当前位置: X-MOL 学术Environ. Sci. Technol. › 论文详情
Ultrafine Particle Number Concentration Model for Estimating Retrospective and Prospective Long-Term Ambient Exposures in Urban Neighborhoods.
Environmental Science & Technology ( IF 7.864 ) Pub Date : 2020-01-24 , DOI: 10.1021/acs.est.9b03369
Matthew C Simon,Elena N Naumova,Jonathan I Levy,Doug Brugge,John L Durant

Short-term exposure to ultrafine particles (UFP; <100 nm in diameter), which are present at high concentrations near busy roadways, is associated with markers of cardiovascular and respiratory disease risk. To date, few long-term studies (months to years) have been conducted due to the challenges of long-term exposure assignment. To address this, we modified hybrid land-use regression models of particle number concentrations (PNCs; a proxy for UFP) for two study areas in Boston (MA) by replacing the measured PNC term with an hourly model and adjusting for overprediction. The hourly PNC models used covariates for meteorology, traffic, and sulfur dioxide concentrations (a marker of secondary particle formation). We compared model performance against long-term PNC data collected continuously from 9 years before and up to 3 years after the model-development period. Model predictions captured the major temporal variations in the data and model performance remained relatively stable retrospectively and prospectively. The Pearson correlation of modeled versus measured hourly log-transformed PNC at a long-term monitoring site for 9 years prior was 0.74. Our results demonstrate that highly resolved spatial-temporal PNC models are capable of estimating ambient concentrations retrospectively and prospectively with generally good accuracy, giving us confidence in using these models in epidemiological studies.
更新日期:2020-01-24

 

全部期刊列表>>
施普林格自然
欢迎访问IOP中国网站
GIANT
自然职场线上招聘会
ACS ES&T Engineering
ACS ES&T Water
屿渡论文,编辑服务
何川
苏昭铭
陈刚
姜涛
李闯创
北大
刘立明
隐藏1h前已浏览文章
课题组网站
新版X-MOL期刊搜索和高级搜索功能介绍
ACS材料视界
天合科研
x-mol收录
上海纽约大学
曾林
天津大学
何振宇
史大永
吉林大学
卓春祥
张昊
杨中悦
试剂库存
down
wechat
bug