估算美国和加拿大减少空气污染排放的基于模型的边际社会效益。
Estimating Model-Based Marginal Societal Health Benefits of Air Pollution Emission Reductions in the United States and Canada.
机构信息
Carleton University, Ottawa, Ontario, Canada.
Georgia Institute of Technology, Atlanta, Georgia, USA.
出版信息
Res Rep Health Eff Inst. 2024 Aug;2024(218):1-63.
We developed spatially detailed source-impact estimates of population health burden measures of air pollution for the United States and Canada by quantifying sources-receptor relationships using the benefit-per-ton (BPT) metric. We calculated BPTs as the valuations of premature mortality counts due to fine particulate matter (PM; particulate matter ≤2.5 μm in aerodynamic diameter) exposure resulting from emissions of one ton of a given pollutant. Our BPT estimates, while accounting for a large portion of societal impact, do not include morbidity, acute exposure mortality, or chronic exposure mortality due to exposure to other pollutants such as ozone. The adjoint version of a widely used chemical transport model (CTM) allowed us to calculate location-specific BPTs at a high level of granularity for source-impact characterization. Location-specific BPTs provides a means for exploiting the disparities in source impact of emissions at different locations. For instance, estimated BPTs show that 20% of primary PM and ammonia emissions in the United States account for approximately 50% and 60% of the burden of each species, respectively, for an estimated burden of $370B USD. Similarly, 10% of the most harmful emissions of primary PM and ammonia emissions in Canada account for approximately 60% and 50% of their burden, respectively. By delineating differences and disparities in source impacts, adjoint-based BPT provides a direct means for prioritizing and targeting emissions that are most damaging. Sensitivity analyses evaluated the impact of our assumptions and study design on the estimated BPTs. The choice of concentration-response function had a substantial impact on the estimated BPTs and is likely to constitute the largest source of uncertainty in those estimates. Our method for constructing annual BPT estimates based on episodic simulations introduces low uncertainty, while uncertainties associated with the spatial resolution of the CTM were evaluated to be of medium importance. Finally, while recognizing that the use of BPTs entails an implied assumption of linearity, we show that BPTs for primary PM emissions are stable across different emission levels in North America. While BPTs for precursors of secondary inorganic aerosols showed sensitivity to emission levels in the past, we found that those have stabilized with lower emissions and pollutant concentrations in the North American atmosphere. We used BPTs to provide location-specific and sectoral estimates for the cobenefits of reducing carbon dioxide emissions from a range of combustion sources. Cobenefit estimates rely heavily on the emission characteristics of the sector and therefore exhibit more pronounced sectoral fingerprints than do BPTs. We provide cobenefit estimates for various subsectors of on-road transportation, thermal electricity generation, and off-road engines. Off-road engines and various heavy-duty diesel vehicles had the largest cobenefits, which in most urban locations far exceeded estimates of the social cost of carbon. Based on our cobenefit estimations, we also provide per-vehicle burden estimates for different vintages of vehicle subsectors such as transit buses and short-haul trucks in major US cities.
我们通过使用效益每吨(BPT)指标量化源-受体关系,为美国和加拿大开发了空气污染人口健康负担措施的空间详细源影响估计。我们将 BPT 计算为由于特定污染物排放一吨而导致细颗粒物(PM;空气动力学直径≤2.5μm 的颗粒物)暴露导致的过早死亡人数的估值。我们的 BPT 估计值虽然考虑了很大一部分社会影响,但不包括由于暴露于臭氧等其他污染物而导致的发病率、急性暴露死亡率或慢性暴露死亡率。广泛使用的化学传输模型(CTM)的伴随版本使我们能够以高粒度水平计算源影响的位置特定 BPT,以进行源影响特征描述。位置特定的 BPT 提供了一种利用不同位置排放源影响差异的方法。例如,估计的 BPT 表明,美国 20%的主要 PM 和氨排放分别占每种物种负担的约 50%和 60%,估计负担为 3700 亿美元。同样,加拿大 10%的主要 PM 和氨排放中最有害的排放物分别占其负担的约 60%和 50%。通过划定源影响的差异和差异,基于伴随的 BPT 提供了一种直接的方法来优先考虑和针对最具破坏性的排放物。敏感性分析评估了我们的假设和研究设计对估计 BPT 的影响。浓度-反应函数的选择对估计的 BPT 有重大影响,并且很可能是这些估计中最大的不确定性来源。我们基于 episodic 模拟构建年度 BPT 估计的方法引入了低不确定性,同时评估了与 CTM 空间分辨率相关的不确定性,认为其具有中等重要性。最后,尽管认识到使用 BPT 涉及线性假设,但我们表明,北美的主要 PM 排放的 BPT 是稳定的,与不同的排放水平无关。虽然二次无机气溶胶前体的 BPT 对过去的排放水平敏感,但我们发现,随着北美大气中排放和污染物浓度的降低,这些 BPT 已经稳定下来。我们使用 BPT 为一系列燃烧源减少二氧化碳排放的共同效益提供了特定地点和部门的估计。共同效益估计主要依赖于部门的排放特征,因此比 BPT 更明显地具有部门特征。我们提供了道路交通、热力发电和非道路发动机等各个子部门的共同效益估计。非道路发动机和各种重型柴油车的共同效益最大,在大多数城市地区,这些效益远远超过了社会碳成本的估计。基于我们的共同效益估计,我们还为美国主要城市的不同车辆子部门(如过境巴士和短途卡车)的不同车型提供了每辆车的负担估计。