event in January 2019 over the Twain-Hu Basin (THB) in Central China, this study characterized the regional transport of PM_2.5 emitted from the North China Plain (NCP) to the THB region in Central China and quantitatively assessed the influence of the regional PM_2.5 transport and precipitation washout on PM_2.5 change in the wintertime heavy air pollution over the THB. It was found that the THB's heavy air pollution event was exacerbated by the strong northeasterly winds driving a quasi 2-day time lag of regional PM_2.5 transport from the NCP to the THB. The multi-scale atmospheric circulations of cold air invasion influenced by East Asian winter monsoon and the terrain block of THB altered the structures of regional PM_2.5 transport in deteriorating air quality to the THB. It was assessed for the THB region that the enhancing contribution of regional PM_2.5 transport to the high air pollution level reached up to 70.5% in the heavy air pollution, and the precipitation washout could contribute the 55.3% PM_2.5 removal to dissipating the PM_2.5 pollution over the THB with frequent precipitation and wet environment, distinguishing from the dominance of wind-cleaning air pollution in the other regions in China.

Characteristics of the source apportionment of primary and secondary inorganic PM2.5 in the Pearl River Delta region during 2015 by numerical modeling

Fine particulate matter (PM_2.5) contains both primary and secondary components, and their source apportionment characteristics in the Pearl River Delta (PRD) region during 2015 were compared by applying an air quality model coupled with an on-line tracer-tagged module. The results of contributions from different source regions to primary PM_2.5 (PPM_2.5) and secondary inorganic PM_2.5 (SIPM_2.5) in four selected cities show that the effect of regional transport on the SIPM_2.5 level is stronger than that on the PPM_2.5 level in the PRD region. For both Guangzhou city and the average of the entire PRD region, the industrial (25-40%) and transportation (20-25%) sectors are major sources of PPM_2.5 and SIPM_2.5. However, the residential sector contributes approximately 25% to the PPM_2.5 level, mainly from residential biomass burning, but accounts for only approximately 10% of the SIPM_2.5 level. The relative importance of each sector to the contributions from local and regional transport indicates that industrial emissions appear to lead to regional air pollution, while the transportation emissions seem to mainly affect the local and surrounding areas. Considering the impact of regional contributions to air quality, efforts made to reduce emissions in each city could not only improve the local air quality but also benefit downstream regions. To further decrease the PM_2.5 level, the local government of each city in the PRD region should not only continue to strengthen the control of local emissions, such as those from transportation and residential biomass burning, but also increase their focus on regional joint prevention and control strategies with upstream area (such as northern Guangdong Province, and Jiangxi, Fujian and Hunan provinces).

Contribution of Regional PM2.5 Transport to Air Pollution Enhanced by Sub-Basin Topography: A Modeling Case over Central China

The Twain-Hu basin (THB), covering the lower plain of Hubei and Hunan provinces in Central China, has experienced severe air pollution in recent years. However, the terrain effects of such sub-basin on air quality over the THB have been incomprehensibly understood. A heavy PM2.5 pollution event occurred over the THB during 4–10 January 2019. By using the observations and WRF-Chem simulations, we investigated the underlying mechanisms of sub-basin effects on the air pollution with several sensitivity experiments. Observationally, air pollution in the western THB urban area with an average PM2.5 concentration of 189.8 μg m−3, which was more serious than the eastern urban area with the average PM2.5 concentration of 106.3 μg m−3, reflecting a different influence of topography on air pollution over the THB. Simulation results revealed that the terrain effect can contribute 12.0% to increasing the PM2.5 concentrations in the western THB, but slightly mitigate the pollution extent in the eastern THB with the contribution of −4.6% to PM2.5 during the heavy pollution episode. In particular, the sub-basin terrain was conducive to the accumulation of PM2.5 by regional transport with the contribution of 39.1 %, and contrarily lowered its local pollution by −57.0% via the enhanced atmospheric boundary layer height and ventilation coefficients. Given a heavy air pollution episode occurring over the THB, such inverse contribution of terrain effects reflected a unique importance of sub-basin topography in regional transport of air pollutants for air pollution in central China.

