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Now that it is breaking out chemical sales again, Shell rejoins the Global Top 50 this year after a 5-year hiatus. Rongsheng Petrochemical, which makes polyester chemicals, debuts this year. The former DowDuPont agricultural chemical business, Corteva Agriscience, made the cut as well.
The Japanese chemical maker has emphasized green projects of late. In June, it signed an agreement to use Ginkgo Bioworks’ synthetic biology capabilities to improve the production of an undisclosed biobased chemical and to make other Sumitomo Chemical products. Sumitomo’s similar relationship with Zymergen resulted in a biobased film for displays and touch screens. Sumitomo is also building a pilot plant in Chiba, Japan, that will make ethylene from ethanol supplied by Sekisui Chemical. In addition, Sumitomo is planning a facility in Singapore that will make methanol from carbon dioxide and hydrogen. To investigate even more technologies with low environmental impact, Sumitomo is building a research facility in Chiba.
Recent years have seen Chinese petrochemical producers, often involved in the polyester supply chain, join the Global Top 50. Hengli Petrochemical is one of those firms. And now Rongsheng Petrochemical is another. The company is one of the largest producers of purified terephthalic acid in the world, with 13 million metric tons of capacity at plants in Dalian, Ningbo, and Hainan, China. It also makes polyester resin and fiber. It is an investor in Zhejiang Petrochemical, a large oil refinery and petrochemical complex that is currently starting up.
Figure 1 depicts absolute cirrus cloud frequencies over water throughout Southeast Asia and the Maritime Continent derived from 2006–15 satellite-based Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP; Winker et al. 2010), level-2, 5-km cloud profile datasets. Cirrus are defined here, as with MPLNET, based on a maximum −37°C cloud-top temperature, as advocated in Campbell et al. (2015). Total cirrus cloud occurrence near Singapore approaches 80% (Fig. 1a). Following Sassen and Cho (1992), over half of these clouds are translucent: optically thin cirrus (OTC) exceed 30% occurrence [Fig. 1b; 0.03 ≤ cloud optical depth (COD) < 0.30], while subvisual cloud (SVC) occurrence (COD < 0.03) is only slightly lower (Fig. 1c).
Annual cirrus cloud absolute occurrence frequencies over the Southeast Asian Maritime Continental basin derived from level-2 NASA CALIOP 5-km cloud profile data products from 2006 to 2015 for all (a) cirrus clouds (see text for specific definition), (b) optically thin cirrus (0.03 ≤ COD < 0.30), and (c) subvisual cirrus (COD ≤ 0.03). Singapore is denoted by the star.
Annual cirrus cloud absolute occurrence frequencies over the Southeast Asian Maritime Continental basin derived from level-2 NASA CALIOP 5-km cloud profile data products from 2006 to 2015 for all (a) cirrus clouds (see text for specific definition), (b) optically thin cirrus (0.03 ≤ COD < 0.30), and (c) subvisual cirrus (COD ≤ 0.03). Singapore is denoted by the star.
Annual cirrus cloud absolute occurrence frequencies over the Southeast Asian Maritime Continental basin derived from level-2 NASA CALIOP 5-km cloud profile data products from 2006 to 2015 for all (a) cirrus clouds (see text for specific definition), (b) optically thin cirrus (0.03 ≤ COD < 0.30), and (c) subvisual cirrus (COD ≤ 0.03). Singapore is denoted by the star.
Absolute and relative single-layer annual and monthly cirrus cloud occurrence rates during 2010 and 2011 in MPLNET observations at Singapore are listed in Fig. 2 alongside histograms of relative occurrence as a function of cloud-top height (CTH) and COD for the 30-sr sample. The Singapore MPL operated on 357 and 363 days in 2010 and 2011, respectively. 15 208 (8% absolute frequency) and 18 234 (10%) single-layer clouds were analyzed for daytime TOA CRF each respective year. Seasonal stats and histograms are shown for February–April (FMA; 3770 and 3920), May–July (MJJ; 4656 and 6594), September–November (SON; 4085 and 5179), and December–February (DJF; 2897 and 2541). Total cirrus cloudiness (i.e., single and multilayer) was 28% and 27%, respectively, varying in height between 10 and 18 km MSL. Relative sample distributions versus COD were consistent across both years: 16%/15% SVC, 64%/65% OTC + SVC, and 35%/35% COD > 0.30. There was a distinct tendency, however, toward lower CTH during 2011 (14.09-km average CTH in 2010 vs 13.45 km in 2011).
