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Air quality is often assessed using particulate matter (PM) mass concentration without considering its toxicity, thus possibly leading to improper control policies or inadequate health protection. Here, we studied differences in oxidative potentials (OPs) of PM samples collected using automobile air conditioning (AC) filters from 19 global cities, as well as influences from microbial contents. Dithiothreitol (DTT) assay showed remarkable differences in the PM OPs among cities (p -values ≤ 0.001, Kruskal-Wallis test). For example, the normalized index of oxidant generation (NIOG) of PM samples in San Francisco (2.20 × 10−2, annual average PM 10 = 16 μg/m3) was found to be twice that in Beijing (1.14 × 10−2, annual average PM 10 = 135 μg/m3). Limulus amebocyte lysate (LAL) assay found that PM-borne endotoxin ranged from 12.16 EU/mg (Florianopolis, Brazil) to 2518.23 EU/mg (Chennai, India) among cities. Besides, culturing method and real-time qPCR revealed significant differences of up to ∼100-fold in both bacterial and fungal levels among 19 cities. Spearman's correlation analysis implied that PM-borne microbes such as bacteria and fungi as well as metals could strongly influence the PM OP. As an example, our results in Xi'an, China further suggest that the PM 2.5 OP evolves for a particular city over the time, which is attributable to both the urbanization and air pollution control measures. This work highlights the importance in optimizing the current air quality control measures by considering the toxicity factor and its microbial constituents. Image 1 • Ambient PM toxicity per unit of mass was shown to vary greatly with different cities across the world. • PM-borne biologicals were shown to exhibit remarkable differences across major cities, contributing to the difference of PM toxicity. • PM toxicity was shown to evolve over the time as a result of ground human activities as well as air pollution control measures. • This work highlights the need of taking into account of PM toxicity for future air pollution control efforts. [ABSTRACT FROM AUTHOR]

The Chinese government aims to mitigate climate change while also reducing local air pollution; this requires co-control of greenhouse gases and pollutants. Here, we develop a method combining an elasticity analysis and a multi-regional input–output model, to measure changes in the emissions of greenhouse gases and pollutants and corresponding socio-economic costs caused by the adjustments in intermediate input, inter-regional trade, and final demand transactions for 30 provinces in China. A filter framework is proposed to identify the key structural transactions that can significantly co-control both emission types with small socio-economic impacts. The results show that 13 effective co-control spots can simultaneously reduce greenhouse gases and pollutants. Among these, eight co-controls are associated with low economic costs, which we refer to as 'sweet spots'. Sweet spots cover agricultural inputs in the food and tobacco sectors of Inner Mongolia, Sichuan, Liaoning, and Hubei; self-inputs in the agriculture of Henan; self-inputs in the food and tobacco sector of Shandong; fixed capital formation of agriculture in Hebei; and urban household consumption of agricultural products in Guangdong. This finding is important, as climate measures mostly side-line the agricultural sector so far, both in China and in other parts of the world. • Structural adjustments could co-control multi-emissions with small economic impacts. • Thirteen effective co-control spots can simultaneously reduce GHGs and pollutants. • Of these, eight co-controls are associated with low economic costs (sweet spots). • Most sweet spots are related to agricultural goods and mostly reduce non-CO 2 GHGs. • All sweet spots have the strongest effect on NH 3 emission, followed by PM 2.5. [ABSTRACT FROM AUTHOR]

Satellite sensors can provide unique views of global pollution information from space. In particular, a series of aerosol and trace gas monitoring instruments have been operating for more than a decade, providing the opportunity to analyze temporal trends of major pollutants on a large scale. In this study, we integrate aerosol products from MODIS (MODIS Resolution Imaging Spectroradiometer, all abbreviations and their definitions are listed alphabetically in Abbreviations) and MISR (Multi-angle Imaging Spectroradiometer), the AAI (Absorbing Aerosol Index) product from OMI (Ozone Monitoring Instrument), column SO2 and NO2 concentrations from OMI, and tropospheric column ozone concentration from OMI/MLS (Microwave Limb Sounder) to study temporal changes in major pollutants over China. MODIS and MISR consistently revealed that column AOD (Aerosol Optical Depth) increased from 2000, peaked around 2007, and started to decline afterward, except for northwest and northeast China, where a continuous upward trend was found. Extensive negative trends in both SO2 and NO2 have also been found over major pollution source regions since ~2005. On the other hand, the OMI AAI exhibited significant increases over north China, especially the northeast and northwest regions. These places also have a decreased Angstrom exponent as revealed by MISR, indicating an increased fraction of large particles. In general, summer had the largest AOD, SO2, and NO2 trends, whereas AAI trends were strongest for autumn and winter. A multi-regression analysis showed that much of the AOD variance over major pollution source regions could be explained by SO2, NO2, and AAI combined, and that the SO2 and NO2 reduction was likely to be responsible for the negative AOD trends, while the AOD increase over NE and NW China may be associated with an increase of coarse particles revealed by increased AAI and decreased AE. In contrast to aerosols, tropospheric ozone exhibited a steady increase from 2005 throughout China. This indicates that although the recent emission control effectively reduced aerosol pollutants, ozone remains a challenging issue and may dominate future air pollution. [ABSTRACT FROM AUTHOR]

