In recent years, the treatment of agricultural wastewater has been an important aspect of environmental protection. The purpose of photocatalytic technology is to degrade pollutants by utilizing solar light energy to stimulate the migration of photocarriers to the surface of photocatalysts and occur reduction-oxidation reaction with pollutants in agricultural wastewater. Photocatalytic technology has the characteristics of high efficiency, sustainability, low-energy and free secondary pollution. It is an environmental and economical method to recover water quality that only needs sunlight. In this paper, the mechanism and research progress of photocatalytic removal of heavy metal ions and antibiotics from agricultural water pollution were reviewed by combining photocatalytic degradation process with agricultural treatment technology. The mechanism of influencing factors of photocatalytic degradation efficiency was discussed in detail and corresponding strategies were proposed, which has certain reference value for the development of photocatalytic degradation.

This work presents a new technique based on modulating the IR absorbance of each substance in a mixture in a chirped manner to reduce the effect of their partial spectral absorption overlap on the accuracy of determining their concentrations. This chirped spectral modulation CSM algorithm can deal with mixtures containing unknown substances rather than the substances whose concentrations are aimed. This novel algorithm, when compared to existing pattern recognition techniques, makes it easy to analyze the constituents of a mixture with high accuracy in the presence of traces of unknown components. It is found that the new algorithm can detect the presence of gas pollutants such as sulfur dioxide, carbon monoxide, carbon dioxide, nitrogen dioxide in a sample containing many other unknown polluting substances. This new algorithm is tested on air samples composed of predetermined percentages of air constituents and the results of calculations are compared with those of classical least squares CLS pattern recognition algorithm. The comparison showed that the new algorithm can detect down to very small traces of harmful gases such as NO₂, and SO₂, at least one order of magnitude less than those detected by the CLS approach. Finally, the new algorithm is used to examine collected air samples from an industrial zone, and in the middle and at the exit of a road tunnel in Riyadh area which showed that the percentages of sulfur dioxide, nitrogen dioxide, and carbon monoxide are well below the safe levels.

果木炭是一种常见的燃料, 其燃烧过程中产生的气体和烟尘气溶胶会影响环境空气质量并损害人体健康, 因此对果木炭燃烧过程中空气成分进行检测与分析具有重要意义。采用激光诱导击穿光谱 (LIBS) 技术对果木炭燃烧时的空气、烟尘气溶胶进行检测, 同时检测果木炭及其燃烧灰烬作为辅助分析。对四种样品的谱线进行标定, 发现果木炭燃烧时空气中碳浓度增大, 生成的气溶胶中含有Ca、Mg、K、Si等元素。果木炭和灰烬的元素组成较为相似, 均含有C、Fe、Mg、Ca、Sr、K、Na和Ba等元素, 果木炭光谱中C、H元素谱线强度均高于灰烬。此外, 结合机器学习算法对有无果木炭燃烧时的空气进行区分, 选取C、CN分子特征谱线所在的波段作为聚类分析的原始特征。主成分分析 (PCA) 结果表明在有无果木炭燃烧两种条件下的空气能被较好地区分, 证明LIBS结合PCA技术能有效地识别果木炭的燃烧并检测果木炭燃烧造成的空气污染。进一步利用 LIBS 结合机器学习算法对果木炭及其燃烧灰烬进行区分, 发现区分效果良好, 为果木炭燃烧后的回收利用提供了参考。

基于光在长光程吸收池中的传输特性，设计了一套新型的大气污染颗粒物消光模拟测量系统。该系统由消光测量装置和大气污染颗粒物模拟装置构成。消光测量装置主要由激光器、开放式Herriot长光程吸收池和光功率计构成。在消光测量装置中，开放式Herriot长光程吸收池将某一波长的光经固定角度的镜片多次反射达到增大光程的目的；同时有利于对其内部反射镜表面的清洁，提高消光测量的灵敏度；还能够实时检测用于消光的颗粒物浓度。消光系数通过吸收池入口和出口处监测到的光功率计算获得，光功率的测量中利用差分法降低了激光器本身能量波动带来的误差，提高消光系数测量的准确性。通过与真实大气雾霾情况下激光雷达测量到的消光系数进行对比，验证了所搭建消光模拟测量系统的合理性。