Regional transport in Beijing-Tianjin-Hebei region and its changes during 2014-2017: The impacts of meteorology and emission reduction

Emissions of air pollutants have been dramatically reduced in the Beijing-Tianjin-Hebei (BTH) region of China during 2014-2017. However, impacts of emission reduction on regional air quality are not well quantified. This study evaluates the impacts of emission reduction and inter-annual meteorological conditions on regional air pollution transport in BTH region by employing Community Multiscale Air Quality model embedded with the Integrated Source Apportionment Model (CMAQ-ISAM). Results suggest that the regional transport contributed 32.5%-68.4% of total PM_2.5 mass concentrations and 52.4%-83.2% of sulfate, nitrate and ammonium in 2017. During 2014-2017, the annual averaged PM_2.5 concentrations in BTH region decreased by 33%, of which the decrease of local emissions, inter-regional transport and transport from outside the BTH region contributed for 47%, 25%, and 28%, respectively. Emission reductions (91%) mitigate not only the impacts of local sources, but also influence the regional transport with similar magnitude, demonstrating the effectiveness of multiple regional joint controls. The variation of meteorology contributes only 9% to the decrease of PM_2.5 in BTH, with higher contributions from the change of regional transport compared to local sources since the regional transport is more sensitive to the meteorology variation. The impacts of meteorological variations are considerable, with over 20% on the relative changes of local and regional contributions, and up to 40% on regional transport in spring and winter. Therefore, more strengthened regional joint air pollution control is suggested in winter and spring for this region.

Joint pollution and source apportionment of PM2.5 among three different urban environments in Sichuan Basin, China

The PM_2.5 were sampled in three different urban environments: (city of) Chengdu, Leshan, and Dazhou, which are located in Sichuan Basin. 8 types of water-soluble ion and 25 types of metal element were measured in each PM_2.5 sample across the seasons of 2017. The study results suggest that the joint PM_2.5 pollution among the three cities mainly occurred in autumn and winter, and the air quality of Chengdu and Leshan was largely affected by Dazhou. Overall, the mass concentrations of PM_2.5 of these three cities exhibited no statistically significant differences. However, Leshan had the highest level of ionic pollution, and the dominant form of inorganic compound in ambient PM_2.5 was NH₄NO₃, and a competitive relationship between form of NH₄NO₃ and (NH₄)₂SO₄ (NH₄HSO₄) was found as well. High homology between SO₄^2- and NO₃^- has been observed in all the three cities, and the ratio between [SO₄^2-] and [NO₃^-] indicated that the stationary source contributed the most to ambient PM_2.5 in Dazhou. The mass concentrations of the total metal elements from the three cities exhibited similar levels, nevertheless, Dazhou had the highest mass fraction of total metal elements in PM_2.5. The enrichment factor of each element indicated that the natural source was highly contributory to the crustal elements in PM_2.5 of all the three cities, whereas Cr, Cu, Se, Mo, Cd, Tl and Bi were primarily originated from anthropogenic source. In addition, the source apportionment of PM_2.5 suggest that Dazhou had the different factors and factor-contributions comparing with Chengdu and Leshan.

Source and exposure apportionments of ambient PM2.5 under different synoptic patterns in the Pearl River Delta region

PM_2.5 is one of the most notorious ambient pollutants in the Pearl River Delta (PRD) region during episodic conditions. In this work, the Comprehensive Air Quality Model with extension (CAMx) was used together with the Particulate Source Apportionment Technology (PSAT) module to analyze the influences of different sources on PM_2.5 concentration in the PRD region under different synoptic patterns (sea high pressure, sub-tropical high pressure and equalizing pressure field). The result shows that the PM_2.5 concentration increases to different degrees under the three synoptic patterns. The emissions outside the PRD region contribute more than 54% under episodic conditions. The source category contribution varies little under different synoptic patterns. Area (46%), mobile (21%) and industry point source (16%) are the major contributors over the three episodic cases. The regional source contributions (from other cities within the PRD) to Foshan, Zhongshan and Zhaoqing are larger and can reach up to 33%. People living in the PRD region are more exposed to pollutants produced from the area and mobile sources. About 80% of the population is exposed to PM_2.5 levels exceeding the IT-3 standard during the pollution episodes.