In this study, an IBSOM (inexact bi-level simulation–optimization model) is developed for conjunctive regional renewable energy planning and air pollution control for EPS (electric power systems) under uncertainty. The IBSOM integrates techniques of CFMTVW (combined forecasting model with time-varying weights), ILP (interval linear programming), MIP (mixed integer programming), CCP (chance-constrained programming), as well as BLP (bi-level programming) into a general framework. In the IBSOM, uncertainties expressed as interval and stochastic parameters within multi-period and multi-option contexts can be effectively tackled. In addition, a leader-follower decision strategy is incorporated into the optimization process where two non-competitive objectives are sequentially proposed, with the environmental sector dominating the upper-level objective (leader’s one) and the energy sector providing the lower-level objective (follower’s one). To solve the proposed model, an improved bi-level interactive solution algorithm based on satisfactory degree is introduced into the decision-making process for balancing to what extent the constraints are met and the objective reaches its optima. Then, the IBSOM is applied to a real-world case study of EPS in Fengtai District, Beijing, China. Interval solutions associated with renewable energy development, electricity generation, facility-expansion scheme, as well as pollutants mitigation can be obtained under different system-violation risk. Results indicate that a higher violation risk would lead to a decreased strictness of the constraints or an expanded decision space, which results in the decreased system cost and pollutant emissions, but increases system risk. Conversely, a lower violation risk would correspond to a lower probability of system–constraint violation, then to higher system cost and more pollutant emissions, but the risk of violating the constraints would be decreased. These variations can enable Stakeholders to coordinate the conflict interactions among system cost, pollutants mitigation, and system-violation risk under multiple uncertainties. Moreover, the performance of the IBSOM is enhanced by comparing with single-level models. Results demonstrate that the IBSOM can promote much more mutual influences and restrictions between the twofold decision makers. [ABSTRACT FROM AUTHOR]

It is critical to explore intervenable environmental factors in suicide mortality. Based on 30,688 suicide cases obtained from the Mortality Surveillance System of the Jiangsu Provincial Centre for Disease Control and Prevention, we utilized a case-crossover design, and found that the OR of suicide deaths increased by a maximum of 0.71 % (95 % CI: 0.09 %, 1.32 %), 0.68 % (95 % CI: 0.12 %, 1.25 %), 0.77 % (95 % CI: 0.19 %, 1.37 %), 2.95 % (95 % CI: 1.62 %, 4.29 %), 4.18 % (95 % CI: 1.55 %, 6.88 %), and 0.93 % (95 % CI: 0.10 %, 1.77 %), respectively, for per 10 μg/m3 increase in the particulate matter (PM) with diameters ≤ 2.5 µm (PM 2.5), PM with diameters ≤ 10 µm (PM 10), ozone (O 3), nitrogen dioxide (NO 2), sulfur dioxide (SO 2), and per 0.1 mg/m3 increase in carbon monoxide (CO) concentrations with the conditional logistic regression analysis. People living in county-level cities were more susceptible. Particularly, a significant positive association was found between air pollutant mixture exposure and suicide deaths (OR=1.04,95 % CI: 1.01, 1.06). The excess fraction of suicide deaths due to air pollution reached a maximum of 8.07 %. In conclusion, we found associations between individual and mixed ambient air pollutants and suicide deaths, informing the development of integrated air pollution management and targeted measures for suicide prevention and intervention. As a major contributor to the global burden of disease, air pollution was confirmed by accumulating studies to have adverse impact on mental health, and potentially lead to suicide deaths. However, systematic studies on the association between air pollution and suicide mortality are lacking. We explored the associations of multiple air pollutants and pollution mixtures with suicide deaths and assessed excess suicide mortality due to air pollution, emphasizing the importance of air pollution control on suicide prevention. Our study provides evidence to support mechanistic studies on the association between air pollution and suicide, and informs comprehensive air pollution management. [Display omitted] • Short-term exposure to air pollution was associated with suicide deaths. • People living in county-level cities were more susceptible. • Short-term exposure to air pollution mixture was associated with suicide deaths. • Air pollution may cause up to 8.07 % of excess suicide mortality. [ABSTRACT FROM AUTHOR]

