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Spatial variation of secondary inorganic PM_(2 5) exposure: from exposure magnitude to exposure distance

机译:二级无机PM_(2 5)曝光的空间变化:从曝光幅度到曝光距离

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Secondary PM_(2.5) exposure, particles formed from precursor emissions, is currently poorly characterized. We estimate secondary PM_(2.5) exposure and exposure travel distances due to precursors such as NH_3, NOx, and SO_2 and evaluate the respective spatial variability within the US. We characterize PM_(2.5) exposure due to NH_3, NOx, and SO_2 using intake fractions (iF), the fraction of PM_(2.5) inhaled by population from a unitary precursor emission. We use a source-receptor (S-R) matrix approach based on the InMAP (Intervention Model for Air Pollution), a reduced-complexity air pollution model, to characterize exposure from ground level emissions in >40,000 source locations in the US. To investigate exposure travel distance we estimate intake travel distance of x (ITDx), distance from the source at which we reach x% of total cumulative iF, for each source. Results indicate substantial spatial variability for PM_(2.5) exposure due to NH_3 emissions in the US. Estimates of iF_(PM2.5,NH3) range between 0.01 and 41.5 ppm. Sources locations in close proximity to big cities (e.g. NY, LA) result in the highest PM_(2.5) exposure from NH_3 emissions. Similar trends are observed for SO_2 and NOx emissions, with iF(PM2.5,SO2) and iF(PM2.5,NOx) estimates spanning between 0.009-3.0 ppm and 0.002-1.3 ppm, respectively. Our analysis produced higher secondary iF(PM2.5,NH3) estimates with higher variability compared to published estimates. In addition, our analysis suggest that exposure radius is precursor dependent with NH3 having on average the shortest (ITD_(50,NH3)=70 km, 95% Cl: 0-450) and SO_2 having on average the largest (ITD_(50,SO2)=200 km, 95% Cl: 0-740) travel distance. Our results improve the exposure characterization of secondary PM_(2.5), especially from NH_3 emissions. This S-R exposure assessment approach enables us to calculate sector specific (e.g. agriculture, electricity production) average iF at local, regional or nation level that can be used in alternative chemical assessment or life cycle assessment.
机译:次级PM_(2.5)曝光,由前体排放形成的颗粒,目前表征差。我们估计次级PM_(2.5)曝光和暴露行驶距离,如NH_3,NOX和SO_2,并评估美国内部的相应空间变异性。我们使用进气级分(IF)的NH_3,NOx和SO_2引起PM_(2.5)曝光,从单一前体发射中吸入PM_(2.5)的分数。我们使用基于Inmap(空气污染的干预模型)的源 - 受体(S-R)矩阵方法,减少复杂性空气污染模型,以在美国> 40,000个源地点的地面排放中表征曝光。为了调查曝光行程距离,我们估计X(ITDX)的进气行进距离,距离源的距离,我们达到每个来源的X%。结果表示由于美国NH_3排放因NH_3排放而导致PM_(2.5)曝光的大量空间变异性。 IF_(PM2.5,NH3)的估计值0.01和41.5 ppm。靠近大城市(例如,纽约,LA)的源位置导致NH_3排放的最高PM_(2.5)曝光。对于SO_2和NOx排放观察到类似的趋势,如果(PM2.5,SO2)和IF(PM2.5,NOx)分别估计分别在0.009-3.0ppm和0.002-1.3ppm之间。与已发布估计数相比,我们的分析产生了更高的次要IF(PM2.5,NH3)估算,具有更高的可变性。此外,我们的分析表明,暴露半径是依赖于NH3的前兆,平均最短(ITD_(50,NH3)= 70km,95%CL:0-450)和SO_2平均最大(ITD_(50, SO2)= 200公里,95%CL:0-740)旅行距离。我们的结果改善了次级PM_(2.5)的曝光表征,尤其是NH_3排放。该S-R暴露评估方法使我们能够计算可用于替代化学评估或生命周期评估的地方,区域或国家/地区的特定(例如农业,电力生产)平均水平。

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