大气污染协同治理能促进污染物减排吗?--基于城市的三重差分研究

大气污染具有流动性,跨区域特征明显,协同治理至关重要。基于2010-2015年275个城市的面板数据,运用三重差分法(DDD)研究了大气污染协同治理对污染物减排的影响。从全样本分析结果来看,大气污染协同治理降低了工业二氧化硫排放量和工业烟(粉)尘排放量,而此结果并没有通过显著性检验。从子样本分析结果来看,大气污染协同治理显著降低了工业二氧化硫排放量,但对工业烟(粉)尘排放量没有产生显著影响。城市在促进不同污染物减排时存在差异,减排难度较低的污染物往往被优先完成。从时间效应来看,大气污染协同治理对污染物减排的影响存在时滞性,而且这种时滞性在不同污染物减排之间存在差异。     

Health Risks of Energy Systems

Health risks from fossil, renewable and nuclear reference energy systems are estimated following a detailed impact pathway approach. Using a set of appropriate air quality models and exposure-effect functions derived from the recent epidemiological literature, a methodological framework for risk assessment has been established and consistently applied across the different energy systems, including the analysis of consequences from a major nuclear accident. A wide range of health impacts resulting from increased air pollution and ionizing radiation is quantified, and the transferability of results derived from specific power plants to a more general context is discussed.     

空气污染对重污染公司股票价格的影响:基于政策干预视角的经济价值研究

随着经济发展和产业结构调整，社会公众和政府部门对空气污染问题的原因和治理给予了更多关注。空气重污染公司聚焦度陡增，在经营业绩、发展前景和股市表现方面受到不同程度的冲击。本文利用2014—2019年全国地级市层面空气重污染公司的日度非平衡面板数据，研究政策干预视角下空气污染对股票交易的影响及其经济价值。相较人体弹性感知能力，以空气质量等级变化为触发条件的地方政府防治措施能够更精准地对空气污染做出反应，进而通过公司基本面和投资者情绪渠道影响股市交易。实证结果显示，空气质量等级恶化会对空气重污染公司的股价产生非持续性负面影响，且股价的短期下跌伴随换手率上升特点。经济意义检验表明，空气污染与股价短期关系的发现能够指导投资实践以获取经济增益，而空气质量指数具有改进股价预测的潜力。本文的研究对理解政策干预视角下空气污染对股票市场的影响、股价预测和投资组合均具有十分重要的理论和实践意义。     

Health Risks and Air Pollution — Error Analysis for a Cross-Sectional Mortality Study

An attempt is made to analyze in quantitative terms the uncertainties in multiple regression estimates of the effects of air pollution on death rates. A range of factors--statistical fluctuations in numbers of deaths, differences in local age distribution, differences in smoking habits, errors in estimated pollution levels, migration, and variability of the characterization of socioeconomic effects--are assessed as potential sources of error. Both the precision and the robustness of the regression calculation are shown to be poor. Examples and illustrative calculations are given based on a study of U. K. death rates around the 1971 Census.     

Expert Elicitation of the Value per Statistical Life in an Air Pollution Context

The monetized value of avoided premature mortality typically dominates the calculated benefits of air pollution regulations; therefore, characterization of the uncertainty surrounding these estimates is key to good policymaking. Formal expert judgment elicitation methods are one means of characterizing this uncertainty. They have been applied to characterize uncertainty in the mortality concentration‐response function, but have yet to be used to characterize uncertainty in the economic values placed on avoided mortality. We report the findings of a pilot expert judgment study for Health Canada designed to elicit quantitative probabilistic judgments of uncertainties in Value‐per‐Statistical‐Life (VSL) estimates for use in an air pollution context. The two‐stage elicitation addressed uncertainties in both a base case VSL for a reduction in mortality risk from traumatic accidents and in benefits transfer‐related adjustments to the base case for an air quality application (e.g., adjustments for age, income, and health status). Results for each expert were integrated to develop example quantitative probabilistic uncertainty distributions for VSL that could be incorporated into air quality models.     