Spatially differentiated effects of socioeconomic factors on China's NOx generation from energy consumption: implications for mitigation policy

Nitrogen oxides (NO_x) has become the priority of China's air pollution control, but the regional socio-economic factors responsible for NO_x generation are embedded with spatial disparities, which leads to different effects of air quality policy at the local level. This study applied a geographically weighted regression (GWR) model to investigate the drivers of NO_x generation from energy consumption (NGEC) in China's 30 provinces, to explore nonstationary spatial effects of NGEC. The results showed that population size has always been the dominant factor in spatial NGEC across all regions of China, although there is a minor north-south difference. However, the effect of per capita GDP and energy intensity leads to a significant north-south difference when they are influencing NGEC, which shows a minor west-east difference from thermal power generation (TE). We also found that in Northern and Northeast China, the transition towards cleaner energy structure based on natural gas has started correlating significantly with NO_x generation through a weakly negative effect in 2015. Our findings show alternative strategies on NO_x reduction, which include the spatially differentiated effect of regional socioeconomic factors on energy consumption.

Source apportionment to support air quality planning: Strengths and weaknesses of existing approaches

Information on the origin of pollution constitutes an essential step of air quality management as it helps identifying measures to control air pollution. In this work, we review the most widely used source-apportionment methods for air quality management. Using theoretical and real-case datasets we study the differences among these methods and explain why they result in very different conclusions to support air quality planning. These differences are a consequence of the intrinsic assumptions that underpin the different methodologies and determine/limit their range of applicability. We show that ignoring their underlying assumptions is a risk for efficient/successful air quality management as these methods are sometimes used beyond their scope and range of applicability. The simplest approach based on increments (incremental approach) is often not suitable to support air quality planning. Contributions obtained through mass-transfer methods (receptor models or tagging approaches built in air quality models) are appropriate to support planning but only for specific pollutants. Impacts obtained via "brute-force" methods are the best suited but it is important to assess carefully their application range to make sure they reproduce correctly the prevailing chemical regimes.

Analysis of the Air Quality and the Effect of Governance Policies in China’s Pearl River Delta, 2015–2018

The evaluation of China’s air pollution and the effectiveness of its governance policies is currently a topic of general concern in the academic community. We have improved the traditional evaluation method to construct a comprehensive air quality assessment model based on China’s major air pollutants. Using the daily air pollutant data of 2015–2018, we calculated and analyzed the monthly air quality of nine cities in the Pearl River Delta of China, and conducted a comparative study on the effect of the air pollution control policies of the cities in the Pearl River Delta. We found that the air quality control policies in those nine cities were not consistent. Specifically, the pollution control policies of Guangzhou and Foshan have achieved more than 20% improvement. The pollution control policies of Dongguan and Zhaoqing have also achieved more than 10% improvement. However, due to the relative lag of the formulation and implementation of air pollution control policies, the air quality of Jiangmen, Zhuhai and Zhongshan has declined. Based on the analysis of the air quality assessment results and the effects of governance policies in each city during the study period, we propose suggestions for further improvement of the effectiveness of air pollution control policies in the region.

