兰州市大气降尘中PAHs主要来源及其分布特征

对兰州市春季不同功能区大气降尘有机质中PAHs种类的分析,检出了大气降尘中有机质USEPA优控PAHs有11种以上,含量较高的萘、荧蒽、菲、芘、,占各采样点PAHs总量的70%以上。源解析表明,兰州市各功能区大气降尘中PAHs来源不仅有较高的燃煤源、交通源(汽车尾气),同时PAHs的组成与分布也在很大程度上受到采样点周围居民居住环境的影响。     

Formation mechanisms of nitrous acid (HONO) during the haze and non-haze periods in Beijing, China

As an important precursor of hydroxyl radical (OH), nitrous acid (HONO) plays a significant role in atmospheric chemistry. Here, an observation of HONO and relevant air pollutants in an urban site of Beijing from 14 to 28 April, 2017 was performed. Two distinct peaks of HONO concentrations occurred during the observation. In contrast, the concentration of particulate matter in the first period (period Ⅰ) was significantly higher than that in the second period (period Ⅱ). Comparing to HONO sources in the two periods, we found that the direct vehicle emission was an essential source of the ambient HONO during both periods at night, especially in period Ⅱ. The heterogeneous reaction of NO₂ was the dominant source in period Ⅰ, while the homogeneous reaction of NO with OH was more critical source at night in period Ⅱ. In the daytime, the heterogeneous reaction of NO₂ was a significant source and was confirmed by the good correlation coefficients (R²) between the unknown sources (P_unknown) with NO₂, PM_2.5, NO₂ × PM_2.5 in period Ⅰ. Moreover, when solar radiation and OH radicals were considered to explore unknown sources in the daytime, the enhanced correlation of P_unknown with photolysis rate of NO₂ and OH ($J_{{\mathrm{NO}}_2}$ × OH) were 0.93 in period Ⅰ, 0.95 in period Ⅱ. These excellent correlation coefficients suggested that the unknown sources released HONO highly related to the solar radiation and the variation of OH radicals.     

Development of a framework to implement a recycling program in an elementary school

This study developed a system to plan, evaluate, implement, and monitor a waste reduction and source-separation program, which was then tested through a field study in a New York City elementary school. Despite efforts to implement integrated waste management in elementary schools, appropriate planning tools that document performance and support program development are lacking. To fill this gap, a system for analyzing existing programs was developed. After identifying the phases required for a successful program, a scoring system was developed to quantify the performance of existing programs. To assess existing protocol, recommendations from leading municipalities were reviewed, and the performance of existing programs was quantified within the scoring system. The existing protocol was found to contain similarities, but an overarching approach was needed to connect the provisions with programs that have been successfully deployed. From this analysis, a scoring system was developed to take into consideration the major elements needed for a waste reduction and source-separation plan, colloquially referred to as a recycling plan, as well as the specifics of implementation. This system allows for the review of programs already developed, and can pinpoint limitations prior to implementation. The framework was evaluated through the test case school, with both waste audit data and diagrams. From the lessons learned, successful techniques and recommendations for utilizing this framework were created.     

中山市臭氧污染来源解析与敏感性分析

利用数值天气预报模式和嵌套网格空气质量预报系统的来源解析模块（WRF NAQPMS/OSAM）对中山市2019年9月1次臭氧（O₃）污染过程进行了模拟分析，并对O₃来源进行了解析。结果表明，WRF-NAQPMS/OSAM模型能较好地模拟出该时段的O₃浓度。此次污染过程区域传输对中山市O₃浓度贡献显著，平均贡献比例为82.9%，本地平均贡献比例为17.1%，对中山市O₃贡献最大的2个来源分别是溶剂源和交通源，平均贡献占比分别为43.0%和42.7%。另外，工业源的贡献也不可忽略，平均贡献占比为11.0%。中山市O₃总体上处于挥发性有机物（VOCs）控制区，结合臭氧生成潜势（OFP）分析和源解析结果，溶剂源、交通源和工业源排放的甲苯、间/对二甲苯、邻二甲苯、1，2，3-三甲苯、正丁烷和异戊烷对O₃形成贡献显著，是中山市O₃污染治理应注意的重要前体物。建议中山市建立以VOCs控制为主导，VOCs和氮氧化物（NO_X）协同控制的长期O₃防控策略。     

An improved grey wolf optimizer algorithm for identification and location of gas emission

Identification of the leakage of hazardous gases plays an important role in the environment protection, human health and safety of industry production. However, lots of current optimization algorithms, such as particle swarm optimization (PSO) and Grey Wolf Optimizer (GWO), suffer from poor global optimization capability and estimation accuracy. In this work, a hybrid differential evolutionary and GWO (DE-GWO) algorithm is proposed. Tested by simulation cases and Prairie Grass emission experimental data, DE-GWO shows higher estimation accuracy than GWO. Compared with the other four optimization algorithms, DE-GWO exhibits finer robust stability under different population sizes, fewer iterations, as well as higher estimation accuracy with fewer search agents. Importantly, simulation results demonstrate that DE-GWO is more suitable to apply in the scene with a small number of sensors. Therefore, the proposed in this paper outperforms other optimization algorithms for the gas emission inverse problem. DE-GWO can provide reliable estimation towards gas emission identification and positioning, which shows huge potential as the data analysis module of real-time monitoring and early warning system.     

2016-2020年珠海市金湾区集中式饮用水水源地环境质量变化特征

根据2016-2020年珠海市金湾区集中式饮用水水源地的监测数据,采用单因子评价法、综合污染指数法和综合营养状态指数法对金湾区黄绿背水库、爱国水库和木头冲水库环境质量变化趋势及特征进行分析评价.结果表明,2016年3个水库的综合污染指数最高,水质最差,超标因子为总磷,除了 2016年黄绿背水库超出《地表水环境质量标准》...