The Risk Screening for Indoor Air Pollution Chemicals in Japan

In recent years, public health problems caused by indoor air pollution have been drawing strong public concern in Japan. After conducting extensive exposure assessment, governmental agencies have taken effective measures to solve the problem; for instance, "Guidelines for indoor air quality (IAQ)" of 13 chemicals, for example, formaldehyde, toluene, and xylene, has been established. Thousands of chemicals have been identified in the indoor environment. Priority rating of those chemicals, however, was not based on the health risk level. We developed a risk-screening scheme for indoor air pollution chemicals and analyzed the current status of the risk levels of those chemicals in Japan. We researched scientific knowledge of health hazards and exposure surveys of indoor air pollution chemicals in Japan, and classified those chemicals based on the health risk level estimated from the scheme. The risk levels of 93 chemicals were characterized and six chemicals (formaldehyde, acrolein, 1,4-dichlorobenzene, benzene, tetrachloroethylene, and benzo(a)pyrene) were classified in the highest risk category.     

Gender and Race in Beliefs about Outdoor Air Pollution

Universal need for, or reactions to, risk communications should not be assumed; potential differences across demographic groups in environmental risk beliefs, attitudes, and behaviors could affect risk levels or opportunities for risk reduction. This article reports relevant findings from a survey experiment involving 1,100 potential jurors in Philadelphia concerning public responses to outdoor air pollution and air quality information. Flynn et al. (1994) and Finucane et al. (2000) found significant differences in risk ratings for multiple hazards, and in generic risk beliefs, between white men (or a subset) and all others (white women, nonwhite men, and nonwhite women). This study examined whether white men had significantly different responses to air pollution and air pollution information. An opportunity sample of volunteers from those awaiting potential jury duty in city courts (matching census estimates for white versus nonwhite proportions, but more female than the city's adult population and more likely to have children) filled out questionnaires distributed quasi-randomly. On most measures there were no statistically significant differences among white men (N = 192), white women (N = 269), nonwhite men (N = 165), and nonwhite women (N = 272). Nonwhites overall (particularly women) reported more concern about and sensitivity to air pollution than whites, and were more concerned by (even overly sensitive to) air pollution information provided as part of the experiment. Nonwhites also were more likely (within-gender comparisons) to report being active outdoors for at least four hours a day, a measure of potential exposure to air pollution, and to report intentions to reduce such outdoor activity after reading air pollution information. Differences between men and women were less frequent than between whites and nonwhites; the most distinctive group was nonwhite women, followed by white men. Flynn et al. (1994) and Finucane et al. (2000) found a far larger proportion of significant differences, with white men as most distinctive, probably due to use of different measures, study design, and population samples. However, all three studies broadly confirm the existence of gender and race interactions in risk beliefs and attitudes (particularly for white men and nonwhite women) that deserve more attention from researchers.     

A New Air Quality Perception Scale for Global Assessment of Air Pollution Health Effects

Despite improvements in air quality in developed countries, air pollution remains a major public health issue. To fully assess the health impact, we must consider that air pollution exposure has both physical and psychological effects; this latter dimension, less documented, is more difficult to measure and subjective indicators constitute an appropriate alternative. In this context, this work presents the methodological development of a new scale to measure the perception of air quality, useful as an exposure or risk appraisal metric in public health contexts. On the basis of the responses from 2,522 subjects in eight French cities, psychometric methods are used to construct the scale from 22 items that assess risk perception (anxiety about health and quality of life) and the extent to which air pollution is a nuisance (sensorial perception and symptoms). The scale is robust, reproducible, and discriminates between subpopulations more susceptible to poor air pollution perception. The individual risk factors of poor air pollution perception are coherent with those findings in the risk perception literature. Perception of air pollution by the general public is a key issue in the development of comprehensive risk assessment studies as well as in air pollution risk management and policy. This study offers a useful new tool to measure such efforts and to help set priorities for air quality improvements in combination with air quality measurements.     

Methods for Detecting and Estimating Population Threshold Concentrations for Air Pollution–Related Mortality with Exposure Measurement Error

The association between daily fluctuations in ambient particulate matter and daily variations in nonaccidental mortality have been extensively investigated. Although it is now widely recognized that such an association exists, the form of the concentration–response model is still in question. Linear, no threshold and linear threshold models have been most commonly examined. In this paper we considered methods to detect and estimate threshold concentrations using time series data of daily mortality rates and air pollution concentrations. Because exposure is measured with error, we also considered the influence of measurement error in distinguishing between these two completing model specifications. The methods were illustrated on a 15-year daily time series of nonaccidental mortality and particulate air pollution data in Toronto, Canada. Nonparametric smoothed representations of the association between mortality and air pollution were adequate to graphically distinguish between these two forms. Weighted nonlinear regression methods for relative risk models were adequate to give nearly unbiased estimates of threshold concentrations even under conditions of extreme exposure measurement error. The uncertainty in the threshold estimates increased with the degree of exposure error. Regression models incorporating threshold concentrations could be clearly distinguished from linear relative risk models in the presence of exposure measurement error. The assumption of a linear model given that a threshold model was the correct form usually resulted in overestimates in the number of averted premature deaths, except for low threshold concentrations and large measurement error.     