Differences in concentration and source apportionment of PM2.5 between 2006 and 2015 over the PRD region in southern China

During China's 11th Five Year Plan (FYP) and 12th FYP (2006-2015), a series of air pollution control measures was implemented in the Pearl River Delta (PRD) region. Therefore, it is vital to determine how the concentration and sources of fine particulate matter (PM_2.5) in this region changed between 2006 and 2015. In this work, using 2006 and 2015 emission inventories, the concentration and source apportionment of PM_2.5 were simulated using the Weather Research and Forecast - Comprehensive Air Quality Model with Extensions (WRF-CAMx) for January, April, July and October in the PRD region. The PM_2.5 in 10 cities and the contributions made by sources in six major categories were tracked using the Particulate Source Apportionment Technology (PSAT) module. The results showed that the PM_2.5 concentration was lower across the entire PRD region in the 2015 emission scenario than in the 2006 scenario, and that the degree of this reduction exceeded 40 μg/m³ in some places. The PM_2.5 contributed by mobile emissions decreased the most, especially in Guangzhou, Foshan and Shenzhen, where mobile contributions decreased from 15.0, 17.9 and 13.0 μg/m³ in 2006 to 2.6, 3.1 and 4.1 μg/m³ in 2015, respectively. The PM_2.5 contributed by power plants also decreased, and in Dongguan and Guangzhou, the extent of this reduction reached 2.5 and 3.4 μg/m³ respectively. However, due to an increase in industrial production and population size, the PM_2.5 from industrial point sources and area sources also increased between 2006 and 2015 in some of the cities. Investigation of the source apportionment for city centers yielded similar results. In addition to emissions within the PRD region, outside-PRD non-local contribution is still an important PM_2.5 contributor. Hence, more stringent policies for controlling industrial and area sources and deepening province-to-province cooperation are urgently needed as the next step in PM_2.5 control.

A Full-Coverage Daily Average PM2.5 Retrieval Method with Two-Stage IVW Fused MODIS C6 AOD and Two-Stage GAM Model

Current PM2.5 retrieval maps have many missing values, which seriously hinders their performance in real applications. This paper presents a framework to map full-coverage daily average PM2.5 concentrations from MODIS C6 aerosol optical depth (AOD) products and fill missing pixels in both the AOD and PM2.5 maps. First, a two-stage inversed variance weights (IVW) algorithm was adopted to fuse the MODIS C6 Terra and Aqua AOD products, which fills missing data in MODIS standard AOD data and obtains a high coverage daily average. After that, using the fused MODIS daily average AOD and ground-level PM2.5 in all grid cells, a two-stage generalized additive model (GAM) was implemented to obtain the full-coverage PM2.5 concentrations. Experiments on the Yangtze River Delta (YRD) in 2013–2016 were carefully designed to validate the performance of our proposed framework. The results show that the two-stage IVW could not only improve the spatial coverage of MODIS AOD against the original standard product by 230%, but could also keep its data accuracy. When compared with the ground-level measurements, the two-stage GAM can obtain accurate PM2.5 concentration estimates (R2 = 0.78, RMSE = 19.177 μg/m3, and RPE = 28.9%). Moreover, our method performs better than the inverse distance weighted method and kriging methods in mapping full-coverage daily PM2.5 concentrations. Therefore, the proposed framework provides a good methodology for retrieving full-coverage daily average PM2.5 concentrations from MODIS standard AOD products.

Integrated system for population dose calculation and decision making on protection measures in case of an accident with air emissions in a nuclear power plant

The accidents in Chernobyl and Fukushima remind us that nuclear power plants should continuously invest resources in improving safety and in risk management. This paper presents the methodology for developing a measuring and modelling system with a high degree of automation, which enables predicting the effects of the spreading of radionuclides from the nuclear power plant to the atmosphere. The end result is the calculated population doses in the event of an accidental release, which is an essential piece of information needed by first responders to take proper action. The key challenge addressed by this methodology is how to build a system so that its operation is maximally automated, ongoing and in real time. Moreover, in a way that "fresh", normalized results for the hypothetically most probable types of emissions are always available to operators. The principle that normalized, fresh results are always automatically available to operators is the only real assurance that they will almost surely be available in the event of an accident and panic. This way, we can avoid performing complex model calculations at the operator's request when the accident is already taking place. The methodology divides the building of the system into key modules, which are substantiated and described. The theoretical section is followed by a description of implementation on the example of the Measuring and Modelling System at the Krško Nuclear Power Plant (in Slovenia). The system has been tested in regular nuclear emergency exercises and rated excellent by IAEA inspections; it has been operating automatically, continuously and in real time for many years. The availability of automatic results is counted for the last two years. Measurements and diagnostic modelling results were available for more than 96% and forecasts were available in more than 91% of all half-hour intervals.

