School of Design, Shanghai Jiao Tong University, Shanghai 200240, China.
School of Design, Shanghai Jiao Tong University, Shanghai 200240, China.
Sci Total Environ. 2023 Apr 15;869:161677. doi: 10.1016/j.scitotenv.2023.161677. Epub 2023 Jan 24.
Landscape classification methods significantly impact the exploration of the mechanism of the relationship between landscapes and atmospheric particulate matter. This study compared the local climate zones (LCZs) and traditional land use/cover change (LUCC) landscape classification methods in explaining spatial differences in concentrations of atmospheric particulate matter (PM and PM) and explored the mechanisms involved in how landscape elements affect atmospheric particulate matter. This was done by establishing a PM and PM land use regression (LUR) model of LCZ and LUCC landscapes under low, typical, and high particle concentration gradients in urban and suburban areas. The results show that under an LCZ classification system, the number of patches in the urban area of Shanghai was 548 times higher than that of a LUCC system. Moreover, LCZs were successfully established for LUR models in 12 scenarios, while only five models were established for LUCC, all of which were suburban models. The R of the LUR model based on the LCZ landscape and atmospheric particulate matter was mostly higher than that of the LUCC. For unnatural landscapes, the LUCC demonstrated that an urbanized environment positively affects the concentration of atmospheric particles. However, the LCZ analysis found that areas with high-density buildings have a positive effect on atmospheric particles, while most areas with low-density buildings significantly reduced the number of atmospheric particles present. Generally, compared with the traditional LUCC landscape classification method, LCZ integrates Shanghai's physical structure and classifies the urban landscape more accurately, which is closely related to the urban atmospheric particulate matter, especially in the urban area. Because the low-density building area has the same effect on the particulate matter as the natural landscape, the use of low-density buildings is recommended when planning new towns.
景观分类方法对探索景观与大气颗粒物关系的机制有重要影响。本研究比较了局地气候带（LCZ）和传统土地利用/覆盖变化（LUCC）景观分类方法，以解释大气颗粒物（PM 和 PM）浓度的空间差异，并探讨了景观要素影响大气颗粒物的机制。这是通过在城市和郊区的低、典型和高颗粒物浓度梯度下建立 LCZ 和 LUCC 景观的 PM 和 PM 土地利用回归（LUR）模型来实现的。结果表明，在 LCZ 分类系统下，上海市城区的斑块数量比 LUCC 系统高 548 倍。此外，LCZ 成功地在 12 种情景下为 LUR 模型建立了分类，而 LUCC 仅为 5 种郊区模型。基于 LCZ 景观和大气颗粒物的 LUR 模型的 R 值大多高于 LUCC。对于非自然景观，LUCC 表明城市化环境对大气颗粒物浓度有积极影响。然而，LCZ 分析发现，高密度建筑区域对大气颗粒物有积极影响，而大多数低密度建筑区域则显著减少了大气颗粒物的数量。总体而言，与传统的 LUCC 景观分类方法相比，LCZ 整合了上海的物理结构，更准确地对城市景观进行分类，与城市大气颗粒物密切相关，特别是在城市地区。由于低密度建筑区域对颗粒物的影响与自然景观相同，因此在规划新城镇时建议使用低密度建筑。
