通过分析2013—2017年海口市风向频率、地面PM_(2.5)浓度及海口市所处北部湾地理位置,确定12月为北部湾对海口市最不利风向时间段.利用中尺度气象模式(WRF,Weather Research Forecast)驱动空气质量模型(CMAQ,Community Multi-scale Air Quality),设置一系列数值模拟情景,深入分析北部湾人为源对海口市PM_(2.5)浓度影响.结果表明:WRF/CMAQ能很好地再现北部湾气象场和PM_(2.5)浓度的时空分布.2013年12月,北部湾人为源对海口市PM_(2.5)平均贡献率约为45.4%,其中约有90%来源于海口市自身人为源,约有10%来源于广东广西片区,海南片区除海口外其余市县贡献可忽略不计.污染时段,北部湾和海口市自身贡献率均下降,平均贡献率分别为40%和36%,表明污染时段海口市PM_(2.5)主要源区不仅来自北部湾.通过分析后向轨迹,发现污染时段均会经过一个关键区——珠三角区域,表明珠三角区域很有可能也是造成2013年12月海口市PM_(2.5)污染的主要源区.清洁时段,北部湾和海口市自身贡献率均上升,平均贡献率分别为52%和48%,表明北部湾对海口市PM_(2.5)浓度影响在清洁时段更显著.因此,北部湾未来产业规划值得关注,因为这些产业很有可能使目前海口市清洁时段变为污染时段,导致空气质量下降. 相似文献
论文应用第5次耦合模式比较计划(Coupled Model Intercomparison Project Phase 5,CMIP5)中5个全球气候模式(Global Climate Models,GCMs)和3种典型浓度路径(Representative Concentration Pathways,RCPs)在全球增温1.5℃和2.0℃下的预估结果,分析了淮河中上游地区未来的气候变化特征。进一步基于SWAT(Soil and Water Assessment Tool)水文模型定量预估了气候变化对该区域径流量的影响,并量化了预估结果的不确定性。结果表明:SWAT模型在淮河中上游对月径流量具有较好的模拟能力。在全球增温1.5℃和2.0℃下,淮河中上游年平均气温分别较基准期(1986—2005年)增加1.1℃和1.7℃;年降水量较基准期分别相应增加4%和7%;基于SWAT模型预估的年径流量较基准期分别增加5%和8%。未来气候变化不会改变月径流分布特征,年内径流仍集中在盛夏和初秋(6—9月)。预估的月丰水流量明显增加,尤其当全球增温达到2.0℃后,出现洪涝的风险明显增大。未来降水量和径流量预估都存在较大的不确定性,不确定性主要来源于GCMs,在全球增温2.0℃下预估的不确定性更大。 相似文献
Objectives: This study reports the results of a pilot program in Kenosha County that used a combination of direct biomarkers extracted from blood spots and nails to monitor repeat intoxicated drivers for their use of alcohol and drugs with a detection window spanning from 3 weeks to several months. The objectives were to test whether the direct biomarkers phosphatidylethanol (PEth), ethylglucuronide (EtG), and 5 drug metabolites would (1) help assessors obtain a more objective evaluation of repeat offenders during the assessment interview, (2) allow for timely identification of relapses and improve classification of drivers into risk categories, and (3) predict recidivism by identifying offenders most likely to obtain a subsequent operating while intoxicated (OWI) offense within 4 years of enrollment in the program.
Methods: All (N = 261) repeat offenders were tested using PEth obtained from blood spots and EtG obtained from fingernails; 159 participants were also tested for a 5 drugs of abuse nail panel. Drivers were tested immediately after the assessment interview (baseline) and at 3, 6, 9, and 12 months after baseline. Based on biomarker results and self-reports of abstinence, offenders were classified into different risk categories and required to follow specific testing timelines based on the program's decision tree.
Results: The baseline analysis shows that 60% of drivers tested positive for alcohol biomarkers (EtG, PEth, or both) at the assessment interview, with lower detection rates (0–11%) for the 5 drug metabolites. The comparison of biomarkers results to self-reports of abstinence identified 28% of all offenders as high risk and assigned them to more frequent testing and more intense monitoring. The longitudinal analysis shows that 56% (completers) of participants completed the program successfully and the remaining 44% (noncompliant) terminated prematurely. Two thirds (68%) of the completers were able to reduce or control their drinking and one third relapsed at least one time during their mandated monitoring periods. After a brief intervention by the assessors, 79% of relapsers tested negative for biomarkers in their repeat tests. The rearrest analysis showed that offenders classified in the noncompliant and relapsers groups were 7 times more likely to receive a new OWI 4 years after enrollment compared to drivers classified as abstainers or controllers. Refractory drivers were monitored the longest and reported no subsequent rearrests.
Conclusion: These findings demonstrate the benefits of more individualized interventions with repeat OWI offenders and calls for further development of multimodal approaches in traffic medicine including those that use direct alcohol biomarkers as evidence-based practices to reduce recidivism. 相似文献