Annual and seasonal relative cirrus cloud occurrence histograms for MPLNET observations at Singapore during (top) 2010 and (bottom) 2011 vs CTH, drawn as functions of COD (30-sr solutions shown only) with corresponding absolute and relative occurrence frequencies and mean average annual CTH (see insets): (a),(f) annual; (b),(g) FMA; (c),(h) MJJ; (d),(i) August–October (ASO); (e),(j) NDJ.
Annual and seasonal relative cirrus cloud occurrence histograms for MPLNET observations at Singapore during (top) 2010 and (bottom) 2011 vs CTH, drawn as functions of COD (30-sr solutions shown only) with corresponding absolute and relative occurrence frequencies and mean average annual CTH (see insets): (a),(f) annual; (b),(g) FMA; (c),(h) MJJ; (d),(i) August–October (ASO); (e),(j) NDJ.
Annual and seasonal relative cirrus cloud occurrence histograms for MPLNET observations at Singapore during (top) 2010 and (bottom) 2011 vs CTH, drawn as functions of COD (30-sr solutions shown only) with corresponding absolute and relative occurrence frequencies and mean average annual CTH (see insets): (a),(f) annual; (b),(g) FMA; (c),(h) MJJ; (d),(i) August–October (ASO); (e),(j) NDJ.
Consideration of single-layer cirrus cloud subsets limits the potential for signal attenuation effects and aliasing of upper-cloud-layer features. Additional constrains on the data sample are present. For instance, as compared with the 40/60 distribution in daytime versus nighttime profiles at the Greenbelt, Maryland, site investigated in Campbell et al. (2016), Singapore experienced a 45/55 split across both 2010 and 2011 (presumably because of frequently lower SZA). Unlike the former sample, however, where an equal 40/60 split was detected in relative cloud occurrence, a 30/70 split was found at Singapore between day and night. This implies day/night cloud sampling bias present, either from lower daytime instrument sensitivity or greater low cloudiness during day that inhibited regular profiling of the upper troposphere. Further to this point, though it likely does not reconcile the full effect, a shutter was used to protect the instrument from extremely low solar zenith angles incident near solar noon on site. The instrument was thus in standby mode for approximately 60 min centered on solar noon each day, the lidar siesta time of the tropics (Sassen et al. 2005).
Cirrus cloud frequency-normalized TOA CRF (left axis; red) vs COD at Singapore. Estimates are shown for both the 20- (red) and 30-sr (dark blue) bookend estimates to the lidar extinction-to-backscatter ratio for (top), (top middle) 2010 and (bottom middle), (bottom) 2011 over (a),(c) water and (b),(d) land, including corresponding relative cloud frequency (log10 based) vs COD (right axis; light blue).
Cirrus cloud frequency-normalized TOA CRF (left axis; red) vs COD at Singapore. Estimates are shown for both the 20- (red) and 30-sr (dark blue) bookend estimates to the lidar extinction-to-backscatter ratio for (top), (top middle) 2010 and (bottom middle), (bottom) 2011 over (a),(c) water and (b),(d) land, including corresponding relative cloud frequency (log10 based) vs COD (right axis; light blue).
Cirrus cloud frequency-normalized TOA CRF (left axis; red) vs COD at Singapore. Estimates are shown for both the 20- (red) and 30-sr (dark blue) bookend estimates to the lidar extinction-to-backscatter ratio for (top), (top middle) 2010 and (bottom middle), (bottom) 2011 over (a),(c) water and (b),(d) land, including corresponding relative cloud frequency (log10 based) vs COD (right axis; light blue).
Table 2.Seasonal relative net TOA cirrus CRF estimates at Singapore (W m−2), solved as function of varying surface albedo, lidar ratio solutions for MPLNET cloud extinction, and year.
It is compelling that the minimum 30-sr estimate over water in 2011 (−4.51 W m−2; NDJ) stands in direct contrast with the maximum 30-sr estimate that year over land (4.01 W m−2; FMA). Considering the overland/water estimates seasonally in tandem with the net annual estimates from Fig. 3, and notwithstanding the hypothetical presence of a meridional/hemispheric gradient in forcing [though these results reinforce the likelihood of such a phenomenon relative to the midlatitude estimates in Campbell et al. (2016)], it is apparent that there exist additional zonal gradients in cirrus cloud net daytime TOA CRF induced by dominant surface type. Whereas Campbell et al. (2016) recognize this process meridionally relative to polar ice coverage, they underestimate the simpler difference between land and open waters. Further, though they report slightly positive midlatitude values over land, the nature of the gradient appears fundamentally different over water. Given the slightly positive estimates over water at Singapore, cirrus likely induce negative daytime TOA CRF over much of the global oceans, presuming forcing turns negative meridionally at a lower latitude than over land.