Despite considerable air pollution prevention and control measures that have been put into practice in recent years, outdoor air pollution remains one of the most important risk factors for health outcomes. To identify the potential research gaps, we conducted a scoping review focused on health outcomes affected by outdoor air pollution across the broad research area. Of the 5759 potentially relevant studies, 799 were included in the final analysis. The included studies showed an increasing publication trend from 1992 to 2008, and most of the studies were conducted in Asia, Europe, and North America. Among the eight categorized health outcomes, asthma (category: respiratory diseases) and mortality (category: health records) were the most common ones. Adverse health outcomes involving respiratory diseases among children accounted for the largest group. Out of the total included studies, 95.2% reported at least one statistically positive result, and only 0.4% showed ambiguous results. Based on our study, we suggest that the time frame of the included studies, their disease definitions, and the measurement of personal exposure to outdoor air pollution should be taken into consideration in any future research. The main limitation of this study is its potential language bias, since only English publications were included. In conclusion, this scoping review provides researchers and policy decision makers with evidence taken from multiple disciplines to show the increasing prevalence of outdoor air pollution and its adverse effects on health outcomes.

Objectives Outdoor air pollution is a serious environmental problem worldwide. Current systematic reviews (SRs) and meta-analyses (MAs) mostly focused on some specific health outcomes or some specific air pollution. Design This evidence gap map (EGM) is to identify existing gaps from SRs and MAs and report them in broad topic areas. Data sources PubMed, Cochrane, Scopus and Web of Science were searched from their inception until June 2018. Citations and reference lists were traced. Eligibility criteria SRs and MAs that investigated the impact of outdoor air pollution on human health outcomes were collected. This study excluded original articles and qualitative review articles. Data extraction and synthesis Characteristics of the included SRs and MAs were extracted and summarised. Extracted data included authors, publication year, location of the corresponding author(s), publication journal discipline, study design, study duration, sample size, study region, target population, types of air pollution and health outcomes. Results Asia and North America published 93% of SRs and MAs included in this EGM. 31% of the SRs and MAs (27/86) included primary studies conducted in 5–10 countries. Their publication trends have increased during the last 10 years. A total of 2864 primary studies was included. The median number of included primary studies was 20 (range, 7–167). Cohort studies, case cross-over studies and time-series studies were the top three most used study designs. The mostly researched population was the group of all ages (46/86, 53%). Cardiovascular diseases, respiratory diseases and health service records were mostly reported. A lack of definite diagnostic criteria, unclear reporting of air pollution exposure and time period of primary studies were the main research gaps. Conclusions This EGM provided a visual overview of health outcomes affected by outdoor air pollution exposure. Future research should focus on chronic diseases, cancer and mental disorders.

The relationship between environmental regulation (ER) and any associated innovative technologies has been studied in the previous decades; however, the estimated results have varied with no obvious consensus. To analyse what drives the different estimates in existing studies, we investigated the regulation–innovation relationship through a meta-analysis of 1276 estimates reported in 49 studies. In our analysis, 41 aspects of study design were controlled, Bayesian model averaging (BMA), and frequentist model averaging (FMA) methods were used to address model uncertainty problems. Our results suggested that controlling resources and ignoring endogeneity problems both played robust and methodical roles in explaining the differences in individual study results. Additionally, our results also indicated that five factors (middle year, publication year, usage of province-level data, linear model function, and the difference-in-differences (DID) model) consistently explained the differences in the reported estimates. We found that the ER had almost zero influence on technical innovation; more than one flexible policy instrument was required to trigger innovative activities among firms and sectors.