Acculturation,Ethnicity, and Air Pollution Perceptions

A globalizing world increases immigration between nations, raising the question of how acculturation (or its lack) of immigrants and their descendants to host societies affects risk perceptions. A survey of Paterson, New Jersey, residents tested acculturation's associations with attitudes to air pollution and its management, and knowledge of and self‐reported behaviors concerning air pollution. Linguistic and temporal proxy measures for acculturation were independent variables along with ethnicity, plus controls for gender, age, education, and income in multivariate analyses. About one‐fifth of contrasts between non‐Hispanic whites, non‐Hispanic blacks, English‐interviewed Hispanics, and Spanish‐interviewed Hispanics were statistically significant (Bonferroni‐corrected) and of medium or higher affect size, with most featuring the Spanish‐interviewed Hispanics. Knowledge variables featured the most significant differences. Specifically, Spanish‐interviewed Hispanics reported less concern, familiarity with pollution, recognition of high pollution, and vigorous outdoor activity, and greater belief that government overregulates pollution than English‐interviewed Hispanics (and than the other two groups on most of these variables too). English‐interviewed Hispanics did not differ from non‐Hispanic whites, but did on several variables from non‐Hispanic blacks. Temporal proxies of acculturation among the foreign‐born were far less significant, but concern and familiarity with air pollution increased with time spent in the United States, while belief in overregulation and a positive trend in New Jersey pollution increased with time in the nation of origin. Implications of these acculturation and ethnicity findings for risk perception/communication research and practice are discussed.     

Estimating the Risks of Smoking, Air Pollution, and Passive Smoke on Acute Respiratory Conditions

Five years of the annual Health Interview Survey, conducted by the National Center for Health Statistics, are used to estimate the effects of air pollution, smoking, and environmental tobacco smoke on respiratory restrictions in activity for adults, and bed disability for children. After adjusting for several socioeconomic factors, the multiple regression estimates indicate that an independent and statistically significant association exists between these three forms of air pollution and respiratory morbidity. The comparative risks of these exposures are computed and the plausibility of the relative risks is examined by comparing the equivalent doses with actual measurements of exposure taken in the homes of smokers. The results indicate that: (1) smokers will have a 55-75% excess in days with respiratory conditions severe enough to cause reductions in normal activity; (2) a 1 microgram increase in fine particulate matter air pollution is associated with a 3% excess in acute respiratory disease; and (3) a pack-a-day smoker will increase respiratory restricted days for a nonsmoking spouse by 20% and increase the number of bed disability days for young children living in the household by 20%. The results also indicate that the estimates of the effects of secondhand smoking on children are improved when the mother's work status is known and incorporated into the exposure estimate.     

大气污染府际间合作治理联盟的达成与稳定——基于演化博弈分析

地方政府的大气污染治理模式主要有属地治理和合作治理模式,合作治理逐渐成为当前大气污染治理的共识。从演化博弈的视角,分析地方政府在大气污染治理中的行为演化路径与稳定策略,探究地方政府间达成并巩固合作治理联盟的因素。比较有中央约束和无中央政府约束下地方政府属地治理和合作治理四种演化博弈结果表明：在属地治理背景下,无论中央政府是否对地方政府进行约束,地方政府均倾向于“搭便车”行为,而中央政府对地方政府的约束在属地治理中面临失灵;在合作治理场景中,地方政府的稳定策略均向达成合作治理或均不治理的方向演进,但在中央政府约束下,地方政府的稳定策略能快速有效得向合作治理的方向演进。为实现大气污染的有效治理,地方政府间必须形成有效的合作治理联盟,合作收益是达成大气污染合作治理联盟的必要条件,而合作成本与中央政府约束的程度决定了合作治理联盟的稳定性。     