Biomass burning (BB) seriously affect air pollution, human health and global climate. A severe pollution episode (PE) caused by BB was investigated in the southern Sichuan Basin (SSB), one of the most polluted areas in China. Hourly variations in criteria air pollutants (PM 2.5 , PM 10 , SO 2 , NO 2 , CO, and O 3), chemical components, and sources of PM 2.5 before, during, and after the severe regional air PE were characterized at three sites, namely Neijiang (NJ), Zigong (ZG), and Yibin (YB). The results showed that combination of intensive pollution from BB, stable meteorological conditions, and the basin topography caused this severe regional PE in the SSB. The average daily concentrations of PM 2.5 during the PE were 1.8–6 times those measured during the periods before and after the PE, and 4.0–7.4 times that of World Health Organization air quality guidelines in the SSB. The highest PM levels occurred in ZG, where the peak values of PM 2.5 and PM 10 reached 536 μg m−3 and 578 μg m−3 at night, respectively. PM 10 , NO 2 , and CO also increased dramatically at night in the SSB. O 3 formation was affected by BB, showing lower levels at night but higher levels in the day during the PE than before and after the PE, whereas SO 2 levels were not affected. Sulfate–nitrate–ammonium in PM 2.5 was the main chemical compositions before the PE, whereas organic matter (OM) and K+ became characteristics compositions during and after the PE. Higher OC/EC and K excess /EC ratios were observed during the PE and K excess /EC ratio was a better indicator of BB in the SSB than OC/EC ratio. The results of a positive matrix factorization model indicated that BB was the most significant contributor to PM 2.5 during the PE, accounting for 58% in NJ, 65% in ZG, and 56% in YB. Backward trajectory analysis confirmed that the SSB is susceptible to pollutants from Chongqing and other surrounding cities, especially in ZG and NJ, due to the unique topography of the basin. Our findings suggest that BB in the basin topography can cause severe regional air pollution events at night, thus supporting the critical need for BB control in the basin to improve regional air quality. Image 1 • The evolution of region air pollution event caused by biomass burning was observed. • PM 2.5 , PM 10 , NO 2 , and CO increased dramatically during the pollution episode. • O 3 formation was influenced by biomass burning. • Chemical components and sources variations of PM 2.5 were investigated. • The southern Sichuan Basin was susceptible to air masses from Chongqing. [ABSTRACT FROM AUTHOR]

Evaluating the efficacy of air pollution control policies is an essential part of the decision-making process to develop new policies and improve existing measures. Since 2005, Fujian Province of Mainland China and Taiwan across the Taiwan Strait have both implemented aggressive air pollution control policies designed based on different principles, but a comprehensive evaluation of these control policies on PM 2.5 pollution levels is still lacking. In the current study, we assessed the effects of these policies in the Taiwan Strait Region from 2005 to 2018 using full-coverage, high-resolution PM 2.5 generated by a satellite-driven machine learning model. A ten-fold cross-validation for our prediction model showed an R 2 value of 0.89, demonstrating that these predictions can be used for policy evaluation. During the 14-year period, PM 2.5 levels in all areas of Fujian and Taiwan underwent a significant decrease. Separate regression models for policy evaluation in Taiwan and Fujian showed that all considered policies have mitigated PM 2.5 pollution to various degrees. The Clean Air Action Plans (CAAP) is the most effective control policy in Taiwan, while the Action Plan of Air Pollution Prevention and Control (APPC-AP) and Three-year Action Plan for Blue Skies (3YAP-BS) as well as their provincial implementation plans are the most successful in Fujian. The effectiveness of control policies, however, varies by land-use types especially for Taiwan. • PM 2.5 levels were estimated in the Taiwan Strait Region at 1-km resolution from 2005 to 2018 • The most effective control policies to lower PM 2.5 levels in Taiwan and Fujian were analyzed • The effectiveness of control policies varies by land use type in Taiwan [ABSTRACT FROM AUTHOR]