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Agricultural land use for export commodities leads to significant biodiversity impacts. A spatially detailed assessment of these impacts is crucial for implementing effective mitigation policies. Using cocoa cultivation and exports in Côte d'Ivoire as an example, we present a novel framework that combines earth observations, enhanced landscape-scale biodiversity models, and subnational export supply chain data sets to track the tele-connected potential biodiversity impacts of export groups and importing countries. We found that cocoa cultivation accounts for â¼44% of the biodiversity impacts in Côte d'Ivoire's cocoa cultivation areas, with >90% attributable to cocoa exports. The top 10 importing countries account for â¼84% of these impacts. Our method offers improved spatial detail compared to the existing approaches, facilitating the identification of biodiversity impact hotspots. Additionally, the biodiversity impacts of agroforestry cocoa are not always lower compared to full-sun cocoa, especially when agroforestry systems are established in regions of high biodiversity importance. Our transferable framework provides a comprehensive understanding of biodiversity footprint and promotes informed decision-making for sustainable agricultural production, processing, and trade. Our framework's application is currently constrained by the scarcity of detailed supply chain data sets; we underscore the urgent need for improved supply chain transparency to fully unlock the framework's potential.
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Agricultura , Biodiversidad , Cacao , Côte d'IvoireRESUMEN
Optimizing urban form through urban planning and management policies can improve air quality and transition to demand-side control. Nitrogen dioxide (NO2) in the urban atmosphere, mainly emitted by anthropogenic sources such as industry and vehicles, is a key precursor of fine particles and ozone pollution. Both NO2 and its secondary pollutants pose health risks for humans. Here we assess the interactions between urban forms and airborne NO2 pollution in different cities with various stages of urbanization in the Yangtze River Delta (YRD) in China, by using the machine learning and geographical regression model. The results reveal a strong correlation between urban fragmentation and tropospheric NO2 vertical column density (TVCD) in YRD cities in 2020, particularly those with lower or higher levels of urbanization. The correlation coefficients (R2) between NO2 TVCD and the largest patch index (a metric of urban fragmentation) in different cities are greater than 0.8. For cities at other urbanization stages, population and road density are strongly correlated with NO2 TVCD, with an R2 larger than 0.61. This study highlights the interdependence among urbanization, urban forms, and air pollution, emphasizing the importance of customized urban landscape management strategies for mitigating urban air pollution.
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To prevent the spread of the COVID-19 epidemic, the Chinese megacity Wuhan has taken emergent lockdown measures starting on January 23, 2020. This provided a natural experiment to investigate the response of air quality to such emission reductions. Here, we decoupled the influence of meteorological and non-meteorological factors on main air pollutants using generalized additive models (GAMs), driven by data from the China National Environmental Monitoring Center (CNEMC) network. During the lockdown period (Jan. 23 - Apr. 8, 2020), PM2.5, PM10, NO2, SO2, and CO concentrations decreased significantly by 45 %, 49 %, 56 %, 39 %, and 18 % compared with the corresponding period in 2015-2019, with contributions by S(meteos) of 15 %, 17 %, 13 %, 10 %, and 6 %. This indicates an emission reduction of NOx at least 43 %. However, O3 increased by 43 % with a contribution by S(meteos) of 6 %. In spite of the reduced volatile organic compound (VOC) emissions by 30 % during the strict lockdown period (Jan. 23 - Feb. 14, 2020), which likely reduced the production of O3, O3 concentrations increased due to a weakening of the titration effect of NO. Our results suggest that conventional emission reduction (NOx reduction only) measures may not be sufficient to reduce (or even lead to an increase of) surface O3 concentrations, even if reaching the limit, and VOC-specific measures should also be taken.
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Contaminantes Atmosféricos , Contaminación del Aire , COVID-19 , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Contaminación del Aire/prevención & control , China , Control de Enfermedades Transmisibles , Monitoreo del Ambiente , Humanos , Material Particulado/análisis , SARS-CoV-2RESUMEN
Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations were operated from 02 to 21 December 2018 in Leshan, southwest China, to measure HONO, NO2 and aerosol extinction vertical distributions, and these were the first MAX-DOAS measurement results in Sichuan Basin. During the measurement period, characteristic ranges for surface concentration were found to be 0.26-4.58 km-1 and averaged at 0.93 km-1 for aerosol extinction, 0.49 to 35.2 ppb and averaged at 4.57 ppb for NO2 and 0.03 to 7.38 ppb and averaged at 1.05 ppb for HONO. Moreover, vertical profiles of aerosol, NO2 and HONO were retrieved from MAX-DOAS measurements using the Heidelberg Profile (HEIPRO) algorithm. By analysing the vertical gradients of pollutants and meteorological information, we found that aerosol and HONO are strongly localised, while NO2 is mainly transmitted from the north direction (city center direction). Nitrogen oxides such as HONO and NO2 are important for the production of hydroxyl radical (OH) and oxidative capacity in the troposphere. In this study, the averaged value of OH production rate from HONO is about 0.63 ppb/hr and maximum value of ratio between OH production from HONO and from (HONO+O3) is > 93% before12:00 in Leshan. In addition, combustion emission contributes to 26% for the source of HONO in Leshan, and we found that more NO2 being converted to HONO under the conditions with high aerosol extinction coefficient and high relative humidity is also a dominant factor for the secondary produce of HONO.
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Contaminantes Atmosféricos , Contaminantes Atmosféricos/análisis , China , Ciudades , Compuestos de Nitrógeno , Dióxido de Nitrógeno/análisis , Ácido Nitroso/análisisRESUMEN
Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations were performed from 27 December 2018 to 16 January 2019 in Changshou, one of subdistricts of Chongqing, China. Primary atmospheric pollutant in Changshou during wintertime was PM2.5, whose contribution averaged about 70.15% ± 9.5% of PM10. The ratio of PM2.5/PM10 decreased when PM2.5 pollution became worse, and it should attribute to biomass burning and the contribution of hygroscopic growth and enhanced heterogeneous chemistry under high relative humidity condition. Moreover, nitrogen dioxide (NO2), formaldehyde (HCHO) and glyoxal (CHOCHO) vertical profiles during the campaign period were retrieved separately. TROPOMI HCHO vertical column densities (VCDs) and MAX-DOAS HCHO VCDs were correlated well (R = 0.93). In order to identify the sources of volatile organic compound (VOC) in Changshou, the ratio of CHOCHO to HCHO (RGF) in five different layers were estimated. The estimated daily averaged RGF were 0.0205 ± 0.0077, 0.0727 ± 0.0286, 0.0864 ± 0.0296, 0.0770 ± 0.0275 and 0.0746 ± 0.0263 in 0-100 m, 100-200 m, 300-400 m, 500-600 m and 700-800 m layers, respectively. The estimated RGF will increase when biomass burnings were dominated. Using NO2 as a tracer of anthropogenic emissions, we found the RGF values gradually decrease with the increase of NO2 levels. RGF values in 0-100 m layer and all the other upper layers are 0.015-0.025 and 0.06-0.14, and that means the dominant sources of VOCs in 0-100 m layer and all the other upper layers are biogenic emission and anthropogenic emission (especially biomass burning), respectively. In addition, we found that RGF has site dependence which is in compliance with several previous studies.