Validation of a Novel Air Toxic Risk Model with Air Monitoring

Three modeling systems were used to estimate human health risks from air pollution: two versions of MNRiskS (for Minnesota Risk Screening), and the USEPA National Air Toxics Assessment (NATA). MNRiskS is a unique cumulative risk modeling system used to assess risks from multiple air toxics, sources, and pathways on a local to a state‐wide scale. In addition, ambient outdoor air monitoring data were available for estimation of risks and comparison with the modeled estimates of air concentrations. Highest air concentrations and estimated risks were generally found in the Minneapolis‐St. Paul metropolitan area and lowest risks in undeveloped rural areas. Emissions from mobile and area (nonpoint) sources created greater estimated risks than emissions from point sources. Highest cancer risks were via ingestion pathway exposures to dioxins and related compounds. Diesel particles, acrolein, and formaldehyde created the highest estimated inhalation health impacts. Model‐estimated air concentrations were generally highest for NATA and lowest for the AERMOD version of MNRiskS. This validation study showed reasonable agreement between available measurements and model predictions, although results varied among pollutants, and predictions were often lower than measurements. The results increased confidence in identifying pollutants, pathways, geographic areas, sources, and receptors of potential concern, and thus provide a basis for informing pollution reduction strategies and focusing efforts on specific pollutants (diesel particles, acrolein, and formaldehyde), geographic areas (urban centers), and source categories (nonpoint sources). The results heighten concerns about risks from food chain exposures to dioxins and PAHs. Risk estimates were sensitive to variations in methodologies for treating emissions, dispersion, deposition, exposure, and toxicity.     

Integrated Uncertainty Analysis for Ambient Pollutant Health Risk Assessment: A Case Study of Ozone Mortality Risk

The U.S. Environmental Protection Agency (EPA) uses health risk assessment to help inform its decisions in setting national ambient air quality standards (NAAQS). EPA's standard approach is to make epidemiologically‐based risk estimates based on a single statistical model selected from the scientific literature, called the “core” model. The uncertainty presented for “core” risk estimates reflects only the statistical uncertainty associated with that one model's concentration‐response function parameter estimate(s). However, epidemiologically‐based risk estimates are also subject to “model uncertainty,” which is a lack of knowledge about which of many plausible model specifications and data sets best reflects the true relationship between health and ambient pollutant concentrations. In 2002, a National Academies of Sciences (NAS) committee recommended that model uncertainty be integrated into EPA's standard risk analysis approach. This article discusses how model uncertainty can be taken into account with an integrated uncertainty analysis (IUA) of health risk estimates. It provides an illustrative numerical example based on risk of premature death from respiratory mortality due to long‐term exposures to ambient ozone, which is a health risk considered in the 2015 ozone NAAQS decision. This example demonstrates that use of IUA to quantitatively incorporate key model uncertainties into risk estimates produces a substantially altered understanding of the potential public health gain of a NAAQS policy decision, and that IUA can also produce more helpful insights to guide that decision, such as evidence of decreasing incremental health gains from progressive tightening of a NAAQS.     

Intake Fraction Variability Between Air Pollution Emission Sources Inside an Urban Area

The cost‐effective mitigation of adverse health effects caused by air pollution requires information on the contribution of different emission sources to exposure. In urban areas the exposure potential of different sources may vary significantly depending on emission height, population density, and other factors. In this study, we quantified this intraurban variability by predicting intake fraction (iF) for 3,066 emission sources in Warsaw, Poland. iF describes the fraction of the pollutant that is inhaled by people in the study area. We considered the following seven pollutants: particulate matter (PM), nitrogen oxides (NO_x), sulfur dioxide (SO₂), benzo[a] pyrene (BaP), nickel (Ni), cadmium (Cd), and lead (Pb). Emissions for these pollutants were grouped into four emission source categories (Mobile, Area, High Point, and Other Point sources). The dispersion of the pollutants was predicted with the CALPUFF dispersion model using the year 2005 emission rate data and meteorological records. The resulting annual average concentrations were combined with population data to predict the contribution of each individual source to population exposure. The iFs for different pollutant‐source category combinations varied between 51 per million (PM from Mobile sources) and 0.013 per million (sulfate PM from High Point sources). The intraurban iF variability for Mobile sources primary PM emission was from 4 per million to 100 per million with the emission‐weighted iF of 44 per million. These results propose that exposure due to intraurban air pollution emissions could be decreased more effectively by specifically targeting sources with high exposure potency rather than all sources.     

