背景:低收入和中等收入国家(LMIC)受到空气污染及其健康负担的影响不成比例,代表全球不平等。COVID-19大流行为调查前所未有的封锁措施对全球空气污染物浓度的影响提供了一个独特的机会。我们的目标是量化由于COVID-19限制而导致的LMIC设置中的空气污染物浓度变化。
方法:2022年3月30日,在五个数据库中进行了系统评价和荟萃分析的搜索;MEDLINE,Embase,WebofScience,Scopus和运输研究信息文档。包括建模和观察性研究,只要这些估计反映了城市或城镇一级的数据,并且完全是在封锁前和封锁期间进行的。计算每种污染物的平均百分比变化,并进行荟萃分析以计算每种污染物的实测地面观测浓度的平均差(PROSPEROCRD42022326924)。
结果:在最初搜索的2982份手稿中,包括256份手稿,提供了所有污染物的3818百分比变化。没有研究包括撒哈拉以南非洲的任何国家,34%和39.4%的研究来自中国和印度。分别。平均百分比变化为-37.4%,-21.7%,-54.6%,-39.1%,-48.9%,16.9%,-34.9%,黑碳(BC)为-30.6%和-14.7%,一氧化碳(CO),一氧化氮(NO),二氧化氮(NO2),氮氧化物(NOx),臭氧(O3),颗粒物10(PM10)和2.5(PM2.5)和二氧化硫(SO2),分别。荟萃分析包括100份手稿,提供908个平均浓度差异,在所有研究设置中,BC的平均浓度显着降低(-0.46μg/m3,PI-0.85;-0.08),CO(-0.25mg/m3,PI-0.44;-0.03),NO2(-19.41μg/m3,PI-31.14;-7.68)和NOx(-22.32μg/m3,PI-40.94;-3.70)。
结论:本系统综述和荟萃分析的结果量化并确认了全球报告的空气污染物浓度趋势,包括O3的增加。尽管全球大部分城市增长发生在LMIC,空气污染数据存在明显的地理差距,如果有的话,不同的分析和报告方法。
BACKGROUND: Low- and middle-income countries (LMIC) are disproportionately affected by air pollution and its health burden, representing a global inequity. The COVID-19 pandemic provided a unique opportunity to investigate the impact of unprecedented lockdown measures on air pollutant concentrations globally. We aim to quantify air pollutant concentration changes across LMIC settings as a result of COVID-19 restrictions.
METHODS: Searches for this systematic
review and meta-analysis were carried out across five databases on 30th March 2022; MEDLINE, Embase, Web of Science, Scopus and Transport Research Information Documentation. Modelling and observational studies were included, as long as the estimates reflected city or town level data and were taken exclusively in pre-lockdown and lockdown periods. Mean percentage changes per pollutant were calculated and meta-analyses were carried out to calculate mean difference in measured ground-level observed concentrations for each pollutant (PROSPERO CRD42022326924).
RESULTS: Of the 2982 manuscripts from initial searches, 256 manuscripts were included providing 3818 percentage changes of all pollutants. No studies included any countries from Sub-Saharan Africa and 34 % and 39.4 % of studies were from China and India, respectively. There was a mean percentage change of -37.4 %, -21.7 %, -54.6 %, -39.1 %, -48.9 %, 16.9 %, -34.9 %, -30.6 % and - 14.7 % for black carbon (BC), carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), oxides of nitrogen (NOx), ozone (O3), particulate matter 10 (PM10) and 2.5 (PM2.5) and sulphur dioxide (SO2), respectively. Meta-analysis included 100 manuscripts, providing 908 mean concentration differences, which showed significant reduction in mean concentration in all study settings for BC (-0.46 μg/m3, PI -0.85; -0.08), CO (-0.25 mg/m3, PI -0.44; -0.03), NO2 (-19.41 μg/m3, PI -31.14; -7.68) and NOx (-22.32 μg/m3, PI -40.94; -3.70).
CONCLUSIONS: The findings of this systematic
review and meta-analysis quantify and confirm the trends reported across the globe in air pollutant concentration, including increases in O3. Despite the majority of global urban growth occurring in LMIC, there are distinct geographical gaps in air pollution data and, where it is available, differing approaches to analysis and reporting.