Application of air parcel residence time analysis for air pollution prevention and control policy in the Pearl River Delta region

In this study, the concept of air parcel residence time was raised and the APRT was investigated to study its potential application in air pollution prevention and control in the Pearl River Delta (PRD) region. The APRT in the PRD region was defined as the total period for which an air parcel stays within the PRD region. The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used to calculate the hourly APRT in 2012, 2014, and 2015 based on forward trajectories from 16,720 starting locations. The seasonal APRT results revealed that long APRT was mainly distributed in southern PRD in the summer half year, but in northeastern PRD in the winter half year. This is related to the prevailing wind directions in the summer and winter monsoons. Moreover, the comparison of APRT in different years revealed that the dispersion condition was relatively poor in fall in 2012 and throughout 2014 but was relatively favorable in 2015, which also corresponded to the pollutant concentrations. The APRT calculated from regional air pollution days indicated that the emission reduction strategy should be implemented in the key areas, namely the eastern and central Guangzhou, western Huizou, and the border between Foshan and Jiangmen, and the construction of new factories should not be allowed in these areas. Compared to the APRT, which was investigated to trace the air pollution source, population exposure to air parcels (PEAP) was investigated to orient the influence of path-and-time-weighted sources to population. Consequently, a high PEAP was found to be distributed mainly in the central Guangzhou and Shenzhen and scattered in other urban areas.

Spatiotemporal patterns of recent PM2.5 concentrations over typical urban agglomerations in China

China experiences severe particulate matter pollution associated with rapid economic growth and accelerated urbanization. In this study, concentrations of PM_2.5 (fine particulate matter with an aerodynamic diameter ≤ 2.5 μm) throughout China, and specifically in nine typical urban agglomerations and one economic region, were statistically analyzed using high-resolution ground-based PM_2.5 observations from June 2014 to May 2018. The spatial variation of PM_2.5 was also explored via spatial autocorrelation analysis. High annual mean PM_2.5 concentrations were predominantly concentrated in the Beijing-Tianjin-Hebei, Central Plain, Northern Slope of Tianshan Mountain, and Cheng-Yu urban agglomerations, as well as the Huaihai Economic Region. The proportion of air quality nationwide monitoring sites where annual average PM_2.5 concentrations exceeded the Chinese Ambient Air Quality Standards (CAAQS) Grade II annual standard were 82.8%, 77.1%, and 70.8% in 2015, 2016, and 2017, respectively. Moreover, the frequency of PM_2.5 concentrations meeting the CAAQS Grade I 24-h standard increased in five national-level urban agglomerations, and the average annual PM_2.5 decreased from 2015 to 2017 with a reduction rate of over 20%. The southern Beijing-Tianjin-Hebei agglomeration and surrounding areas revealed the highest PM_2.5 pollution in four seasons. Monthly mean PM_2.5 typically exhibited a characteristic "U" shape. Diurnal mean PM_2.5 concentrations were generally consistent with typical urban agglomerations, with maximum and minimum PM_2.5 values occurring at approximately 08:00-12:00 and 15:00-17:00, respectively, except for the Northern Slope of Tianshan Mountain urban agglomeration (NSTM-UA) (14:00 and 08:00, respectively). A positive spatial autocorrelation of PM_2.5 concentrations was observed in all urban agglomerations (except NSTM-UA); high-high agglomeration centers of PM_2.5 pollution were located far inland with a circular distribution, and low-low agglomeration centers formed at the periphery of the high-high agglomeration region. This study is key for understanding the difference in PM_2.5 concentrations among urban agglomerations and region-oriented air pollution control strategies are highly suggested.