Experience with urban air pollution in Paterson, New Jersey and implications for air pollution communication

Communication about air pollution can help reduce health risks, but a scattered, largely qualitative literature on air pollution beliefs, attitudes, and behaviors raises questions about its effectiveness. A telephone survey of Paterson, New Jersey (USA) residents tested four hypotheses aimed toward integrating these findings. Self-reported sheltering indoors during high pollution, the recommended strategy, was predicted by perceived air quality and self-reported "sensitivity" to air pollution. Nearly a quarter of the sample reported mandatory outdoor activity (e.g., work) that might increase their exposures, but this factor did not significantly affect self-reported sheltering. Perceptions of air quality did not correlate strongly with official monitoring data (U.S. Air Quality Index (AQI)); even people who regularly sought AQI data relied upon sensory cues to high pollution, and secondarily upon health cues. Use of sensory and health cues, definitions of what makes someone sensitive to air pollution, and (less strongly) definitions of vulnerability to air pollution varied widely. The minority aware of the AQI were more likely to seek it if they had illnesses or saw themselves in the targeted AQI audience, yet less likely if they believed themselves sensitive to pollution. However, their sense of the AQI's match to their own experience was driven by whether they used sensory (yes) or health (no) cues, not by illness status. Some urban residents might not have access to AQI data, but this barrier seems outweighed by need to bridge interpretive gaps over definitions of air pollution, sensory perception, vulnerability, and health consequences.     

The Benefits of Probabilistic Exposure Assessment: Three Case Studies Involving Contaminated Air,Water, and Soil1

Probabilistic risk assessments are enjoying increasing popularity as a tool to characterize the health hazards associated with exposure to chemicals in the environment. Because probabilistic analyses provide much more information to the risk manager than standard “point” risk estimates, this approach has generally been heralded as one which could significantly improve the conduct of health risk assessments. The primary obstacles to replacing point estimates with probabilistic techniques include a general lack of familiarity with the approach and a lack of regulatory policy and guidance. This paper discusses some of the advantages and disadvantages of the point estimate vs. probabilistic approach. Three case studies are presented which contrast and compare the results of each. The first addresses the risks associated with household exposure to volatile chemicals in tapwater. The second evaluates airborne dioxin emissions which can enter the food-chain. The third illustrates how to derive health-based cleanup levels for dioxin in soil. It is shown that, based on the results of Monte Carlo analyses of probability density functions (PDFs), the point estimate approach required by most regulatory agencies will nearly always overpredict the risk for the 95^th percentile person by a factor of up to 5. When the assessment requires consideration of 10 or more exposure variables, the point estimate approach will often predict risks representative of the 99.9^th percentile person rather than the 50^th or 95^th percentile person. This paper recommends a number of data distributions for various exposure variables that we believe are now sufficiently well understood to be used with confidence in most exposure assessments. A list of exposure variables that may require additional research before adequate data distributions can be developed are also discussed.     

城市机动车限行对PM2.5的影响与效果检验

为缓解城市道路拥堵与交通污染问题,全国多地陆续实施机动车限行政策,但针对不同城市不同限行政策对大气污染的影响却鲜有文献研究。根据政策特征,本文将限行政策分为一般限行和特殊限行两类。基于双重差分模型,采用2001-2017年我国各省会城市及直辖市的面板数据,本文分别研究了不同类型的限行政策对城市PM_2.5污染的改善作用。研究发现：首先,机动车PM_2.5排放已经成为了城市PM_2.5排放的主要来源之一,机动车限行措施也越来越多地被运用到治理城市空气污染的过程中;第二,一般限行政策和特殊限行政策均不同程度地缓解了大气污染,但相对而言,特殊限行政策的减排效果更明显;第三,限行政策的力度,如限行区域的相对大小和限制机动车的相对数量均能影响政策效果,一般来说,限行区域越大,限行的车辆越多,减排效果越显著;第四,在剔除特殊样本"北京"和"限购"政策的影响后,限行政策依然有效。本文从机动车PM_2.5排放的角度实证检验了限行政策对大气污染的影响和效果,为政府进一步制定更高效合理的道路交通污染防治措施提供了参考依据。     

Exposure-Response Functions for Health Effects of Air Pollutants Based on Epidemiological Findings

Quantitative knowledge about health damage due to air pollution is an important element in analyses of cost-effective abatement strategies, and is also essential for setting Air Quality Standards. Epidemiological studies, in spite of the numerous problems connected to them, provide a reasonable basis for exposure-response functions in this context. On the basis of a literature review, exposure-response functions that relate ambient air pollutant concentrations to the frequency of various health effects are recommended in this paper. The following end-points were examined: Acute and chronic respiratory symptoms in children and adults, crude mortality, and lung cancer incidence. The effects are attributed to one indicator component, which in most cases is particles. A calculation procedure is suggested which makes it possible to estimate excess annual symptom-days for short-term effects using the annual average concentration.